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A 



RAND 



The Effects of the Florida 
Medicaid Eligibility Expansion 
for Pregnant Women 

Stephen H. Long and M. Susan Marquis 



December 1995 



Health Care Financing Administration and March of Dimes Birth 
Defects Foundation 



RAND is a nonprofit institution that seeks to improve public policy through research and analysis. 
RAND's publications do not necessarily reflect the opinions or policies of its research sponsors. 



Ill 



CONTENTS 



LIST OF APPENDICES v 

FIGURES V ii 

TABLES i x 

EXECUTIVE SUMMARY x i 

ACKNOWLEDGMENTS xv 



INTRODUCTION 1 

BACKGROUND 2 

Previous Studies 2 

Expansions for Pregnant Women in Florida 4 

DATA AND METHODS 6 

Data 6 

Methods 7 

RESULTS 16 

Aggregate Analysis 16 

Person Level Analysis of Outcomes 25 

DISCUSSION 31 

Findings From the Florida Expansion Compared to Other Studies ... 31 

Policy Implications 32 

Directions for Further Research 34 

REFERENCES 37 



LIST OF APPENDICES 



A. SELECTION OF THE STUDY STATE 

B. IMPLEMENTING THE MEDICAID EXPANSIONS FOR PREGNANT WOMEN: THE 

EXPERIENCE IN FLORIDA 

C. EVALUATION OF A MEDICAID ELIGIBILITY EXPANSION IN FLORIDA: 

DEVELOPING THE DATABASE 

D. ESTIMATION FOR AGGREGATE ANALYSIS 

E. EXPLANATORY VARIABLES AND REFERENCE POPULATION 

F. REGRESSION RESULTS 



Vll 



FIGURES 



Figure l--Distribution of Deliveries by Primary Payer 17 

Figure 2--Distribution of Prenatal Care Visits Among Medicaid 

Women by Site of Care 19 

Figure 3 --Distribution of Source of Financing by Type of Hospital 

and Study Period 21 

Figure 4--Percent of Medicaid Expansion Population Enrolling in 

First Trimester, by Time Period 26 



IX 



TABLES 



Table 1. Predicted Values for Comparing Insurance Groups 15 

Table 2 . Deliveries by Primary Delivery Payer 16 

Table 3. Ambulatory Prenatal Visits by Primary Delivery Payer 18 

Table 4. Maternal Hospital Admissions by Primary Delivery Payer 22 

Table 5 . Flow of Payments for Maternity Care 24 

Table 6. Prenatal Care and Birth Outcomes for Low- Income Women 

by Insurance Status 28 

Table 7 . Prenatal Care and Birth Outcomes for Medicaid Women 

Using Different Delivery Systems, 1991 30 



XI 



EXECUTIVE SUMMARY 



OBJECTIVES 

This study investigates the effects of a Medicaid eligibility- 
expansion on the financing of maternity care, on the use of prenatal 
care services, and on birth outcomes for newly entitled women. It also 
examines its effect on the role of other government programs that 
provide prenatal care--specif ically, the public health system. We study 
the experience in Florida. This is a populous state with a large 
Medicaid population. It introduced a substantial eligibility expansion 
in 1989, raising the income threshold for pregnant women from 100 
percent of poverty to 150 percent of poverty. Florida has traditionally 
relied heavily on county health departments to serve low-income women, 
and thus is a good state in which to study interactions between Medicaid 
financing changes and the publicly financed direct-delivery system. 

DATA AND METHODS 

We study prenatal care and birth outcomes in Florida for deliveries 
in the period July 1988 through June 1989 and in calendar year 1991. 
This includes the twelve month period just prior to the income 
eligibility expansion and a full calendar year beginning eighteen months 
after the expansion was first implemented. Data for the analysis come 
from a variety of sources. These include: the Florida birth and death 
certificates, the hospital discharge abstracts, Medicaid eligibility and 
claims files, individual encounter records for personal health services 
provided by each of the county health departments in the state, the 
American Hospital Association annual survey files for Florida hospitals, 
and the 1990 Census. The birth and fetal death records for all women in 
.the state, regardless of payer, define our study universe. We developed 
algorithms to match records in the other databases for women who 
delivered in one of our study periods to the record for that birth in 
the vital statistics database. 

Our evaluation of the expansion consists of two parallel analyses. 
First, we investigate aggregate changes in the quantity of care, 



Xll 



delivery provider, and sources of financing maternity care in the two 
periods. Then we compare the amount and timing of prenatal care and the 
birth outcomes for a woman covered by the Medicaid program and an 
uninsured woman in each period to estimate the effect of extending 
Medicaid coverage. Finally, we contrast birth outcomes for Medicaid 
women who use the county health departments for their prenatal care with 
outcomes for women using another delivery system. 

RESULTS 

Aggregate Analysis . The Medicaid expansion in Florida led to a 
substantial shift in the source of payment for deliveries between the 
baseline period and 1991. The number of births covered annually by 
Medicaid rose by 47 percent over this time period. Most of this 
increase represents women who otherwise would have been uninsured for 
their prenatal care and delivery. 

The additional prenatal care financed by Medicaid as a result of 
these expansions was accommodated almost entirely by county health 
departments. The number of prenatal visits provided by the county 
health departments over this period increased by 100 percent. Thus, the 
Medicaid expansion did not substitute for care already provided by 
county health departments, but rather the Medicaid financing appears to 
have provided the financial resources to expand the capacity of the 
counties to deliver prenatal care to low-income women. 

The Medicaid expansion had a much smaller effect on the type of 
hospital women used for their care; although there was a small shift in 
care away from public hospitals toward both voluntary and proprietary 
hospitals. Although there was little change in the number of admissions 
of pregnant women to public and voluntary hospitals, there was a sizable 
decrease in the share of patients who are self -pay. As a result, 
hospitals benefited from the expansions. Their maternity-related 
revenues grew by 5 percent, whereas the admissions for maternity care 
were fairly constant . 

Person Level Analysis of Outcomes . We find evidence that women 
enrolled in the Medicaid expansion use more prenatal care and have 
better birth outcomes than they would if they remained uninsured. 



Xlll 



Although providing Medicaid benefits to low-income women serves to 
improve their access to care, there remains a substantial gap between 
Medicaid enrollees and those with private insurance in use of prenatal 
care and in birth outcomes . 

The county health departments may have been a significant factor in 
the improved outcomes for the expansion population. As noted above, 
most of the additional Medicaid financed prenatal care was provided by 
the counties. In addition, we find that Medicaid women using the county 
health departments for their prenatal care experienced significantly 
better health outcomes than women using another delivery system. 

DISCUSSION 

We come to stronger conclusions about the benefits of the 
expansions than most of the earlier literature. Methodological 
differences may account for some of this. The large sample size and our 
use of area income to identify the subset of women who are most likely 
to be uninsured and eligible under the expansion are methodological 
improvements over other studies. In addition, we rule out selection as 
the sole explanation of our results by also studying differences between 
Medicaid women enrolled because of their AFDC participation, as opposed 
to their pregnancy, and the uninsured. On the other hand, the Florida 
experience may have differed from that in other states. The county 
health departments were a significant factor in the Medicaid expansion; 
improvements probably would have been more modest without it. 

Our findings have significance for current policy discussions. 
Congress is considering major changes in federal funding for Medicaid 
and public health. Our results suggest policymakers should be cautious 
about cutting back on the eligibility for the expansion population, 
because the expansions appear to have had a beneficial impact. Second, 
our results emphasize the inter-relationship of expanding insurance 
coverage and providing a delivery system to accommodate peoples' needs. 
In particular, the findings suggest that financing Medicaid eligibility 
expansions by contractions in the public health system and other 
policies to shift care sources to the private delivery system may have 
unintended, unfavorable effects on birth outcomes for low-income women. 






DIRECTIONS FOR FUTURE RESEARCH 

The findings from our study of the 1989 Florida eligibility- 
expansion raise a number of important questions about the effect that 
new directions in Medicaid will have on access to care for low-income 
pregnant women and on their birth outcomes. These new directions 
include further eligibility expansions for higher income women, 
increasing physician fees to encourage use of office-based care, and 
greater emphasis on managed care enrollment. 

• Will eliminating financial barriers have the same effect on 
access to care and outcomes for the near poor--who are the 
subject of the more recent expansions in Florida and other 
states? 

• Does Medicaid eligibility improve access and outcomes for 
important subgroups of pregnant women--especially teenagers and 
women at high risk for poor birth outcomes? 

• What are the likely effects on birth outcomes if increasing 
physician fees leads to a shift to more prenatal care delivered 
by office-based physicians? What are the likely effects on 
birth outcomes for Medicaid beneficiaries of the greater 
emphasis on managed care? 

• Will the effects of the expansions change when the public 
health system cannot expand further to meet the increased 
demand? 

• Does providing care directly to uninsured women through the 
public health system have the same effect on prenatal care use 
and birth outcomes as providing public insurance to pay for 
care received in the private sector? 

Florida remains a good candidate state for study to answer these 
questions. The state has experienced a number of changes in Medicaid 
eligibility and in the delivery system over the period 1988 through 
1994. The questions that we posed above can be addressed with further 
analysis of the database that we have constructed for 1988 through 1991 
or by extending the database to 1994 using the technology that we 
developed in this work. Such a database would be an invaluable source 
for answering the critical questions that are facing policymakers about 
reforming the Medicaid program. 



XV 



ACKNOWLEDGMENTS 



This research was supported by a cooperative agreement from the 
Health Care Financing Administration (18-C-90113/9-01) and a grant from 
the March of Dimes Birth Defects Foundation. Any views expressed herein 
are the authors' and should not necessarily be attributed to the 
sponsors or RAND. The authors are grateful to their project officers-- 
Marilyn Hirsch and Herb Silverman at HCFA and Kay Johnson at the March 
of Dimes--for a great deal of encouragement, assistance, and patience 
over the life of this project. Many people in Florida assisted in 
providing data and helping us understand the f iles--including Meade 
Grigg, Phil Street, and Dan Thompson of the Department of Health and 
Rehabilitative Services; Fred Roberson and Jack Shi of the Medicaid 
program; and Chris Augsburger of the Agency for Health Care 
Administration. Ellen Harrison performed expertly in constructing the 
analysis files; Nancy Allen assisted with the Medicaid data. Finally, 
we are grateful to many people who commented on an earlier draft, 
particularly Feather Davis, Genevieve Kenny, Charles Mahan, and Sarah 
Rosenbaum. 






THE EFFECTS OF THE FLORIDA MEDICAID ELIGIBILITY 
EXPANSIONS FOR PREGNANT WOMEN 



Stephen H. Long and M. Susan Marquis 



INTRODUCTION 

The reduction of infant mortality became a policy priority for the 
federal and state governments in the latter months of 1986. Since then, 
publicly financed perinatal care and delivery systems have undergone 
radical changes. In 1987, state Medicaid programs started to implement 
a series of far-reaching eligibility expansions for low-income pregnant 
women and young children. By July 1994, all states made Medicaid 
benefits available to pregnant women and infants with income below 133 
percent of the federal poverty level, and 33 states used optional 
authority to set the income thresholds for eligibility at higher levels. 
These expansions also stimulated states to simplify Medicaid eligibility 
processing, implement outreach programs, and introduce enhanced prenatal 
care benefit programs in an effort to improve access to prenatal care 
for low- income women and, thereby, to improve birth outcomes and infant 
health. 

The Medicaid eligibility expansions for pregnant women and children 
were the most important policy changes in the program in the 1980s. Yet 
there are only a limited number of studies of the effect of these 
expansions and it is not clear from these studies whether the expansions 
led to an improvement in prenatal care and birth outcomes (Alpha Center, 
1995) . Moreover, to understand the full effect of the interventions it 
is also essential to understand how the Medicaid program changes 
affected other government programs that deliver prenatal care and how 
the expansions affected private payers. The effects on prenatal care 
access and birth outcomes are likely to be quite different if Medicaid 
financed care substitutes for care previously financed and provided 
under other programs, such as Title V or private insurance, rather than 
providing new coverage for those who previously lacked insurance or 
access to other public programs. None of the previous studies, however, 
addresses these substitutions. 






Our objective is to investigate these interactions between the 
Medicaid program and other sources of financing and providing maternal 
health care, and, with this perspective, to study whether pregnant women 
newly entitled to Medicaid coverage received more or earlier prenatal 
care, and whether their birth outcomes were improved. We study the 
experience in Florida. Florida is a good site for this study for a 
number of reasons. It ranks fourth among the states in total 
population, and there are about 200,000 births each year. Florida 
significantly expanded Medicaid eligibility for pregnant women and also 
aggressively implemented other strategies to ensure that women who were 
made eligible by the expansions gained coverage under the program. 
Florida relies heavily on county health departments to provide prenatal 
care to its low-income women, and hence is a good place to study 
interactions between the Medicaid financing changes and the publicly 
financed direct-delivery system. (See Appendix A for a more complete 
discussion of our choice of Florida as the state in which to carry out 
this study) . 

BACKGROUND 

Previous Studies 

Earlier studies measuring the effects of providing Medicaid 
coverage to uninsured pregnant women have produced mixed results. Those 
that measure the change in prenatal care and incidence of adverse birth 
outcomes in a population after expanding the availability of public 
insurance program to low-income women conclude that the expansion did 
not result in improved care or birth outcomes (Piper, Ray, and Griffin, 
1990), even when other temporal changes are accounted for (Haas, 
Udvarhelyi, Morris, and Epstein, 1993). However, measures of the 
effects of the increased access to insurance may be diluted in these 
studies because the comparison groups include women who are not directly 
affected by the expansions and because temporal controls are lacking or 
limited. 

Other studies making concurrent comparisons of pregnant women 
enrolled in public insurance programs with uninsured women provide some 
evidence of improved prenatal care access and birth outcomes for those 



with public insurance coverage. Haas and colleagues (1993) report that 
those enrolled in a state program for low-income pregnant women were 
less likely to initiate care late in the pregnancy and less likely to 
experience adverse birth outcomes than uninsured women. Braveman and 
others (1993) find that Medicaid women have more prenatal care visits 
than the uninsured, though they started care later than the uninsured. 
These cross-section comparisons, however, may be biased if women 
enrolling in the public insurance programs differ from those remaining 
uninsured in ways that are not accounted for. In particular, the 
studies control for demographic characteristics, but do not adjust for 
income differences or health differences that are important correlates 
of use and outcomes (Starfield et al . , 1991; Rosenzweig and Schultz, 
1982) . 

Moreover, expanding the availability of public insurance for low- 
income women may not be enough to improve prenatal care use and birth 
outcomes. Benefits of removing financial barriers to care can only be 
realized if eligible woman enroll in Medicaid and if they enroll early 
in the pregnancy. Piper and others (1994) , for example, found evidence 
that simplifying the Medicaid enrollment process by establishing 
presumptive eligibility led to earlier enrollment in Medicaid, earlier 
initiation of prenatal care, and improvements in the adequacy of care 
for Medicaid patients, although they were not able to identify 
consequent improvements in birth outcomes. Differences between states 
in their success at getting women onto Medicaid early in the pregnancy 
appear to be related to efforts to simplify enrollment procedures. 
California, which made few changes in enrollment procedures, enrolled 
only 39 percent of its Medicaid expansion population in the first 
trimester of pregnancy compared to 54 percent for Michigan, which 
adopted a number of enrollment changes (Alpha Center, 1995) . 

In addition, the content and scope of prenatal care, not just the 
quantity of care, is believed to be an important factor in birth 
outcomes (Starfield, 1985). Some research supports this view. Several 
studies of Medicaid patients find the incidence of low birthweight and 
infant mortality is lower for low-income women who receive prenatal care 
from the public health system, which provides coordinated maternity care 



and related support services, than for other women (Buescher et al., 
1987, 1991, 1992; Thompson et al., 1993; Clarke et al . , 1993). 

Our study addresses the issues raised in the earlier research. We 
combine cross-section and time-series analysis methods. To control for 
self -selection in the cross-section comparisons, we develop a proxy 
measure of income and we distinguish between women whose enrollment in 
the public insurance program is related to the pregnancy versus other 
enrollees. We also control for the mother's health risk. We study a 
state which adopted a number of programs and procedures designed to 
maximize the effectiveness of the improved financial access for low- 
income women. And finally, we compare outcomes for Medicaid women in 
different delivery systems to investigate the effects of content and 
scope of services available. 

Expansions for Pregnant Women in Florida 1 

In October 1987, Florida became one of the first 15 states to take 
advantage of the option that was authorized by Congress as part of the 
Omnibus Budget Reconciliation Act of 1986 (OBRA86) to provide Medicaid 
benefits to pregnant women with income below poverty. Two years later, 
in July 1989, the' state further expanded eligibility for pregnant women 
by increasing the income threshold to 150 percent of poverty. Finally, 
in May 1992, Florida raised the income limits to 185 percent of poverty. 

As a complement to the expansion of financial access to coverage, 
Florida also enacted a broad range of other strategies to help ensure 
that the eligibility expansions had their desired impact. These 
included changes in the Medicaid eligibility determination process, 
outreach and public information campaigns, policies to improve physician 
participation in Medicaid, and technical assistance to county health 
departments to foster more effective Medicaid enrollment and billing 
practices. 

In October 1987, the Medicaid program adopted several changes to 
simplify and streamline the determination of eligibility for pregnant 
women. The processing changes involved: dropping the assets test for 
pregnant women; granting continuous eligibility to pregnant women 



1 This section is based on a report prepared by Ian Hill, which is 
included as Appendix B. 



throughout their pregnancies regardless of changes in income; adopting 
presumptive eligibility, which permits state-selected providers to grant 
immediate, temporary eligibility to low-income pregnant women while the 
formal application is being processed; shortening the application form; 
and outposting Medicaid eligibility workers at health care provider 
sites to facilitate the application for Medicaid benefits. In an effort 
to increase the supply of obstetrical providers from which the newly 
eligible Medicaid beneficiaries could obtain prenatal care, the state 
increased the Medicaid reimbursement rates for prenatal care during the 
late 1980s and early 1990s to encourage greater physician participation 
in the program. The largest single increase occurred in 1988 when the 
global fee for maternity care was increased by more than 250 percent 
(from $315 to $800) . The fee was raised again by 25 percent in 1989 and 
increased 50 percent (to $1500) in 1992. 

However, the strategy that most Florida officials credit with 
having the greatest impact on the state's ability to effectively 
implement the Medicaid expansions was the creation of Technical 
Assistance and Coordination teams (TACTs) between 1988 and 1990. TACTs 
were designed to provide assistance to counties in implementing their 
indigent care programs. As is the case in many Southern states, public 
health departments in each county in Florida have traditionally played a 
major role in providing services directly to low-income individuals and 
families. A significant portion of each county health department's 
service capacity is devoted to the delivery of prenatal care. However, 
prior to 1987, county health departments rarely billed Medicaid when 
serving Medicaid-eligible women and children. TACTs worked with county 
staff to increase the Medicaid revenues that the county health 
departments collected when serving Medicaid-eligible clients by helping 
them with procedures to improve eligibility determination and enrollment 
of clients and increase Medicaid billings. (More detail about the 
implementation of the Medicaid expansions and related reforms in Florida 
is contained in Appendix B) . 



DATA AND METHODS 

Data 

We studied all births in Florida occurring in the period July 1988 
through June 1989 and in calendar year 1991. This study period includes 
the twelve month period just prior to the expansion of eligibility to 
women with income between 100 percent and 150 percent of poverty and the 
second full calendar year after the expansion was implemented. We chose 
July 1988 through June 1989 as the "baseline" year so that women with 
income below poverty who delivered during the baseline period would have 
been eligible for Medicaid throughout their pregnancy under the October 
1987 expansion. We chose 1991 as the post-expansion period to allow 
time for the new eligibility policy to be implemented. The other 
strategies that the state adopted to complement the eligibility 
expansion were all in place during both of these periods. 

Data come from the Florida birth and death certificates, the 
hospital discharge abstracts, Medicaid eligibility files and claims 
files, individual encounter records for personal health services 
provided through each county health department in the state, the 
American Hospital Association (AHA) annual survey files for Florida 
hospitals, and the 1990 Census. 

The birth and fetal death records define our study universe and 
provide information about the mother's demographic characteristics, the 
amount and timing of prenatal care, and the birthweight of the newborn. 
The birth records matched to infant death certificates also indicate 
whether the newborn survived its first year. 

The hospital discharge data provide information to identify the 
primary payer for the delivery and to measure hospital charges. We 
selected discharge records for the study periods that had an ICD-9 
indicating a delivery or a hospitalization for prenatal care. A 
computer algorithm linked the vital statistics and hospital discharge 
data files using common variables including hospital, mother's date of 
birth, date of birth or death (vital statistics) and date of first 
procedure (hospital discharge file), and the mother's zipcode. We 
matched 93 percent of the birth records for which the reported delivery 
location was a hospital in the Florida hospital discharge data system 



and 87 percent of the hospital discharge records that we identified as 
deliveries using this algorithm (for more detail on the matching see 
Appendix C) . 

The Medicaid eligibility data allow us to distinguish reasons for 
entitlement and, in particular, to classify separately pregnant women 
covered by Medicaid because they are receiving AFDC cash assistance, 
those who qualify under the medically needy program, and those covered 
by the Medicaid income expansions. We linked the Medicaid eligibility 
data to the matched vital statistics and discharge file using social 
security number, which is also present in the vital statistics data. We 
successfully matched 80 percent of birth records in which the hospital 
discharge record indicated Medicaid as the payer to the eligibility file 
(see Appendix C for further information) . 

We constructed summary records for each episode of prenatal care 
provided through the county health departments over the period 1987 
through 1991 (we include care delivered prior to each study year in 
order to measure all of the prenatal care associated with the deliveries 
occurring in the study year) . These episodes were matched to our other 
three data sets using social security number; we were able to match 
about 75 percent of the episodes to the other three linked files. 

Finally, we used the AHA data to measure the type of hospital and 
added this information to our analytic file. Information from the 1990 
Census on the income and poverty status of residents in each Florida 
zipcode area was also added to the file in order to develop a control 
measure for income status as we discuss later. 

Methods 

Our evaluation of the effects of the Medicaid expansion consists of 
two parallel analyses. First, we investigate aggregate changes in the 
quantity, delivery provider, and sources of financing for maternal 
health care between the baseline period and 1991. Then we estimate 
differences in the amount and timing of prenatal care and in the birth 
outcomes for a woman covered by the Medicaid program and an uninsured 
woman or one covered by some other payer. We also contrast birth 
outcomes for Medicaid patients who use the county health departments for 
their prenatal care with those using the private delivery system. 



8 

Aggregate Analvsis- 

Overview. Our aggregate analysis examines the changes in the 
primary source of financing for deliveries in the two study periods; 
changes in the quantity of maternity related services, the type of 
provider delivering care, and the financing of the services; and changes 
in the flow of payments for maternal health care. We present a series 
of matrices that categorize deliveries, services, and payments according 
to the financing source--private insurance, Medicaid, and "other payer." 
This last category includes those whose care was paid for by some other 
third-party payer such as Medicare, CHAMPUS, or state and federal 
programs that make payments on behalf of a patient receiving care, and 
the uninsured. The hospital discharge data--our primary source for 
payer--does not allow us to further classify these other payers. We 
also are unable to separately identify a woman's source of insurance, if 
any, for prenatal care. 

The quantity of prenatal care and the number of prenatal and 
delivery admissions are categorized by both payer and site of service. 
For ambulatory care we distinguish between care provided in county 
health departments and care provided at other sites, including physician 
offices, hospital clinics, and hospital outpatient departments. 
Hospital admissions are categorized by the type of hospital--public, 
voluntary, or proprietary. Our measure of quantity and our measure of 
payment covers care received by women who delivered in the study period, 
irrespective of whether the care was provided in that period. 

Measuring deliveries . The vital statistics records for all births 
and fetal deaths registered to Florida residents measure the total 
number of deliveries in each year. We distributed these deliveries among 
the three payer categories based on the distribution of primary payer at 
delivery for deliveries included in the matched hospital discharge file 
and vital statistics file for each year. 

Measuring use of services. The linked file also provides us with 
an estimate of the average number of prenatal care visits received by 
women in different payer statuses. We multiply these estimates by the 
number of deliveries to measure aggregate prenatal care visits. The 



2 This section overviews the aggregate analysis methods. Detail is 
contained in Appendix D. 



encounter data from the county health department system yielded a count 
of the total number of prenatal care visits provided by county health 
departments. We distributed this total among the different payers based 
on the distribution of county health department visits that we were able 
to match to the vital statistics/hospital discharge file. 

The total number of hospitalizations for deliveries was counted 
from the vital statistics data on location of delivery. We allocated 
this total among the types of hospitals and payers based on the 
distribution observed in our linked analysis file. We estimated the 
number of prenatal admissions for women delivering in each study period 
from the number of admissions in the period with ICD-9 codes related to 
prenatal or maternity care that did not result in delivery. Because the 
hospital discharge data lack individual identifiers, we are not able to 
track the prenatal hospital admissions of women who gave birth in the 
study period. We therefore approximate these by looking at all prenatal 
admissions in a period, regardless of whether the woman actually gave 
birth in the period. Because the number of births changes little from 
year to year, this method provides a good estimate of the number of 
prenatal admissions for women delivering in the study period. 

Measuring payments . The third matrix we present shows the flow of 
payments for maternal care in the two periods. It measures the direct 
payments for care by patients and on account of patients by third-party 
payers. That is, it measures what was actually collected by the 
provider for the care of a particular patient. It does not include 
contributions that are not tied to particular patients, such as federal 
block grants to states for Title V programs and general contributions by 
local governments to public hospitals for charity care. 

To measure the payment flows, we started with an estimate of the 
total charges for inpatient hospital services and for physician and 
related services (such as laboratory tests and x-rays) categorized by 
the delivery payer. The total charge estimates for each payer are based 
on estimates of the average charge per quantity of service multiplied by 
our estimates of the units of service as described above. For hospital 
admissions, estimates of the average charge for women in different payer 
statuses and in different hospital types are from the hospital discharge 
data. For physician and other services, we use an estimate of charges 



10 



per prenatal visit from the Florida Medicaid claims file for 1991 and 
from the claims data for two large employers in Florida as the basis for 
assigning total charges per payer. 

In order to distinguish direct patient payments from third-party 
payments, we need to separate the charges for visits and admissions by 
the uninsured from those for persons with a third-party source of 
payment who are included in "other payer" . Because our primary data 
sources do not provide this information, we used information about the 
distribution of delivery payer for Florida sample persons in the 1988 
National Maternal and Infant Health Survey (NMIHS) to estimate the share 
of deliveries for uninsured women and the share of their visits that are 
included in the "other payer" category to allocate the charges. We 
allocated the charges for "other payers" in both of our study periods 
using the estimated 1988 ratios. Because the Medicaid expansions would 
be expected to decrease the share attributable to the uninsured, our 
procedure will somewhat understate the increase in payments over the 
period. More detail on the per case charges and on our procedures for 
estimating the aggregate matrices are in Appendix D. 

The resulting matrix of charges was converted to payments using 
estimates of the ratio of payments to charges for different payers. 
Payment to charge ratios for hospital care were provided by the Agency 
for Health Care Administration in Florida. A Medicaid payment to charge 
ratio for physician and related services was derived from the Florida 
Medicaid claims files for maternity care. The ratio for private 
insurance payers was based on the maternity care claims data from two 
large Florida employers. Absent other data sources to provide payment 
to charge ratios for physician services in Florida for the uninsured and 
those covered by third-party payers other than private insurance and 
Medicaid, we used the hospital ratios. Based on the similarity of the 
private insurance and Medicaid ratios for hospital and physician 
services, this seemed a reasonable assumption. Payments to county 
health departments for prenatal care were measured from state Health 
Office budget and revenue statistics for the county health department 
system. 






11 



Person Level Analysis of Outcomes 

Overview. Our objective is to measure whether expanding Medicaid 
coverage to a previously uninsured woman improves her access to prenatal 
care and reduces the occurrence of poor birth outcomes. The method is 
to compare outcomes for women in different insurance statuses, 
controlling for demographic and health factors that are known to affect 
service use and birth outcomes. We compare four groups of women: those 
enrolled in Medicaid under the eligibility expansions; those enrolled in 
Medicaid because of their participation in AFDC; women covered by "other 
payers" who reside in low-income areas; and women covered by private 
insurance who reside in low-income areas. We compare outcomes among 
these groups in each of the two study periods. 

Because many believe that birth outcomes for low-income women 
depend on the scope and content of care provided rather than the 
quantity of care, we also compare outcomes for Medicaid beneficiaries 
who use the county health departments for their care with those using 
other providers. Through a special grant program in Florida, the former 
emphasize comprehensive systems of prenatal care and provide support 
services such as health education, nutritional counseling, social work 
services, home visits, in addition to clinical prenatal services. 

Comparison Groups. Our data do not permit us to precisely identify 
uninsured women who would be eligible for the Medicaid expansions for 
two reasons. First, our insurance measure from the hospital discharge 
file does not distinguish among the uninsured and those who are covered 
by other non-private third party payers (except Medicaid) . Second, we 
do not have a measure of the woman's income. As a proxy for Medicaid 
income eligibility, we measure outcomes for women who live in areas in 
which over 30 percent of the population has a family income below 150 
percent of poverty (the threshold of the Medicaid expansion in 1988) . 
This definition encompassed the poorest quintile of neighborhoods; on 
average, over 40 percent of the population in these neighborhoods had 
income below 150 percent of poverty. The difference in outcomes between 
women whose deliveries were covered by Medicaid and women in low-income 
areas with "other payer" is our measure of the effect of providing 
Medicaid coverage to the uninsured. This measure may understate any 
positive effects of providing public coverage to uninsured women to the 



12 



extent that not all of those with "other payers" are uninsured women. 
This bias, however, should be small because the NMIHS of 1988 shows that 
about two-thirds of all women with "other payer" are uninsured, and this 
fraction would be expected to increase among low- income women. 

We also compare outcomes for those on Medicaid and the uninsured 
with those for women who are covered by private insurance. Again, we 
limit our comparison to women residing in low- income areas as a proxy 
measure to control for economic circumstances of the individual. Other 
research (Starfield et al., 1991; Rosezweig and Schultz, 1982) has shown 
that there are income effects related to seeking prenatal care and to 
birth outcomes . 

The difference in outcomes between Medicaid beneficiaries and low- 
income uninsured women who do not enroll in Medicaid may overstate the 
effect of providing Medicaid coverage if those who enroll in Medicaid to 
receive maternity care are healthier, or more likely to use prenatal 
care than those who do not enroll. To control for this selection, we 
distinguish between those who are enrolled in the expansions for 
pregnant women and women whose enrollment in Medicaid is unrelated to 
their pregnancy but stems from their participation in AFDC. Differences 
between the two Medicaid populations is a measure of selection. We 
interpret differences between the AFDC Medicaid population and the low- 
income uninsured as a measure of the insurance effect of Medicaid, 
controlled for any self -selection in the expansion population. 

For Medicaid beneficiaries, we look at differences in outcomes for 
patients using the county health departments for their prenatal care and 
those using other providers. In this analysis, we categorize a woman 
according to where she received the majority of her prenatal care 
visits. Users of the county health department system are therefore 
women who used the clinics for at least half of their prenatal visits. 
Our results were not sensitive to this definition. We obtained similar 
results if we included women who received any of their care at the 
county health department as using this system. We examine whether the 
effect of choice of delivery system on outcomes differs between Medicaid 
enrollees in the expansion program and the AFDC Medicaid beneficiaries. 

Outcome Measures. The outcomes that we investigate are measures of 
prenatal care use and birth outcomes. We examine whether any prenatal 



13 



care was obtained, the timeliness of initiating care among those who 
sought care, and the number of prenatal care visits for those receiving 
prenatal care. Timeliness is defined as seeking care prior to the third 
trimester. We also measure access using two indices of adequacy of 
care: the Kessner Index (1973) and Kotelchuck Index (1994) . Both 
indices are based on the timing of initiation and the number of visits, 
adjusted for gestational age. Neither index reflects the content of 
care, which many analysts cite as an important correlate of birth 
outcomes. However, we indirectly investigate the effect of the scope 
and content of care on birth outcomes by comparing Medicaid women who 
use the county health departments for their care and women using the 
private delivery system. 

We also investigate differences in the occurrence of adverse 
outcomes among women with different insurance status. The adverse 
outcomes we examine are low birthweight (less than 2500 grams) , very low 
birthweight (less than 1500 grams) , and infant death (death within the 
first year after birth) . Because we did not have death certificates for 
deaths occurring in 1992, we have missed some infant deaths for babies 
born late in 1991. This will cause us to understate the number of 
infant deaths in that year, but should not bias our comparison of 
different insurance groups. To correct for the underestimate, we 
multiplied our estimates of infant deaths in 1991 for all subgroups by a 
constant factor (1.20) that reflects the ratio of all infant deaths to 
infant deaths occurring in the calendar year of birth based on the 1988- 
1990 observations. 

Sample. Our person-level analysis includes women with a live birth 
for whom we could find a matching hospital discharge record. We exclude 
fetal deaths in this analysis because of missing data on important 
demographic characteristics that we wish to control for in our 
comparisons. Most notably, we do not have zip code to assign an income 
status. These fetal deaths, however, account for only about one-half of 
one percent of all deliveries in a year. We also exclude births of 
less than 500 grams (0.15 percent of records). 

Our analysis is restricted to women whose birth record includes 
information to calculate the key outcome measures and demographic 
characteristics. This restriction eliminated 5.4 percent of records in 






14 



our matched file in the baseline period and 5.2 percent of records for 
1991. Our final analysis sample included 156,453 women in the baseline 
period and 164,039 women in 1991. Excluding women with missing 
information about any outcome disproportionately excludes babies who die 
soon after birth because their birthweight is often not recorded. Thus, 
the infant death rate for our analysis sample is lower than the infant 
death rate for all births. However, our estimates of differences in the 
death rates among payer groups are not affected by this exclusion. We 
verified this by producing estimates (not reported) of infant death 
rates by payer for all births as well as the analysis sample estimates. 

To study differences in the outcomes among women treated in 
different delivery systems, we limit our contrast to women enrolled in 
Medicaid in 1991, either in the expansion program or because of their 
AFDC participation. Our sample for this analysis included 58,751 women. 

Analysis. We use regression analysis to control for the effects of 
differences between our contrast groups in demographic characteristics. 
Indicators for insurance status measure the effect of payer on the 
outcomes. The indicators in the model distinguish among women enrolled 
in Medicaid according to the reason for their entitlement, women with 
private insurance according to the income of the area in which they 
reside, and women without private insurance or Medicaid according to the 
income of the residence. 

The regression models fit to estimate differences in outcomes for 
women in different delivery systems use the Medicaid enrollees in 1991. 
The models include the indicator for the delivery system used, an 
indicator for whether an AFDC or expansion enrollee, and the interaction 
between these in order to investigate whether the effects of the choice 
of delivery system differ for those in the expansion program and other 
Medicaid patients. 

In addition to the insurance indicators, the explanatory variables 
in the model measure the mother's age, education, race, marital status, 
parity, and whether the birth was a singleton birth. For 1991, we also 
include measures of ethnicity and whether the mother had any medical 
risk factors. We fit ordinary least squares regression for the number 
of prenatal care visits. For the other outcome variables, which are 
dichotomous, we fit logistic regression. 



15 



We use the regression model to estimate the outcomes for our 
comparison groups standardized to a common set of demographic 
characteristics. The reference for our comparisons is a woman whose 
characteristics assume the average value of these characteristics for 
women in the Medicaid expansion population in 1991. 

To illustrate how we use the regressions to produce our results, 
let Y be the outcome of interest. We fit a regression model of the 
form: 

Y = p + PjfAFDC) + P 2 (Uninsured) + P 3 ( Privately Insured) + 
P,*x, 

where AFDC, Uninsured, and Privately Insured are indicators for the 
source of the financing of the delivery and X denotes the demographic 
characteristics of the women. In our tables of results, we present 
predicted estimates of the outcome Y for a woman with characteristics 
given by X e , which denotes the average value of the characteristics for 
women in the expansion population in 1991, while varying the insurance 
group. Table 1 summarizes the predicted values in terms of the 
regression coefficients. 

Table 1. Predicted Values for Comparing Insurance Groups 



Privately 
Expansion AFDC Uninsured Insured 

Outcome Y p 0+ p/X. P.+fc+P/X. P„+P,+P 4 *X. P„+P 3 +P 4 *X e 



The difference in the predicted value for any two groups, 
therefore, reflects the difference due only to insurance status because 
the effects of demographic characteristics are the same across groups. 
(See Appendix E for the definitions of our explanatory variables and the 
values for the reference population. See Appendix F for the regression 
parameter estimates.) 



16 



RESULTS 

Aggregate Analysis 

Chancres in Coverage 

The Medicaid expansions led to substantial shifts in the source of 
payment for deliveries in Florida between the baseline period and 1991. 
In just two and one-half years, the number of births covered annually by 
Medicaid rose from 47,000 to 70,000, a 47 percent increase (Table 2 and 
Figure 1) . Because there was only a 2 percent increase in total births 
per year over this period, nearly all of the Medicaid growth represented 
a shift among payment sources. The proportion paid for by Medicaid rose 
from 25 percent to 36 percent. In contrast, the proportion of births 
covered by private insurance remained essentially the same over the 
period. Therefore, the public expansions did not substitute for private 
insurance. Instead, they either covered the uninsured or replaced other 
sources of third party coverage (for example, Medicare, CHAMPUS, and 
other federal and state programs that pay for patients' care). Although 
our data do not permit us to distinguish between these two groups of 
"others," data from the NMIHS in Florida show that in the baseline 
period two-thirds of the group without Medicaid or private insurance 
(about 33,000 women) were uninsured. Thus it is likely that the 
expansion, which covered 23,000 additional deliveries per year, served 
largely to cover women who otherwise would have been uninsured. 

Table 2. Deliveries by Primary Delivery Payer 



Payer 



Number of Deliveries 



7/88-6/89 



1991 



Percent 
Change 



Private Insurance 
Medicaid 

a 

Other Payer 



91,948 (48.7%) 
47,413 (25.1) 
49,432 (26.2) 



89,108 (46.1%) -3.1? 
69,643 (36.0) 46.9 
34,541 (17.9) -30.1 



Total 



188,793 (100.0) 



193,292 (100.0) 



2.4 



Note: Column percent in parentheses. 
Includes other non-private third party payers (e.g., CHAMPUS, 
Medicare, other state and federal programs that make payments on behalf 
of patients) and the uninsured. 



17 





100% 




90% 




80% 


CO 


70% 


LU 




rr 




> 


60% 


_l 




LU 




Q 


50% 


LL 




o 




(- 


40% 


z 




LU 




() 




(T 


30% 


LU 




0. 






20% 




10% 




0% 



49% 







26% 



25°/ 




□ Private 
insurance 



□ Other payer 



I Medicaid 




Baseline (7/88-6/89) 



TIME PERIOD 



46% 



18% 




36% 



1991 



Figure l--Distribution of Deliveries by Primary Payer 



Changes in Ambulatory Prenatal Care Visits 

Total ambulatory prenatal visits by all women rose by 150,000, or 
about 7 percent between the baseline period and 1991 (Table 3). This 
was greater than the increase in total deliveries, and so there was 
about a 5 percent increase in prenatal visits per person, on average. 
The increase in prenatal visits per person occurred among all three 
coverage groups. However, the increase in prenatal care visits per 
person for those on Medicaid and others without private insurance (the 
group that previously included the newly entitled Medicaid 
beneficiaries) increased by about 7 percent over the period, whereas the 
increase for the privately insured was about 4 percent. So viewed in 
the aggregate, the Medicaid expansion appears to have led to a small 
increase in access for the non-privately insured relative to what we 



Table 3. Ambulatory Prenatal Visits by Primary Delivery Payer 



7/88 - 6/89 1991 

County Other County Other 
Health Delivery Health Delivery 
Total Dept . System Total Dept ■ System 

Number of Visits 



Private Insurance 1,133.9 13.0 1,120.9 1,141.8 1674 l, 125.4 

Medicaid 466.6 177.2 289.4 729.7 433.3 296.4 

Other Payer' 473.7 59.7 414.0 352.9 48.1 304.8 

Total 2,074.2 249.9 1,824.3 2,224.4 497.8 1,726.6 



Percent Distribution by Payer (row percent) 



Private Insurance 100.0 1.1 98.9 100.0 FTi 98TeT 

Medicaid 100.0 38.0 62.0 100.0 59.4 40.6 

Other Payer' 100.0 12.6 87.4 100.0 13.6 86.4 

Total 100.0 11.9 88.1 100.0 22.4 77.6 



Percent Distribution by Payer (column percent) 



Private Insurance 54.7 5.2 61.4 51.3 3 . 3 55 2 

Medicaid 22.5 70.9 15.9 32.8 87.0 17.2 

Other Payer' 22.8 23.9 22.7 15.9 9.7 17.6 

Total 100.0 100.0 100.0 100.0 100.0 100.0 



'Includes other non-private third party payers (e.g., CHAMPUS, Medicare, other state and federal 
programs that make payments on behalf of patients) and the uninsured. 



19 



expect based on the trend for the privately insured. But we return to 
the question of effects on access and outcomes later. 

Striking changes occurred in the quantity of prenatal care 
delivered by different parts of the delivery system. The total number 
of visits provided by county health departments rose by 250,000 (100 
percent) , a number greater than the total increase in visits at all 
sites combined. The proportion of visits provided by health departments 
rose from 12 percent to 22 percent. In contrast, total visits to all 
other ambulatory care sites fell somewhat. 

The Medicaid eligibility expansion was almost fully accommodated by 
this huge growth of care provided by county health departments. Of the 
263,000 additional prenatal visits by Medicaid women in 1991, 256,000 
took place there. As a result, a significant shift in where Medicaid 
women received their care accompanied the expansions (Figure 2) . By 











90% • 
















80% • 










46% 




UJ 

b 

</> 

>- 
m 

(0 


70%- 
60% • 


62% 


















D Other sites 




8 
> 
u. 
o 

i 

o 
2 

UJ 

K 


50%- 
40%- 














30% ■ 


^^^H 




I 59% 






20% ■ 


38% 1 


■ Health 
Dept. 


i^^H 






10% - 


i^H 




i^H 






0% - 


i ^ — ^ 1 

Baseline (7/88-6/89) 1991 








TIME PERIOD 



Figure 2--Distribution of Prenatal Care Visits Among Medicaid Women by 

Site of Care 






20 



1991, county health departments provided 59 percent of ambulatory- 
prenatal care for this coverage group, up from 38 percent only two and 
one-half years earlier. As a result, care delivered to Medicaid 
beneficiaries at other sites decreased. 

Another effect of increasing Medicaid coverage was to reduce the 
number of visits provided to uninsured patients or to those covered by 
other non-private third party payers by 121,000, or almost 2 6 percent. 
According to the 1988 NMIHS, about 63 percent of these visits were 
visits by uninsured patients, and so a large fraction of the decrease is 
visits previously provided as charity care by hospitals or physicians. 
Visits to county health departments fell by 12,000, or 10 percent of the 
total decrease. Most of the decrease was in visits to other sites which 
fell by 109,000 visits, or almost 90 percent of the total decrease. 

Changes in Hospital Admissions 

The Medicaid expansion had a much smaller effect on the types of 
hospitals women used, when compared to the substantial shifts in the 
sites of ambulatory care. For all payers combined, use of public 
hospitals declined about 3 percent, from 29 percent of admissions in the 
baseline period to 27 percent in 1991 (Table 4) . The use of voluntary 
hospitals declined by a similar percentage. In contrast, the increase 
in use came at proprietary hospitals, whose share of maternity care rose 
from 14 percent to 17 percent. However, most of the increase in the 
admissions to proprietary hospitals is a general trend for all payer 
groups and not a consequence of the expansions. 

Although there was little change in the number of admissions of 
pregnant women to public and voluntary hospitals, there was a sizable 
increase in the share of these admissions that are financed by Medicaid 
and a sizable decrease in the share that are self-pay or financed by 
some other government program (Figure 3). For public hospitals, the 
Medicaid share increased from 31 percent to 47 percent whereas for 
voluntary hospitals it increased from 25 percent to 36 percent. For 
public hospitals, the share attributable to other payers fell from 42 
percent to 28 percent, for voluntary hospitals the decrease was from 22 
percent to 16 percent. There was also an increase in the share of 
admissions to proprietary hospitals that was financed by Medicaid and a 



21 



100% 



80% .. 



50% -■ 






□ Other 




Voluntary, 

Baseline(7/88- 

6/89) 



TYPE OF HOSPITAL AND TIME PERIOD 





Voluntary, 
1991 



Figure 3--Distribution of Source of Financing by Type of Hospital and 

Time Period 



reduction in the share financed by other payers, but the magnitude of 
these changes was not large because the vast majority of admissions to 
proprietary hospitals are for the privately insured (70 percent in 
1991) . 

Medicaid eligibles use a very different mix of hospitals than the 
privately insured. For example, in 1991, public hospitals provided 36 
percent of maternity-related admissions for Medicaid women versus 15 
percent for the privately insured. In that same year, voluntary 
hospitals accounted for 56 percent of Medicaid admissions and 58 percent 
of privately insured admissions. Finally, proprietary hospitals only 
accounted for 9 percent of Medicaid admissions versus 27 percent for the 
privately insured. The pattern for the uninsured and those covered by 
other payers is similar to that of Medicaid, but with greater use of 



Table 4. Maternal Hospital Admissions by Primary Delivery Payer 



7/88 - 6/89 __ZZZ!Zm 1991 



Public Voluntary Proprietary Public Voluntary Proprietary 

J__J Hospital Hospital Hospital Total Hospital Hospital Hospital 



Number of Admissions 



Private Insurance 102.2 15.9 65.4 20.9 9777 TTTs 5679 2 6 

Medicaid 53.6 19.0 30.2 4.4 77.1 27.4 42.7 7 o 

Other Payer' 56.4 25.5 26.1 4.8 38.8 16.3 18.6 3.9 

Total 212.2 60.4 121.7 30.1 213.6 58.5 118.2 36.9 



Percent Distribution by Payer (row percent) 



Private Insurance 48.2 26.3 53.7 69.4 45 .7 25 3 48~ _ 2~ 



'Includes other non-private third party payers (e.g., CHAMPUS, Medicare, other state and federal 
programs that make payments on behalf of patients) and the uninsured. 



Private Insurance 100.0 15.5 64.0 20.5 100 . 157! 5871 26 6 

Medicaid 100.0 35.4 56.3 8.3 100.0 35.5 55.4 g.j 

Other Payer' 100.0 45.2 46.3 8.5 100.0 42.0 47.9 10. 1 

Total 100.0 28.5 57.3 14.2 100.0 27.4 55.3 17.3 



Percent Distribution by Payer (column percent) 

70.4 
Medicaid 25.2 31.5 24.8 14.6 36.1 46.8 36.1 19.0 



Other Payer' 26.6 42.2 21.5 16.0 18.2 27.9 15.7 10.6 

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 



K> 



23 



public hospitals (42 percent versus 3 6 percent) and lower use of 
voluntary hospitals (48 percent versus 55 percent) . 

Changes in Payments for Maternity Care 

Payments to providers for maternal care in 1991 totaled $928 
million dollars, up 3 percent from the baseline period total of $902 
million, expressed in constant 1991 dollars (see Table 5) . Medicaid 
payments, which are financed with about 55 percent federal funds and 45 
percent state funds in Florida, increased by about $52 million, or 38 
percent. Medicaid payments for persons in the expansion population 
increased by 140 percent; they totaled $105.7 million in 1991, up from 
$43.3 million in the baseline period. Medicaid payments for other 
beneficiaries declined by 11 percent or $10.3 million over this period, 
from $91.9 million in the baseline period to $81.6 million in 1991. In 
contrast, payments by other third parties and the uninsured fell by 
almost 30 percent. 

Hospitals benefited from the expansions. Their maternity-related 
revenues grew by 5 percent, whereas admissions of maternity patients 
remained fairly constant (Table 4) . This extra revenue largely results 
from Medicaid payments for admissions that were previously provided as 
bad debts or charity care. 

In contrast, payments for physician care and related services rose 
by only 0.4 percent in constant 1991 dollars, whereas ambulatory care 
prenatal visits increased by 7 percent. Two main reasons account for 
this difference. First, total physician payments are a combination of 
payments for ambulatory prenatal care and inpatient care, mostly for 
deliveries. Deliveries and total physician payments remained relatively 
constant. Second, the increase in ambulatory prenatal care was 
accommodated almost entirely by county health departments. 

Medicaid accounted for 20 percent of total payments for maternity- 
related care in 1991, although 36 percent of deliveries in that year 
were to women with Medicaid coverage. This difference arises because 
Medicaid pays a smaller proportion of what it is charged for maternal 
health services than private insurers. Private insurers accounted for 
63 percent of payments in 1991, although only 46 percent of deliveries 



24 



Table 5. Flow of Payments for Maternity Care 
(Millions of 1991 dollars) 



Paver 



Physician 
Services 



Hospital 

Services 



7/88 - 6/89 



Private Insurance 

Medicaid 

Other Third Party Payer 

Self Pay 

Cost Sharing 

Uninsured 
Total 



298.3 i 67.0%) 280.1 ( 61.3%) 
51.4 ( 11.5) 83.8 ( 18.3) 
35.0 ( 7.9) 56.5 ( 12.4) 



44.5 ( 10.0) 

15.9 ( 3.6) 

445.1 (100.0) 



14.7 ( 3.2) 

22.0 ( 4.8) 

457.1 (100.0) 



1991 



Private Insurance 

Medicaid 

Other Third Party Payer 

Self Pay 

Cost Sharing 

Uninsured 
Total 



299.5 ( 67.0) 

65.1 ( 14.6) 

25.9 ( 5.8) 

44.6 ( 10.0) 

11.6 ( 2.6) 

446.7 (100.0) 



287.5 ( 59.7) 

122.2 ( 25.5) 

41.0 ( 8.5) 

15.1 ( 3.1) 
15.5 ( 3.2) 

481.3 (100.0) 



Percent Change 



private Insurance 





. 4 


Medicaid 


26 


.7 


Other Third Party Payer 


-26 


.0 


Self Pay 






Cost Sharing 





.2 


Uninsured 


-27. 





Total 


0. 


,4 



2.6 

45.8 

-27.4 

2.7 

-29.5 

5.3 



Total 



578.4 ( 64.1%) 

135.2 ( 15.0) 

91.5 ( 10.1) 

59.2 ( 6.6) 

37.9 ( 4.2) 

902.2 (100.0) 



587.0 ( 63.3) 

187.3 ( 20.2) 

66.9 ( 7.2) 

59.7 ( 6.4) 

27.1 ( 2.9) 

928.0 (100.0) 



1 . 5 

38.5 
-26.9 

0.8 

-28.5 

2.9 



Note: Column percents in parentheses. 



25 



were to women with private insurance coverage. Direct patient payments- 
-including cost sharing by insured patients and payments made by 
uninsured patients--accounted for 9 percent of funds. This distribution 
of payments by source in Florida is similar to national patterns (Long, 
Marquis, and Harrison, 1994) . 

Person Level Analysis of Outcomes 

Our analyses of the individual effects of the Medicaid eligibility 
expansions are based on the following causal model. For the expansions 
to improve birth outcomes for those who enroll rather than remain 
uninsured, several conditions must be met. First, women must enroll for 
Medicaid-paid services early in their pregnancies. Then, they must 
initiate prenatal care earlier and receive more care than they would if 
uninsured. Third, the content of the expanded care must be associated 
with an increased likelihood of good birth outcomes. We examine each 
stage in this process. Although a finding of better overall birth 
outcomes for the expansion population would be suggestive of an effect, 
findings that establish all of the steps in this causal chain serve to 
increase our confidence that effects we observe can be attributed to the 
Medicaid eligibility expansion and other Medicaid program changes that 
were introduced along with the eligibility changes. 

Timing of Medicaid Eligibility 

An increasing proportion of the Medicaid expansion population 
enrolled early in their pregnancies over the study period (Figure 4) . 
Although only 27 percent of women in the expansion population who 
delivered between July 1988 and June 1989 enrolled in the first 
trimester, by 1991 the rate increased to 46 percent. Most of the 
increase occurred early in our study period; in the first 12 months 
following the increase in the income threshold to 150 percent of 
poverty, 40 percent of the expansion population enrolled in the first 
trimester. This improvement is not explained by earlier enrollment 
among the higher income women newly eligible as a result of the increase 
in the income threshold. We tested for this possibility by examining 
the early enrollment rates over time for the subset of the expansion 
population having income below 100 percent of poverty. The change in 






26 



timing of their enrollment was similar to that for the entire expansion 
population. This suggests that the procedures Florida adopted in 1987 
to simplify eligibility and enroll women earlier in their pregnancy were 
successfully implemented by the end of 1988. 





















46 






45- 




40 










40- 
















IT 
Ul 

1- 
Cfl 
Ul 

s 
E 

i- 
i- 

N 


35- 
30- 


27 














z 

a 

z 
-i 
_i 
o 

IT 
Z 
111 


25- 
20- 


■ 














z 

Ul 

o 

i 

E 


15- 
10 
5- 


| 


















Baseline period 


12 months after expansion 


Calendar 






(7/88-6/89) 


(7/89-6/90) 
TIME PERIOD 


1991 



Figure 4--Percent of Medicaid Expansion Population Enrolling in First 

Trimester, by Time Period 

The share of the expansion population enrolled early in their 
pregnancy in 1991 compares favorably with rates in other states (cited 
earlier) that have implemented a range of strategies to simplify the 
eligibility determination process. Nonetheless, half of women in 
Florida who ultimately enroll under the expansion rules did not do so 
during the first trimester. 



Prenatal Care Use 

Women enrolled in the Medicaid expansion program use more prenatal 
care than women living in low-income areas who are without Medicaid or 
private health insurance- -hereafter termed "uninsured" women. In both 
study periods, the Medicaid beneficiaries were less likely to forego 



27 



prenatal care (Table 6) . The proportion not receiving prenatal care 
ranged from 1.3 percent to 1.4 percent for the Medicaid expansion group, 
significantly less than the rate of 3.4 percent to 3.7 percent for 
uninsured women. Among those seeking care in 1991, the percent of 
Medicaid beneficiaries initiating care late in the pregnancy (4.7 
percent) was below the rate for uninsured women (5.4 percent); however, 
there was not a significant difference in timeliness in the baseline 
period. Medicaid expansion women obtaining prenatal care had more 
visits than the uninsured in each period. Overall, the Medicaid 
beneficiaries were less likely to receive inadequate care than the low- 
income uninsured women. 

This result does not appear to be due to the selection of healthier 
women or those who are more disposed to seek prenatal care into the 
Medicaid expansion population. We found similar differences between 
women who are enrolled in Medicaid because they receive AFDC cash 
assistance and uninsured women. Medicaid eligibility for this group is 
based only on having low-income and assets, and not on being pregnant. 
However, some women applying for Medicaid pregnancy benefits may have 
found they were also eligible for AFDC cash assistance, signed up for 
the cash benefits, and been designated as an AFDC recipient by Medicaid. 
Their participation in Medicaid is related to being pregnant. Including 
these women in our "selection control" group would bias the comparison. 
To test for this, we also contrasted the expansion population with AFDC 
recipients who were enrolled in the program for most of their pregnancy 
(enrolled prior to the pregnancy or during the first trimester) and 
found similar results. Moreover, our estimates indicate that the number 
of pregnant women in eligibility groups other than the expansion group 
did not increase over time, and in fact, decreased slightly. 

Although providing Medicaid benefits to low-income women appears to 
increase their use of prenatal services relative to what they would be 
expected to use if uninsured, still the Medicaid women do not receive 
the level of prenatal care obtained by privately insured women. On all 
of our measures in both periods, Medicaid women have significantly 



Table 6. Prenatal Care and Birth Outcomes for Low- Income Women by Insurance Status 



Measure 



July 8 8 - June 89 



1991 



Medicai d 
Expans ion 



Medica id 

AFDC 



Oilier Low- 
Income* 3 



Private 

Low- 
Income" 



Medicaid 
Expansion 



Medicaid 
AFDC 



Other Low- 
Income 3 



Pi l vat e 

Low- 
Income" 



Prenatal Care 



No prenatal (%) 

User initiates third 

trimester (%) 
Visits/user 

Inadequate care (%) 

Kessner 

Kotel chuck 



1 .4 + 


1.9 


7.3. 


6.4 


11.0 


10.9 



8.9 + 
3 5.2* 



8.3* 
33.9* 



3.7*i 


0.8** 


1.3 + 


1 .6 


7.0. 


2.6*. 


4.7 


4.6 


9.8*. 


11.7*+ 


11.2 


11.2 



11.2' 



4 1 



3.4* + 

5.4* + 

10.6*+ 



0.7' 

1.5' 
12.2' 



3.5* + 


6.4 


6.5 


9.4* + 


2.5 


20.8*+ 


22.5 


22.1 


24.7*4 


H.H 



Birth Outcomes 



Low birthweight/1000 
Very low birthweight/1000 

Infant death/100Q C 



67.2 


65.1 


72. 1 + 


55.4*+ 


60.6 


61.3 


68.2 


8.9 


7.8 


9.9 + 


9.0 


9.2 


8.1 


9. 1 


6.9 


6.6 


8.5. 


8.6 


6.5 + 


5.0* 


6.7 



i 4 . 8 ' 

8.7 
7.2 



Pregnant women with "other" payer living in areas with more than 30 percent oE population with ncome below 150 percent poverty 
b 
Pregnant women with private insurance living in areas with more than 30 percent of population with income below 150 percent 

poverty, 
c 
Analysis sample estimate underestimates population rate; 1991 rate adjusted to include deaths occurring in 1992. See l^xt for 

detai Is . 

•Significantly different from Medicaid Expansion population, p =.05. 
.Significantly different from Medicaid AFDC population, p =.05. 



29 



poorer access to care than the privately insured. While there is 
improvement over time in access for the Medicaid women, similar 
improvements are also seen for the privately insured and the uninsured. 
The changes in access over time thus seem to be the result of an overall 
trend in the state, rather than the effect of the Medicaid program 
changes. The expansion, however, improved access for low-income women 
because it provided coverage to many previously uninsured women--who 
have poorer access than those enrolled in Medicaid. 

Birth Outcomes 

The rate of low and very low birthweight infants and the rate of 
infant death is generally lower among women enrolled in the Medicaid 
expansion program than it is for the uninsured (Table 6) . However, only 
the difference in the incidence of low birthweight infants in 1991 is 
statistically significant; in that year, the rate of low birthweight 
infants per 1000 was 60.6 for the expansion population versus 68.2 for 
the uninsured. Women enrolled in AFDC also have better birth outcomes 
than the uninsured; we find statistically better outcomes on all three 
measures in the baseline period and on the low birthweight measure in 
1991. 

Consistent with the utilization findings, women covered by Medicaid 
remain significantly more likely to give birth to a low birthweight 
infant than women with private insurance. 

Role of Different Delivery Systems 

The additional prenatal care financed by Medicaid that resulted 
from the expansion of eligibility to more low-income women was provided 
largely by county health departments. As shown in Table 7, this may 
have been an important factor in the better outcomes for the expansion 
population compared to those for the uninsured. The rate of low 
birthweight infants per 1000 among the Medicaid expansion mothers using 
the county health departments was 49.9, versus 70.4 for the other 
expansion mothers. The incidence of very low birthweight infants and 
infant deaths was also significantly lower among women enrolled in the 
Medicaid expansion who used the county heath department for their 
prenatal care than among similar women who obtained their care in 



Table 7. Prenatal Care and Birth Outcomes for Medicaid Women Using Different Delivery Systems, J 991 



Medicaid Expansion Population Medicaid AFDC Populatioi 



County Health Other Delivery County Health Other Delivery 
Measure Department System Department System 

Prenatal Care 



User initiates third trimester (%) 6.2 3.7* 6 \ g 

Visits/user 10.7 11.8* 10.5 
Inadequate care (%) 

Ressner 6.7 4.1 7.2 

Kotelchuck 25.5 18.8* 27.3 



Birth Outcome 



a 



Infant death/1000 4.3 6.0* 3. 



4.2* 

11.7* 

4.6* 
21.3* 



Low birthweight/1000 49.9 70.4* 5476 ' 599* 

Very low birthweight/1000 6.9 10.9* 6.4 9 5* ej 



4.2 



Analysis sample estimate underestimates population rate; 1991 rate adjusted to include deaths occurring 
in 1992. See text for details. 
♦Significantly different from county health department, p=.05. 






31 



another delivery system. We find better outcomes for women using the 
county health department even though they initiated care later and had 
fewer visits than women using another delivery system. 

Because the county health departments made special efforts to 
enroll low-income pregnant women in the Medicaid expansion program, 
there may be differences between the expansion population in the two 
delivery systems not accounted for by our control variables that might 
explain this result. However, women using the county health department 
who are enrolled in Medicaid because of their AFDC eligibility also have 
better birth outcomes than similar women using another delivery system. 

The finding is also not a result of referrals to another delivery 
system for women at risk of poor birth outcomes. Our estimates are 
adjusted for a measure of medical risk factors. In addition, we obtain 
similar results (not shown) when we compare outcomes for women who 
received any of their prenatal care in the county health department with 
all other Medicaid women. 

DISCUSSION 

Findings From the Florida Expansion Compared to Other Studies 

The Florida Medicaid eligibility expansion from 100 percent of 
poverty to 150 percent of poverty led to a large increase in Medicaid 
enrollment by pregnant women who would otherwise have lacked insurance 
coverage to pay for their prenatal care and delivery. We found strong 
evidence that women in the expansion population had better access to 
prenatal care than they would have had if they remained uninsured. Our 
results also consistently point to improved birth outcomes for the 
expansion enrollees. 

We come to stronger conclusions about the benefits of the expansion 
than most of the earlier literature. Is this because our methods are 
more precise, because Florida differs from other states, or both? We 
believe the answer is both. 

Large sample sizes are needed to precisely measure the birth 
outcomes we are trying to study, because they are very rare events. 
This suggests that research needs to focus on either the most populous 
states or places where policy held constant long enough to permit 






32 



pooling several years of data. Hence, Florida represented an 
opportunity to have large enough samples to find effects if they were 
present, and to stratify to more homogeneous subgroups to refine the 
comparisons. Moreover, our use of area income to identify the subset 
of women who are most likely to be uninsured and eligible under the 
expansion is a methodological improvement over other studies. Finally, 
earlier cross-section comparisons have been cautious in attributing 
differences between the expansion population and uninsured women to 
effects of the Medicaid program because of possible selection bias. We 
rule out selection as an explanation by finding similar results for 
Medicaid beneficiaries who are not enrolled in the program as a result 
of their pregnancy. 

The Florida experience, however, may differ from other states. 
Most of the additional prenatal care financed by Medicaid was 
accommodated in the county health departments, and this resulted in a 
substantial increase in the quantity of prenatal care provided by public 
clinics. This may not have happened in other states that have been 
studied. From our finding of better birth outcomes among Medicaid 
enrollees using the county health department compared to those using 
another delivery system, it appears that the county health department 
expansion was an important feature of the Florida intervention. Without 
it, the improvements probably would have been more modest. Some 
observers of the expansions have pointed to the importance of expanded 
services for low-income women. In Florida, Medicaid did not pay for 
these services, but the effect of offering Medicaid revenues to the 
county health departments was to provide revenue to cover basic medical 
services so that non-Medicaid funds could be used to support those 
additional services. 

Policy Implications 

The Congress is currently considering major changes in federal 
funding for Medicaid and public health, most of which would control the 
growth of federal spending and provide the states with greater 
flexibility to use federal funds as they see fit. In this context our 
study findings are important. First, they suggest that the expansions 
may indeed have had an impact, so as policymakers consider spending 



33 



reductions, they should be cautious about cutting back on eligibility 
for the expansion population. 

Second, the results emphasize the inter-relationship of expanding 
insurance coverage and providing for a delivery system to accommodate 
peoples' needs. Specifically, our findings suggest that of the low- 
income women benefiting from the expansion in insurance for their 
pregnancies, those who used the county health departments for prenatal 
care had the better outcomes. On the other hand, some states have 
financed their Medicaid expansions, in part, by a contraction of their 
public health systems, assuming that the increased financial access 
provided by Medicaid would lead more low-income women to use the private 
delivery system (Alpha Center, 1995) . Our findings indicate the 
possibility that this could have unintended unfavorable effects on birth 
outcomes . 

Some states have accompanied eligibility expansions with fee 
increases to try to remove barriers to office-based care. Some are 
emphasizing enrollment in managed care. Although increasing financial 
access would be expected to have beneficial effects, our results suggest 
that it is not clear what the ultimate outcome of these trends will be, 
especially in states with a strong tradition of direct delivery through 
the public health system. Birth outcomes might deteriorate if these 
efforts to shift care to the private sector are not complemented by 
programs to provide the non-clinical support services to pregnant women 
that the public health system now provides. 

Several of our findings suggest that despite its contributions, the 
Florida intervention may not have achieved the full potential of such 
efforts. First, although the improvements in public awareness of the 
expanded eligibility limits and in eligibility processing appear to have 
had an impact on the percent of women becoming eligible early in their 
pregnancies, by 1991 it was still the case that about half of women who 
became eligible for Medicaid-paid deliveries did not become eligible 
during their first trimester. This suggests room for further 
improvement. Second, there remains a significant gap between Medicaid 
eligible women and low- income, privately insured women in use of 
prenatal care and in birth outcomes. 



34 



Our study provides new information about the Medicaid expansions in 
one state. However, national policy can not be based on one case study 
alone. Therefore, it will take study of more states with varied 
circumstances to fully evaluate the effects of this major initiative in 
Medicaid from the last decade that is still playing out over this one. 

Directions for Further Research 

The Medicaid expansions were the major policy change in the program 
in the 1980s. The program is now undergoing many other new changes and 
facing new challenges--including continued income expansions, raising 
physician fees to encourage use of office-based care, enrolling Medicaid 
patients in managed care, and Congressional consideration of options to 
control federal costs. While these changes do not all focus specifically 
on pregnant women, they may alter the availability of public programs to 
finance care for low- income pregnant women, the amount and kind of 
prenatal care that low- income women receive, and birth outcomes. 

The findings from our study of the 1989 Florida eligibility 
expansion raise a number of important questions about the effect that 
the new directions in Medicaid will have on access to care for low- 
income pregnant women and on their birth outcomes . 

• Will eliminating financial barriers have the same effect on 
access to care and outcomes for the near poor--who are the 
subject of the more recent expansions in Florida and other 
states? 

• Does Medicaid eligibility improve access and outcomes for 
important subgroups of pregnant women--especially teenagers 
and women at high risk for poor birth outcomes? 

• What are the likely effects on birth outcomes if increasing 
physician fees leads to a shift to more prenatal care 
delivered by office-based physicians? What are the likely 
effects on birth outcomes for Medicaid beneficiaries of the 
new emphasis on managed care? 



• 



• 



Will the effects of the expansions change when the public 
health system can not expand further to meet the increased 
demand? 

Does providing care directly to uninsured women through the 
public health system have the same effect on prenatal care use 
and birth outcomes as providing public insurance to pay for 
care received in the private sector? 



35 



Answers to these questions are critical to understanding the 
effects the recent policy changes in Medicaid will have on maternal 
health care and infant health, and therefore to evaluating some of the 
costs and benefits of these policy changes. This kind of information 
will be of paramount importance to state policymakers if federal 
proposals to restructure the Medicaid program and limit the growth in 
federal contributions are implemented. Some of these proposals would 
provide block grants to states, providing states with new flexibility in 
how they structure programs to provide health care services to their 
low-income population. If this occurs, state policymakers will need to 
make tradeoffs between expenditures on public insurance programs and 
direct delivery of services to the low-income population; they will need 
to evaluate the costs and benefits of care delivered in different 
settings; and they will need information about how different programs 
benefit especially vulnerable populations. 

Florida remains a good candidate state to study to answer these 
questions. A number of these questions can be answered with further 
analyses of the database that we constructed for the years 1988-1991. 
In addition, we have developed a technology for linking data collected 
in the state of Florida that could readily be applied to extend our 
database to cover additional years. 

Florida has experienced a number of additional changes in Medicaid 
eligibility and in delivery systems since the end of our 1991 study 
period. The income eligibility limit for pregnant women was increased 
from 150 percent of poverty to 185 percent in 1992, allowing one to 
observe the effects of expansions over a broader range of the near poor 
income distribution. 

The state has also seen substantial shifts in the mix of sites at 
which prenatal care for low-income women is provided since 1991. Over 
the initial years of our proposed study period, most of the prenatal 
care services newly financed by Medicaid were accommodated by expansions 
in the county health departments. Following the increase in obstetrical 
fees in 1991, however, there was a shift in the prenatal services for 
Medicaid patients from the county health departments to the private 
sector. For example, the number of pregnant Medicaid beneficiaries seen 
in county health departments fell from 66,000 to 47,000 between 1991 and 



36 



1994, despite growth in the number of Medicaid pregnant women over this 
time. Within the private sector, the period 1991 through 1994 resulted 
in a sizable increase in the number of Medicaid patients enrolled in 
managed care plans--from 125,000 to about 600,000. Thus, this period 
would provide additional information about the effect of changing sites 
of care on birth outcomes. 

Expanding our database to cover the 1992-1994 period would provide 
an invaluable source for answering the critical questions facing 
policymakers as they reform health care policy for low-income women. 



37 



REFERENCES 



Alpha Center, The Medicaid Expansions For Pregnant Women and Children. 
Washington, D.C. : Alpha Center; 1995. 

Braveman, Paula, Trude Bennett, Charlotte Lewis, Susan Egerter, and 
Jonathan Showstack, "Access to Prenatal Care Following Major Medicaid 
Eligibility Expansions", JAMA. 1993; 269: 1285-1289. 

Buescher, Paul A. and Nancy I Ward, "A Comparison of Low Birth Weight 
Among Medicaid Patients of Public Health Departments and Other 
Providers of Prenatal Care in North Carolina and Kentucky". Public 
Health Reports. 1992; 107: 54-59 

Buescher, Paul A., Clinton Smith, Joseph L. Holliday, and Ronald H. 
Levine, "Source of Prenatal Care and Infant Birth Weight: The Case 
of a North Carolina County". Am J Obstet Gynecol. 1987; 156: 204-210 

Buescher, Paul A., Marcia S. Roth, Dennis Williams, and Carolyn M. 
Goforth, "An Evaluation of the Impact of Maternity Care Coordination 
on Medicaid Birth Outcomes in N. Carolina. AJPH. 1991; 81; 1625-1629. 

Clarke Leslie L., Michael K. Miller, W. Bruce Vogel, Karen E. Davis, 
Charles S. Mahan, "The Effectiveness of Florida's 'Improved Pregnancy 
Outcome' Program". Journal of Health Care for the Poor and 
Underserved. 1991; 4, 117-132. 

Haas, Jennifer S., Steven Udvarhelyi, Carl N. Morris, and Arnold M. 
Epstein, "The Effect of Providing Health Coverage to Poor Uninsured 
Pregnant Women in Massachusetts". JAMA. 1993; 269: 87-91. 

Kessner D. M. , J. Singer, C.E. Kalk, and E.R. Schlessinger, Infant 

Death: An Analysis by Maternal Risk and Health Care. Washington D.C: 
Insitutie of Medicine and National Academy of Sciences; 1973. 

Kotelchuck, Milton, "An Evaluation of the Kessner Adequacy of Prenatal 
Care Index and a Proposed Adequancy of Prenatal Care Utilization 
Index". AJPH. 1994; 84: 1414-1420. 

Long, Stephen H. , M. Susan Marquis, and Ellen R. Harrison, "The Costs 
and Financing of Perinatal Care in the United States". AJPH. 1994; 
84: 1473-1478. 

Piper, Joyce M. , Edward F. Mitchell, and Wayne A Ray, "Presumptive 
Eligibility for Prenant Medicaid Enrollees: Its Effects on Prenatal 
Care and Perinatal Outcome". AJPH. 1994; 84: 1626-1630. 

Piper, Joyce M. , Wayne A. Ray, and Marie R. Griffin, "Effects of 

Medicaid Eligibility Expansion on Prenatal Care and Pregnancy Outcome 
in Tennessee". JAMA. 1990; 264: 2219-2223. 



38 

Rosenzweig, Mark R. and T. Paul Schultz, "The Behavior of Mothers as 
Inputs to Child Health: The Determinants of Birth Weight, Gestation, 
and Rate of Fetal Growth", In The Economic Aspects of Health, Victor 
R. Fuchs (Ed.). Chicago: University of Chicago Press, 1982. 

Starfield, Barbara et al . , "Race, Family Income, and Low Birth Weight". 
A J Epidemilogy. 1991: 134, 1167-1174. 

Starfield, Barbara, "Low Birthweight" . In The Effectiveness of Medical 
Care: Validating Clinical Wisdom. Baltimore: Johns Hopkins University 
Press, 1985. 

Thompson, Daniel, Diane Dimperio, Ronald G. Humphries, C. Meade Girgg, 
and Charles S. Mahan, "Low Birth Weight Rates For Florida Medicaid 
Recipients Receiving Prenatal Care in Public Health Units Compared to 
Those Receiving Care Elsewhere", Talahassee: Florida Department of 
Health and Rehabiitative Services; 1993. 



A-l 



APPENDIX A. SELECTION OF THE STUDY STATE 
Ian T. Hill, Stephen H. Long, and M. Susan Marquis 



This appendix details the criteria we established to guide our 
selection of the study state, describes states along the selection 
dimensions, and presents the reasons for selecting Florida as the study 
state. 



CRITERIA FOR SELECTION 

We established the following criteria for selecting candidates for 
the study state: 



A significant Medicaid eligibility expansion. The state must 
have increased Medicaid eligibility thresholds for pregnant 
women by a substantial amount, and the increase must be 
surrounded by lengthy periods of stable eligibility rules. To 
observe the effects of an eligibility change, it made sense to 
look in places where the policy change was "substantial" and 
where we can take accurate measures of "before" and "after" 
conditions. We also preferred a state that simultaneously 
adopted policies to encourage program participation—including 
information outreach campaigns, expanded services, and 
eligibility streamlining--because the effectiveness of the 
Medicaid eligibility expansion will depend on these policies as 
well as the change in the threshold. 

Strong Title V and other direct delivery programs, with a 
reputation for good data. To observe the effect of the 
Medicaid eligibility expansions on the direct delivery system, 
we looked for a state with a strong tradition of direct 
delivery through Title V programs and other systems, including 
community and migrant health centers. 

Availability of Medicaid eligibility and claims, vital 
statistics, and uniform hospital discharge abstract data. Our 

analysis plan required that we obtain and merge data from 
Medicaid, vital records, and hospital discharges at the person 
level. The eligibility files also needed to distinguish in the 
"post" period those who would have been eligible under the 
pervious rules from those eligible under the new rules. 
Uniform discharge data were required to identify the insurance 
status of women who were not covered by Medicaid. 

Favorable prospects for complete cooperation by state and local 
officials. We preferred to work in a state where we know 
people and expect full cooperation, because without it we would 
not be able to gain access to the necessary data. 

Minimize overlap with other studies. Other things equal, it 
was desirable to work in a state that remained unburdened by 
other studies, especially studies of financing issues. 



A-2 



CHARACTERISTICS OF THE STATES 



A descriptive typology of the fifty states and the District of 
Columbia along many of our criteria is provided in Tables A.l through 
A. 4, which appear at the end of this Appendix. 

Tables A.1-A.3 present characteristics of state Medicaid programs 
for pregnant women, infants, and children. Specifically, these tables 
show Medicaid eligibility thresholds and effective dates for expansions 
of coverage, the presence of statewide prenatal care outreach/public 
information campaigns, the presence of enhanced prenatal care benefit 
programs, and the effective dates of efforts to streamline Medicaid 
eligibility processes. These data provide measures for our first 
criterion for selecting a study state--the level of increase in Medicaid 
eligibility and the degree to which each state engaged in other efforts 
to improve access to and the quality of Medicaid-f inanced prenatal care. 

Table A. 4 presents characteristics of state and local health care 
delivery systems--specif ically , total maternal and child health 
spending, and the number and proportion of women served by both local 
health departments and community and migrant health centers (C/MHCs). 
These data provide information regarding the role of the direct delivery 
system in providing prenatal care (selection criterion 2). 



STATE SELECTION 

We concluded that Florida was the preferred state for our study. 
Florida was quick to respond to the new eligibility opportunities. The 
eligibility threshold for pregnant women was increased from 47 percent 
of poverty to 100 percent in October 1987, then to 150 percent in July 
1989 (Table A.l). Florida adopted all six of the eligibility 
streamlining methods shown in Table A. 3 before the end of 1987, well in 
advance of most states. 

The state also has a well established direct delivery system. 
Florida ranks third in the nation in total public spending on maternal 
and child health (MCH) , third in number of women served by MCH clinics, 
and third in number of women served by community and migrant health 
centers (Table A. 4) . This large absolute size of the direct delivery 
effort is important to our ability to detect changes. 

Florida has Medicaid data that distinguish enrollees by their 
basis of eligibility (income at or below AFDC threshold, above AFDC but 
at or below 100 percent of poverty, and over 100 percent of poverty but 
at or below 150 percent) . Florida has a uniform hospital discharge 
abstract data system. In addition, the state of Florida maintains a 
database of individual encounter records for all personal health 
services provided through each county health department. This unique 
database greater facilitates our analysis of the substitutions between 
programs following the Medicaid expansions. Importantly, the Medicaid 
Director and the state Health Department Director offered to cooperate 
with us in the study. Finally, there were no other major studies of the 
Medicaid eligibility expansions being conducted in Florida at the time 
we selected it. 



A-3 



REFERENCES 



Association of Maternal and Child Health Programs, Caring for Mothers 
and Children: A Report of a Survey of FY 1987 State MCH Program 
Activities, Washington, D.C., March 1989. 

Health Resources and Services Administration, U.S. Department of Health 
and Human Services, 1990-1991 Grant Applications, Rockville, MD: 
Division of Primary Care Services, Bureau of Primary Health Care 
1992. 

Hill, Ian T., The Medicaid Expansions for Pregnant Women and Children: 
A State Program Characteristics Information Base, Washington, D.C.: 
Health Systems Research, Inc. for the Health Care Financing 
Administration, February 10, 1992. 

Hill, I.T., Reaching Women Who Need Prenatal Care: Strategies for 
Improving State Perinatal Programs, Washington, D.C. : National 
Governors' Association, 1988. 

National Association of Community and Migrant Health Centers, Directory 
of Community and Migrant Health Centers, Washington, D.C, 1990. 

The Public Health Foundation, Public Health Agencies 1991: An Inventory 
of Programs and Expenditures, Washington, D.C, 1991. 

U.S. General Accounting Office, Prenatal Care: Early Success in 
Enrolling Women Made Eligible by Medicaid Expansions, Pub. No. 
GAO/PEMD-91-10, Washington, D.C, February 1991. 



Table A.l 

Medicaid Eligibility Thresholds and Effective Dates for 

Expansions of Coverage for Pregnant Women and Infants 

January 1987 - December 1991 



STATES 



Apr 



Jul 



Jan Apr 



1989 



Jan Apr 



Jul 



1990 



Apr 



1991 



Apr 



Jul Oct 



Alabama 
Alaska 
Ar i zona 

Arkansas 
Ca lif ornia 

Colorado 
Connect icut 
Delaware 
D.C. 
Florida 

Georgia 



16% 



1 1 1 inois 



« 



64% 



45% 



i .1 1 
67% 
61% 



75% 
4/87 



100% 
4/87 



100% 
10/87 



100% 
1/88 

100% 
2/88 



100% 
4/88 



100% 
1/88 



100% 
7/88 



100% 
7/88 

50% 
7/88 



100% 
7/88 



100% 
1/89 



185% 
1/89 



150% 
1/89 



185% 

7/89 

b 
75% 

7/89 





150% 




7/89 


100% 




1/89 




100% 


185% 


1/89 


1/90 


67% 


b 
75% 


1/89 


7/89 



100% 
7/89 
185% 
7/89 
150% 
7/89 



133% 




4/90 




b 
133% 




4/90 




b 
133% 


140% 


4/90 


10/90 


133%" 




4/90 





133% 
4/90 



133% 
4/90 



133% 
4/90 

133%' 

4/90 

13 3%" 

4/90 



185% 
7/90 



185% 
7/91 



160% 
4/91 



150% 
7/91 



> 



Table A.l 

Medicaid Eligibility Thresholds and Effective Dates for 

Expansions of Coverage for Pregnant Women and Infants 

January 1987 - December 1991 (Continued) 



Apr 



Jul 



Jan Apr 



Jul 



19B9 



Jan Apr 



Jul 



Apr 



199 1 



Jan Apr 



Kentucky 

Louisiana 

Maine 

Maryland 

Massachussetts 

Michigan 

Minnesota 

Mississippi 



35% 



Nevada 

New Hampshire 
New Jersey 

New Mexico 

New York 

Nor t h Carol ina 



71% 



53% 



38% 



71% 



34% 



100% 
7/87 
100% 
7/87 



100% 
7/87 



100% 
10/87 



100% 
10/87 



100% 
1/88 



100% 
7/88 



125% 
10/88 



185% 
10/88 







185% 








7/88 






100% 




185% 




1/88 


185% 
7/88 


10/88 


100% 




185% 




0/87 


100% 
1/88 


7/88 





100% 
10/88 



100% 
1/89 



185% 
7/89 



100% 
7/89 



75% 
7/89 

75%' 
7/89 



133% 


185% 


4/90 


7/90 


b 
133% 




4/90 





133% 

4/90 

b 
133% 

4/90 

b 
133% 

4/90 

b 
133% 

4/90 

b 
133% 

4/90 





133% 




4/90 


185% 




1/90 




150% 




1/90 





133% 
4/91 



185% 
7/91 

185% 
7/91 



185% 
10/90 



> 
I 



Tabla A.l 

Medicaid Eligibility Thresholds and Effective Dates for 

Expansions of Coverage for Pregnant Women and Infanta 

January 1987 - December 1991 (Continued) 



Apr Jul 



Jan Apr Jul Oct 



1989 



Jan Apr Jul 



Jan Apr Jul 



Jan Apr Jul 



North Dakota 



Oregon 

Pennsylvania 
Rhode Island 
South Carolina 

South Dakota 
Tennessee 



56% 



4 5* 



)',* 



100% 
4/87 



85% 
11/87 



100% 
10/87 



100% 
7/87 



Utah 


91% 




Vermont 


81% 




Virginia 


47% 




Washington 


73% 


90% 

7/87 


West Virginia 


38% 


100% 
7/87 



100% 
10/87 



100% 
1/88 



100% 
4/88 



100% 
9/88 



100% 
7/88 



100% 
9/88 



185% 
7/88 

100% 
7/88 



150% 
7/88 



185% 
10/88 



100% 
1/89 



100% 
1/89 



75% 
7/89 



85% 
7/89 



185% 
7/89 



130% 
9/89 



185% 
7/89 



150% 
1/90 



133% 


4/90 


b 
133% 


4/90 


b 
133% 


4/90 


b 
133% 


4/90 


b 
133% 


4/90 



133% 

4/90 



133% 

4/90 

b 
133% 

4/90 



133% 
4/90 



185% 
7/91 



o> 



185% 
12/91 



Table A.l 

Medicaid Eligibility Thresholds and Effective Dates for 

Expansions of Coverage for Pregnant Women and Infanta 

January 1987 - December 1991 (Continued) 



STATES 



1988 



Apr 



Jan Apr 



1989 



Jan Apr 



Apr 



1991 



Apr 



Wi scons i 



Wyi jin i ng 



84* 



100% 
10/88 



133* 


1SS% 


4/90 


7/90 


b 
1 33% 




4/90 





Figure represents stares' AFDC or Medically Needy Income threshold (whichever is most generous) as a percent 
of the Federal poverty level for a f.imily of three. 

states complying with federal mandate. 



From 9/88 to 1/89, the state funded a program covering pregnant women and infants up to 120% of poverty. 
Between 7/H9 and 4/90, the income limit for this program was raised to 130% of poverty. 

lource: Hill. Ian T. Pis. Medicaid Expansions for Preaanant Women and rhldren: A state 

Pic-gr a m Character i st i cs 'nj ormat i on B a se . Washington, D.C. : Health Systems Research, Inc. 

for Health Care Financing Administration. February 10, 1992. 



> 

i 



A-8 



Table A. 2 
Presence of Outreach Campaigns and Enhanced Prenatal Care Benefits 



Statewide Public Enhanced 

States Information/Outreach Campain Prenatal Care 

Alabama X X 

Alaska X X 

Arizona a 

Arkansas X . X 

California X X 

Colorado X 

Connecticut X 

Delaware X 

D.C. X 

Florida 

Georgia X 

Hawaii X X 

Idaho X X 

Illinois X X 

Indiana X 

Iowa X X 

Kansas X 

Kentucky 

Louisiana X 

Maine 

Maryland X X 

Massachusetts X X 

Michigan X X 

Minnesota X X 



A-9 



Table A. 2 
Presence of Outreach Campaigns and Enhanced Prenatal Care Benefits (Continued) 



States 



Mississippi 
Missouri 
Montana 
Nebraska 
Nevada 

New Hampshire 
New Jersey- 
New Mexico 
New York 
North Carolina 
North Dakota 
Ohio 

Oklahoma 
Oregon 
Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 



Statewide Public 
Information/Outreach Campain 



Enhanced 
Prenatal Care 



X 
X 



X 
X 
X 
X 
X 



X 
X 

X 

X 
X 
X 
X 
X 
X 

X 
X 
X 

X 

b 



X 
X 

X 
X 
X 
X 
X 
X 
X 



Source: Hill, Ian T. The Medicaid Expansions for Pregnant Women and 
Children: A State Program Characteristics Information Base. 
Washington, D.C. : Health Systems Research, Inc. for the 
Health Care Financing Administration. February 10, 1992. 

Arizona provides these services, when medically indicated, through 
the Arizona Health Care Cost Containment System (the state's 
Medicaid program), begun in 10/82. 



Starting in January 1988, Rhode Island's state - funded Rite Start 
program extended enhanced prenatal services to low- income pregnant women. 



A-10 



Table A. 3 

Effective Dates for State Strategies to Streamline 

Medicaid Eligibility 



States 


Drop 
Assets 


Continuous 
Eligibility 


Presumpt 
Eligibil. 


ive 
ity 


Outstation 

Eligibility 

Workers 


Shorten 

Application 

Form 


Expedite 
Eligibility 


Alabama 


7/88 


7/88 


7/88 to 7/91 


1/89 


4/90 


9/91 


Alaska 


1/89 


1/89 






7/91* 




1/89 


Arizona 


1/88 


1/88 






7/91 a 






Arkansas 


10/88 


4/87 


4/87 




7/91° 






California 




1/91* 






5/90 


11/91 


1/89 


Colorado 


7/90 


7/90 


1/90 




7/91* 


7/91 




Connecticut 
Delaware 


4/88 
1/88 


4/88 
1/88 


7/91 




7/91* 
1/88 


7/91 
1/88 


7/91 
1/88 


D.C. 

Florida 
Georgia 


4/87 

10/87 

1/89 


4/87 
10/87 
1/89 


7/91 
10/87 




7/91* 
7/86 
1/89 


7/86 
1/89 


11/86 
7/89 


Hawaii 


1/89 


1/89 


1/89 




7/91' 


10/91 




Idaho 


1/89 


1/89 


1/89 




7/91* 


7/91 




Illinois 


9/91 


10/88 


1/89 




9/91* 


9/91 




Indiana 
Iowa 


7/88 


7/88 
7/89 


7/88 to 7/91 
7/89 


7/91* 
9/90 


6/92 




Kansas 


7/88 


1/91* 






7/91* 




7/88 


Kentucky 
Louisiana 


6/89 
1/89 


8/88 
1/89 


1/89 




7/91* 
1/89 


9/89 
1/89 




Maine 


10/88 


10/88 


10/88 




7/91* 






Maryland 


7/87 


7/87 


7/87 




7/91* 


7/87 




Massachusetts 
Michigan 


7/87 
10/88 


7/87 
10/88 


7/87 




7/91* 
10/88 


2/90 
1/89 





A-ll 



Table A. 3 

Effective Dates for State Strategies to Streamline 

Medicaid Eligibility (Continued) 



States 


Drop 
Assets 


Continuous 
Eligibility 


Presumptive 
Eligibility 


Outstation 

Eligibility 

Workers 


Shorten 

Application 

Form 


Expedite 
Eligibility 


Minnesota 

Mississipi 

Missouri 


7/88 
10/88 

7/90 


7/88 

10/87 
7/90 




7/90 


7/91* 
10/87 
9/89 


7/88 
7/91 


7/88 


Montana 


7/89 


1/91* 




1/91 


7/91* 






Nevada 


7/89 


11/91* 






7/91* 






New Hampshire 


7/89 


1/91* 












New Jersey- 
New Mexico 


7/87 
12/88 


7/87 
7/89 




5/88 
4/89 


7/91* 
1/90 


8/88 
1/90 




New York 
North Carolina 


1/90 
10/87 


1/90 
10/87 




1/90 
10/87 


7/91* 
10/87 


1/91 




North Dakota 




1/91* 






7/91* 






Ohio 


1/89 


11/91* 






4/91 


4/91 


4/91 


Oklahoma 
Oregon 


4/88 

11/87 


4/88 
11/87 




7/90 


7/91* 
9/90 


7/88 


7/88 


Pennsylvania 


4/88 


1/91* 




4/88 


7/91* 






Rhode Island 
South Carolina 


4/87 
10/87 


4/87 
10/87 






7/91* 
11/87 


12/89 




South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 


7/88 
3/88 
12/91 
1/89 
7/89 
7/88 


7/88 
7/87 
9/88 
1/89 
4/87 
7/89 




2/89 
9/89 
3/89 


7/91* 
7/87 
1/90 
1/89 
10/89 
7/89 


7/88 

9/89 

10/89 
7/88 


10/89 
7/88 


Washington 


7/89 


7/87 






7/91* 


2/90 


1/90 


West Virginia 


7/87 


7/87 






7/91* 


4/88 


7/88 


Wisconsin 


7/89 


7/89 




4/88 


7/91* 


10/90 


1/90 


Wyoming 


10/88 


10/88 






7/91* 






Source: Hill, 


Ian T. 
rharactei 


The Medicaid Exoansions for 


Preanant Women 


and Children 


: A 


State Proaram C 


ristics Information 


Base. Wa 


ishington, D.C. 


: Health Sys 


terns 



Research, Inc. for the Health Care Financing Administration, February 10, 1992 



a States complying with federal mandates. 



A-12 



Table A. 4 
State And Local Health Care Delivery System Characteristics, 1989 





Total MCH 


Total women 




Monies 


served by 


States 


(in thousands) 


MCH 


Alabama 


$28, 532 


20,172 


Alaska 


6,318 


25 


Arizona 


21,418 


4,553 


Arkansas 


17,262 


8,726 


California 


206,608 


30,197 (1986 data) 


Colorado 


16,592 


4,000 


Connecticut 


12,176 


4,933 


Delaware 


5,791 


1,779 


D.C. 


16,454 


1,032 


Florida 


109,121 


43,081 


Georgia 


57,416 


11,033 


Hawaii 


14,973 


219 


Idaho 


4,652 


553 


Illinois 


41,460 


4, 184 


Indiana 


24,393 


2,809 


Iowa 


14,312 


2,179 


Kansas 


8,049 


2,398 


Kentucky 


39,494 


12,874 


Louisiana 


37,593 


17,539 (1986 data) 


Maine 


7,950 


1,066 (1986 data) 


Maryland 


150,064 


N/A 


Massachusetts 


26,841 


12,000 


Michigan 


86,159 


N/A 


Minnesota 


15,311 


4,660 


Mississippi 


29,914 


17,290 


Missouri 


$20,390 


8,069 


Montana 


c 





Nebraska 


3,644 


946 


Nevada 


6,378 


596 



Ratio women Total women Ratio women 
served by MCH served by served by C/MHCs 
to all women C/MHCs to all women 



2.1% 
0.0% 
0.5% 
1.7% 
0.4% 
0.5% 
0.6% 
1.1% 

0.6% 
1.5% 
0.7% 
0.1% 
0.2% 
0.2% 
0.2% 
0.4% 
0.4% 
1.5% 

1.8% 
0.4% 

N/A 
0.8% 

N/A 
0.5% 
2.9% 
0.7% 

0.0% 
0.3% 

0.2% 



6 


,245 




342 


1 


,609 




208 


20 


,592 


9 


,361 


1 


,688 




249 




622" 


13 


,378 


2 


,319 




584 


1 


,836 


2 


,502 




404 


1 


,544 




511 


2 


,511 


1008" 




8 


2 


,578 


4 


,555 


2 


,792 


1 


,313 


2 


,413 


4 


,754 




562 




288 




509 



0.66% 
0.25% 
0.19% 
0.04% 
0.29% 
1.15% 
0.22% 
0.15% 

0.37% 
0.48% 
0.14% 
0.22% 
0.82% 
0.09% 
0.03% 
0.25% 
0.09% 
0.29% 

0.10% 
0.00% 
0.22% 
0.31% 
0.13% 
0.13% 
0.40% 
0.41% 

0.32% 
0.08% 
0.18% 



A-13 



Table A. 4 
State And Local Health Care Delivery System Characteristics, 1989 (Continued) 





Total MCH 


Total 


women 




Ratio women 


Total women 


Ratio women 




Monies 


served by 




served by 


MCH 


served by 


served by C/MHCs 


States 


(in thousands) 


MCH 




to all women 


C/MHCs 


to all women 


New Hampshire 


6,484 


811 






0.3% 




367 


0.13% 


New Jersey 


23,553 


9,819 






0.5% 




6,310 


0.35% 


New Mexico 


8,249 


4,646 






1.3% 




254 


0.07% 


New York 


59,879 


53,325 






1.2% 




18,095 


0.42% 


North Carolina 


53,687 


28,741 






1.8% 




4,877 


0.31% 


North Dakota 


3,278 


1466' 






1.1% 




N/A 


N/A 


Ohio 


48,889 


23,096 






0.9% 




7,504 


0.30% 


Oklahoma 


17,329 


5,214 


(1983 


data) 


0.7% 




355 


0.05% 


Oregon 


18,712 


6675* 






1.0% 




3,752 


0.58% 


Pennsylvania 


53,557 


25,445 






0.9% 




3,470 


0.13% 


Rhode Island 


7,147 


3,553 






1.5% 




2,513 


1.06% 


South Carolina 


45,446 


22,865 






2.7% 




3,927 


0.47% 


South Dakota 


3,492 


54 






0.0% 




13 


0.01% 


Tennessee 


42,506 


14,195 






1.2% 




1,810 


0.16% 


Texas 


90,204 


77,429 






1.9% 




7,647 


0.19% 


Utah 


10,809 


468 






0.1% 




949 


0.24% 


Vermont 


6,719 


4,431 






3.3% 




41 


0.03% 


Virginia 


56,283 


16500* 






1.1% 




910 


0.06% 


Washington 


22,514 


3,669 






0.3% 




5,444 


0.47% 


West Virginia 


18,219 


5,282 






1.3% 




4,437 


1.10% 


Wisconsin 


15,990 


301 






0.0% 




1,203 


0.11% 


Wyoming 


3,788 









0.0% 




10 


0.01% 


Source: Public 


Health Aaencies 


1991: An 


Inventorv 


of Proarams 


and 


tion, 1991. 




Expenditures. Washinaton. D.C.: 


The 


Public Health Founda' 




Carina 


for Mothers and 


Children: 


A ReDort 


of a Survev 


of 1 


Hf 1987 




State MCH Proaram Activities. W 


ashinc 


fton, 


D . C . : The . 


Association 





of Maternal and Child Health Programs, March 1989. 

Directory of Community and Migrant Health Centers . Washington, D.C. : 
The National Association of Community and Migrant Health Centers, 1990. 



1990-191 Grant Application . Rockville, MD. : Division of Primary 
Care Services, Bureau of Primary Health Care, Health Resources and 
Services Administration, U.S.. Department of Health and Human Services, 
1992 

a Estimated figure AMCHP, 1987. 

b Data from calendar year 1990. 

c Montanta did not report to Public Health Foundation in 1989. 



KcS 



Health Systems Research, i nc 

2021 l Street nw Suite 400 
Washington OC 20036 
'202) S28.5100 
Fax: (202) 728.9469 



Appendix B 

IMPLEMENTING THE MEDICAID EXPANSIONS FOR PREGNANT WOMFX- 
THE EXPERIENCE IN FLORIDA "WUH. 



Prepared for: 

Office of Research and Demonstrations 
Health Care Financing Administration 
Baltimore, MD 
Cooperative Agreement 18-C-901 13/9-01 



Prepared by: 

Ian Hill 

Health Systems Research, Inc. 

Washington, DC 



Under Subcontract with: 

The RAND Corporation 
Washington, DC 
Subcontract #91-18 



24 July 1995 



Acknowledgments 

The author would like to express his sincere gratitude to the many persons who devoted their 
time and energy to site visit interviews and were kind enough to submit additional document 
and reports describing their efforts. Specifically, thanks are to be extended to the follow?™ 
Florida Department of Health and Rehabilitative Services officials: Charles Mahan Donna 
Barber. Meade Grigg, Fred Roberson. Lynn Bodiford. Molly Melor. Gary Cravton Manlvn 
Reaves. Michael Cuppoli. and Phyllis Siderits. The author would also like to thank Garv" 
Clarke, tormer Deputy Assistant Secretary for Medicaid, for his critical insights into the' 
historical events leading up to Florida's Medicaid expansions. 

Many thanks are also extended to Project Officer Marilyn Hirsch at the Office of Research and 
Demonstrations. Health Care Financing Administration, for her input on the design of the 
evaluation and for her guidance throughout the development of this report. 

At RAND, both Stephen Long and Susan Marquis are to be thanked for their energetic 
participation in the Florida site visit as well as their critical advice and guidance in carrying out 
this qualitative evaluation. 

Finally, at Health Systems Research, Inc., the author thanks Renee Schwalberg for her 
thorough analysis of the HCFA 2082 data. 



Health Systems Research, Inc. 



Table of Contents 



I. Background „ 

1 



II. The Impetus for Medicaid Expansions in Florida. 

A. Passage of the Health Care Access Act of 1984 .. 



.j 



.j 



B. Lack of Impact and the Need for Additional Expansion 

III. Florida's Systems for Providing Maternity Care 

A. Organization of State Agencies 

6 

B. The Public Health Service Delivery System 8 

C. Federally-Funded Primary Care Centers 8 

D. The Role of Private Physicians . Q 



IV. Expanding Medicaid and Improving Its Ability to Serve Mothers 1 1 

A. Expanding Medicaid Eligibility , -, 

B. Simplifying the Medicaid Eligibility Process j 2 

C. Promoting Use of Prenatal Care Through Outreach 14 

D. Improving Physician Participation in Medicaid 1 5 

E. Providing Technical Assistance to Counties to Facilitate Effective Implementation 17 

V. Key Findings and Implications for the Evaluation 19 

A. Improvements in Enrollment, Expenditures, Revenues, and Outcomes 19 

B. Qualitative Impressions of Program Impact and Lessons Learned 25 

Works Cited 
Appendix A. 



Health Systems Research, Inc. 



[. Background 

In March 1992. the federal Health Care Financing Administration (HCFA) awarded a 
Cooperative Agreement to the RAND Corporation (RAND) and its subcontractor Health 
Systems Research, Inc. (HSR), to study the impact of the Medicaid eligibility expansions for 
pregnant women on state service delivery and financing sv stems for maternity care The 
methodology tor the study includes both quantitative and qualitative components The 
quantitative analysis, which will be conducted by RAND, involves a detailed studv of how the 
Medicaid eligibility expansions affected how pregnant women flow through prenatal care and 
delivery systems and how the amount and distribution of funds supporting prenatal and 
delivery services changed among payers. The qualitative analvsis. to be completed by HSR 
involves a similarly detailed study of how a selected jurisdiction enacted Medicaid expansions 
and. in particular, how this jurisdiction implemented strategies in an effort to ensure that access 
to. and quality of, prenatal care improved as a result of the expansions. 

During the summer of 1992, the project developed a report entitled Impacts of Medicaid 
Eligibility Expansions and Innovative Programs for Maternal Health Care: Methodology and 
State Selection Report (Hill, Long, and Marquis, 1992). In it, the authors detailed the analytic 
framework and estimation methods to be used in conducting the study. Further, the report 
presented a 50-state typology describing selected characteristics of state Medicaid and Title 
V/Maternal and Child Health (MCH) programs, as well as state and local health care delivery 
systems for maternity care. A primary purpose behind the development of the typology was to 
assist the RAND/HSR research team with the selection of a state, or states, to include in the 
study. The report concluded that the research effort should focus on the State of Florida 
because it is a state that significantly expanded Medicaid eligibility for pregnant women in 
response to federal statutory changes, aggressively implemented numerous strategies to 
streamline access to Medicaid coverage, possesses a strong prenatal care service delivery 
system composed of a mix of public and private providers, maintains multiple databases that 
would support a sophisticated quantitative analysis, and has no other significant studies of the 
Medicaid expansions already underway. In addition and importantly, the director of the state 
Medicaid program and the state health officer both offered to cooperate with the research team 
in the conduct of the study. 

In November 1992, HSR Project Leader Ian Hill and RAND Project Leaders Stephen Long and 
Susan Marquis conducted a two-day site visit to Florida. During the visit, team members 
conducted interviews with numerous officials representing the Medicaid, MCH, and Children's 
Medical Services programs within the state Department of Health and Rehabilitative Services 
(HRS), as well as officials from the newly created Agency for Health Care Administration 
(AHCA). While RAND team members focused their interviews on issues surrounding the 
existence and collection of data for the quantitative analysis, Mr. Hill spoke with state officials 
about the impetus for, and objectives behind, the Medicaid expansions, the specific policies 
and programs that were enacted, strategies to implement initiatives at the local level, and 
impressions regarding the successes and failures of the changes in the program. 
This report represents the final qualitative analysis of Florida's experience with implementing 
the Medicaid expansions for pregnant women. Based on information gathered during the site 

I 

Health Systems Research, Inc. 



S^tSIT* ob,a,ned from s,a,e 0,T,cials ' ,h,s repm «—• >■««— in , he 



following sections: 



■ In Section II. the various factors leading up to Honda's decision to expand 
Medicaid coverage o low-income pregnant women will be discussed, including 
summaries of the health and socio-economic status of child-bearing women 
during the mid-1980s and the political environment of the penod that pr" vLd 
the impetus for change. ynwaea 

■ In Section III. an overview of Florida's prenatal care systems will be provided 
including summaries of the organizational structure and roles and 
responsibilities of the state agencies involved with the delivery and financing of 
care, and the public and private delivery systems in place at the local level. 

■ In Section IV. the specific policy and program changes enacted to improve 
access to Medical- financed prenatal care will be described, including detailed 
descriptions of strategies that were employed to ensure effective implementation 
ot these initiatives. 

■ In Section V, the key findings of the qualitative evaluation will be presented 
including summaries of state officials' impressions of the impacts of their 
efforts, and descriptive data illustrating how the Medicaid expansions affected 
Medicaid enrollment and expenditures and documenting positive trends related 
to birth outcomes and access to prenatal care. 

The qualitative knowledge gained through this case study provides the project with critical 
insights into the factors that contributed to Florida's successes and/or failures in expanding 
Medicaid coverage for pregnant women. In addition, the narrative allows the research team to 
more fully understand and accurately interpret the outcomes and implications of the various 
quantitative analyses being conducted by RAND. 



Health Systems Research, Inc. 



on 



II. The Impetus for Medicaid Expansions in Florida 

In Florida during the early 1980s, the health of the state's newborns was verv poor fn 
1983. infants in the state died at a rate of 12.2 per 1.000 live births compared to the national 
average or 1 1.2. On this indicator. Florida ranked 41st among the 50 states Further 7 4 
percent ot all intents bom that year were low birthweight (less than 2 500 grams) a rate rh.t 
did not compare favorably to the national average of 6.8 percent and ranked the state 39th o 
this indicator. Not surprisingly, indicators of women's access to, and utilization of nrenata 
care were similarly poor. For example, the percentage of women who received prenatal care 
during their first trimester of pregnancy was 68.2-compared to 76.2 percent nationally and 
ranking the state 45th--while the percentage who received late or no prenatal care was 8 5 

HedS g Stetis?« 46tH "* C ° mpared t0 a nati ° nal aVerage ° f 56 percent - (National Center for 

Poor health status among mothers and children was but one symptom of a much broader 
medical indigency problem in Florida during the period. Roughly 15 percent of the state's 
total population was uninsured for health coverage, compared to the national average of 1 1 
percent (Current Population Survey, 1986-89). And, after excluding the elderly this rate rose 
to 22 percent (Clarke, 1995). The state Medicaid program, the principal source 'of health 
insurance for low-income families, was limited in its coverage. Specifically, the income 
eligibility threshold for a family of three under the state's Aid to Families with Dependent 
Children (AFDC) program, to which Medicaid eligibility was linked, was set at just 3 1 percent 
of the federal poverty level, a threshold that was more strict than that of all but 1 1 states (Social 
Security Administration, 1984). Further, in 1983, Florida was one of just 16 states that did not 
cover the optional Medically Needy group under its Medicaid program (HCFA, 1984). 
Overall, Medicaid had not succeeded in providing coverage to a significant proportion of the 
state's poor; just 24 percent of all persons living below the federal poverty level were Medicaid 
recipients in 1984 (Health Care Financing Administration, 1985). 

The burden of medical indigency was falling heavily upon the hospitals in the state and 
disproportionately on public and not-for-profit institutions. For example, three of the more 
than 200 general hospitals in Florida accounted for more than 20 percent of all Medicaid 
hospital days and 35 percent of all charity care provided in the state (Clarke, 1986). These 
same three facilities provided more Medicaid and charity care than all 85 for-profit hospitals 
combined (Clarke, 1986). As health care costs generally and hospital costs specifically 
continued to rise faster than national averages, state officials, politicians, and industry officials 
all recognized the need for change. 



A. Passage of the Health Care Access Act of 1 984 

In 1983, a newly-formed commission, headed by State Senator Bob McKnight and called the 
Task Force on Competition and Consumer Choice, conducted hearings across the state and 
began developing proposals for statewide policy changes. After extensive analysis of a range 
of options, including those of both a competitive and a regulatory nature, the commission 



Health Systems Research, Inc. 



spearheaded the development of a broad-based consensus among state officials hn.«i. , 

;~^T munity vvhich resuited in the ^ ° f - «^^^ 

The law contained several provisions intended to contain the rate of growth of hospual costs 
reduce the number ot persons who were medically indigent, and finance and more ecu tab v 
distribute the bad debt absorbed by hospitals who served the poor. Perhaps the mo Umponant 
provision ot the law .mposed a one-percent tax on the net operating revenues of FlondT 
hospitals to be raised to 1.5 percent in the second and all subsequent vears, to finance 
Medicaid and primary care expansions. The law also created the Public Medical Assistance 
Trust Fund into which state appropriations and hospital tax revenues would be deposited and 
trom which monies would be drawn to pay the health care costs of newly covered Medicaid 
recipients. Importantly revenues placed in the Fund would be used to draw down additional 
federal Medicaid matching funds at the rate of 56 percent. 

The Health Care Access Act also authorized expansions of Medicaid eligibility to include 
several previously uncovered optional groups as well as an appropriation to expand county 
health departments capacity to provide primary care services to low-income persons as 
described below. K ' 

■ Effective July 1,1985, Medicaid eligibility was expanded to include married 
pregnant women, children under age 21 in intact families, and unemployed 
parents and their children under age 1 8 in families meeting the AFDC 
program's eligibility thresholds. 

■ Effective July 1 , 1 986, Medicaid was expanded to include coverage of the 
Medically Needy, that is, persons who met the program's categorical 
requirements but whose income was too high to qualify them for either the 
AFDC or Supplemental Security Income (SSI) programs. This expansion 
effectively raised the income eligibility threshold for families to 47 percent of 
the federal poverty level. 

■ An appropriation of $ 1 million was authorized to support county health 
departments' provision of primary care services, with the distribution of funds 
based on a county's need and willingness to participate. 

These and other provisions of the law reflected the desire among all the various public- and 
private-sector partners to develop systems reforms in a comprehensive and consensual manner. 
The hospital revenue tax and creation of the Trust Fund, in particular, were seen as strategies 
that would "level the playing field" for hospitals by allowing each to recover its costs in direct 
proportion to the amount of Medicaid care it provided. At the time, the law seemed quite 
likely to succeed; according to one estimate over 300,000 persons would be made eligible for 
Medicaid as a result of the eligibility expansions (Lou Harris and Associates, 1985). In a 
relatively short time, however, problems arose. 



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B - Lack of Impact and the Need for Additional E^ a o sifl n 

By 1987. policymakers and providers were becoming increasingly frustrated bv an apparent 
lack of impact ot the law. By July of that year, only slightly more than 16.000 persons had 
enrolled under the expansions of both categorically and medically needy eligibility eroum 
Vorse. the Public Medical Assistance Trust Fund reported a SI 80 million surplus'bv mid 
1987 causing hospital officials across the state to cry foul and government officials'to besin 
scrambling to identify more effective strategies for expanding low-income families- financial 
access to health care and putting the hospital tax revenues to good use. Fortunately this cm < 
co.ncided closely with events at the federal level that altered the Medicaid statute to give states 
new flexibility to expand their programs for pregnant women and young children. 

The remainder of this report will describe how the State of Florida reacted to this opportunity 
not only by adopting sweeping expansions of Medicaid eligibility for mothers and children but 
also by implementing numerous strategies and initiatives to help ensure that these expansions 
actually resulted in improved access to, and use of, Medicaid-financed prenatal care. As will 
be described in Section IV of this report, these strategies included efforts to simplify and 
streamline the Medicaid eligibility process, to conduct outreach to inform women of the 
importance of prenatal care and the availability of Medicaid coverage, and to enhance public 
and private providers' willingness and capacity to serve low-income mothers. To provide a 
context^ within which to consider these strategies. Section III will first provide an overview of 
Florida's systems for providing and financing maternity care. 



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III. Florida's Systems for Providing Maternity Care 

This section presents an overview of Florida's systems for providing and financing m af 
care Specifically, it describes the structure, roles, and responsibilities of the state aSS* 
involved in caring tor mothers and children, the organizat.on of the public sector service 
delivery; system tor prenatal care, the number and distribution of federallv-runded primary care 
centers ,n the state, and the traditional role of private sector physicians in serving low-mcomT 
mothers and their families. income 



A. Organization of Stare AgenH^ 

Until 1993, all of the state agencies involved in serving disadvantaged families generally and 
low-income pregnant women specifically were housed in the single "umbrella" agency 'the 
Department of Health and Rehabilitative Services (HRS). 1 As illustrated in Figure 1 the 
principal programs serving these groups were organized into three divisions, as described 
below. 

■ Public Health. Under the direction of the Deputy Secretary for Health, this 
division oversaw programs related to environmental health, disease control and 
AIDS prevention, technical health services, and personal health and primary 
care. Within the office of Personal Health and Primary Care, the MCH program 
serves as the designated grantee of the federal Title V Block Grant. 

■ Programs. Under the direction of the Deputy Secretary for Programs, this 
division housed the programs for regulation of health facilities, developmental 
services, aging and adult services, alcohol, drug abuse and mental health, and 
children, youth and families. Of particular relevance to this report, the division 
also housed the Medicaid program, the office of Economic Services 
(responsibility for determining eligibility for Medicaid, AFDC, Food Stamps, 
and a variety of other public welfare programs), and the Children's Medical 
Services program (responsible for administering the Title V Children with 
Special Health Care Needs program as well as the Regional Perinatal Intensive 
Care Centers program for high-risk pregnant women and newborns). 

■ Operations, Under the direction of the Deputy Secretary for Operations, this 
division served a liaison function between the state and local levels by 
administering all HRS programs through its network of 1 1 District Offices and 
67 local public health units. 



The Health Care Reform Act of 1992 created the new Agency for Health Care Administration (AHCA) in an 
effort to consolidate under one structure all state agencies involved with health care purchasing and regulation. 
The Medicaid program, as well as programs related to provider licensure and certification, certificate of need, 
comprehensive health planning, and hospital cost containment were moved out of HRS. 

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Figure 1 

ORGANIZATIONAL STRUCTURE OF THE 

DEPARTMENT OF HEALTH AND REHABILITATIVE SERVICES* 








Deputy Secretary 
for Health 














Environmental 
Health 




Disease Control 
- & AIDS Prevention 








Technical 
Health Services 




Personal Health 
- & Primary Care 



Organizational structure in effect October 1988 



HRS 

Secretary 



Deputy Secretary 
for Operations 



District 
Administrator 



HRS Public 
Health Units 



1 



Deputy Secretary 
for PrograiiK 



Medicaid 



Children's 
Medical 
Services 



Aging and 
Adult Services 



Economic 
Services 



J 



Regulation & 

Health 

Facilities 



Developmental 
Services 



Children, Youth 
and Families 



Alcohol, Drug 
Abuse & Mental 

I lea lib 



B. The Public Health Service De livery Svsjffim 

The State of Florida is divided into 67 counties, each of which has its own local health 
department (LHD). [ n «taL these 67 LHDs operate some 220 clinic service sites As 
illustrated in Figure 2. Florida's counties are also organized into 1 1 Health Districts each of 
which has a headquarters office that serves a liaison role between the state and local levels 
Importantly, all district and local offices are "arms" of state government and are staffed bv 
state employees. Therefore, the central HRS office has direct authority over how policies and 
programs are implemented at the local level. 

As is the case in many Southern states, LHDs in Florida have traditionally plaved a major role 
in providing services directly to low-income individuals and families. In most instances LHDs 
are staffed by a full complement of public health nurses, health educators, nutritionists and 
other ancillary staff. Approximately one-half of all LHDs have physicians on staff, while the 
remainder work with community physicians under contract with the state. A typical LHD 
provides a broad array of preventive and primary care services, including well-child exams 
immunizations, pregnancy testing and family planning services, screening for sexually- 
transmitted diseases, and WIC. Importantly, a major portion of LHDs' service capacity is 
devoted to the delivery of prenatal care. Beginning in 1982, the state implemented the 
Improved Pregnancy Outcomes (IPO) project to channel special grant monies to the counties to 
foster the development of more comprehensive systems of prenatal care. Through the IPO 
project, Florida was able to raise the quality of county prenatal programs to a relatively equal 
plain. By the mid-1980s, most LHDs provided not only clinical prenatal services using 
contract obstetricians (OBs) and certified nurse midwives (CNMs), but also offered a wide 
range of psychosocial support services, including health education, nutritional counseling, 
social work services, and home visiting. 

Historically, state general revenues and federal Title V Block Grant moneys comprised more 
than 75 percent of LHD budgets; county funds have never supported a majority of LHD 
operating costs. Primary care monies authorized by the Health Care Access Act were initially 
distributed to 18 counties through a competitive Request for Proposals process and have been 
credited with giving LHDs in those counties a revitalized role in providing and brokering 
indigent care (HRS, 1986). Notably, LHDs rarely billed Medicaid when serving Medicaid- 
eligible women and children prior to 1987. As will be described in the next section of this 
report, increasing LHDs' capacity to capture Medicaid revenues to support service delivery 
represented a major objective of HRS after the state implemented the Medicaid expansions. 

C. Federally-Funded Primary Care Centers 

Florida also boasts an extensive network of Federally-Qualified Health Centers (FQHCs), that 
is. Community Health Center (CHC), Migrant Health Center (MHC), and Health Care for the 
Homeless projects. In all, 46 grantee providers operate some 118 clinics, most often 



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Figure 2 
HRS District Boundaries 

Effective October 1984 




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situated ^relatively urban regions of the state. , Twenty-seven providers receive CHC 
bection 3^-funds and operate 70 clinics. 15 providers receive MHC-Sect.on 329-fonds and 
operate 38 clinics, and tour Homeless Health Care grantees oversee service delivery in 10 
sues.) (National Association of Community Health Centers. 1991). Bv definition and «■ 
requirement of receiving federal funds, these clinics provide a comprehensive arrav of pnmarv 
care services to all populations, regardless of ability to pay. L.ke their LHD counterparts 
tederally-tunded climes represent a major source of preventive and primarv care for low 
income families. ' 

In an effort to better integrate their service delivery efforts. LHDs and FQHCs have 
increasingly negotiated arrangements whereby public health units take responsibility for 
providing prenatal care services to Medicaid patients while FQHCs provide well-child and 
other primary care services for families. Of note, nearly 40 percent of the $10 million in new 
primary care funds appropriated to LHDs in 1984 were channeled to private providers via 
contracting arrangements. Of these, the largest proportion went to FQHCs (HRS, 1986). 

D. The Role nf Private Phvsirian^ 

As is also the case in many Southern states, private physicians have not historically played a 
significant role in serving poor and disadvantaged families. Rather, they have preferred to 
leave this responsibility to LHDs and FQHCs. This situation is borne out by historically low 
participation rates among physicians in the Florida Medicaid program. Low fees and 
cumbersome administrative rules are usually blamed for this lack of participation, and often for 
good reason; in 1986, Medicaid paid obstetricians a global fee of just $315 for providing both 
prenatal care and delivery services to a Medicaid-eligible pregnant woman. In addition, the 
economic impact of malpractice has dramatically stifled physician participation in Medicaid 
Malpractice insurance crises in both the 1970s and 1980s resulted in extremely high premiums 
-for OBs, rates were as high as $200,000 per year, and averaged $65,000 in 1986-and limited 
availability (Clarke, 1986). As will be discussed in the next section, a major objective of 
perinatal reform efforts in the late 1980s was to restructure payment and administrative policies 
so that physicians would be more willing to serve Medicaid mothers. 

The State of Florida does possess the largest number of CNMs of any state-350 in 1992. In 
contrast to obstetricians, these clinicians have traditionally been very willing to serve low- 
income women and have worked closely with both LHD and FQHC providers. 



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[V. Expanding Medicaid and Improving Its Ability to Serve Mothers 

As discussed in Section [I. 1987 found Florida policymakers in the midst of a continued 
indigent care crisis. Incremental Medicaid expansions enacted in 1985 and 1 986 w ere Lnn 
to draw significant numbers of new recipients into the program and the Public Med cal 
Assistance Trust Fund, established to pay for the health care costs of new Medicaid !Lkl 
and supported by a new tax on hospital revenues, had built up a surplus of mU onso T n 
that was sitting unused. Meanwhile, the problems of infant mortaJ^Id mc 2K££S 

; o^i h ; h state H 7 R r of infant monaiity *« iow ^^ - '«s 

S™ PerCCm ' reSpeCtlVely " COntinued t0 Ia * * behind national avenges 

During the previous year, however, the nation's infant mortality crisis had gained 
unprecedented attention at the federal level. Citing indicators that placed the United States 
behind 17 other industrialized nations, advocacy groups like the Children's Defense Fund 
succeeded in getting the attention of national policymakers (Children's Defense Fund 1989) 
Documenting that an investment in prenatal care is cost-effective-specifically that over S3 00 
can be saved in avoided neonatal costs for every S 1 .00 spent on prenatal care-'the Institute of 
Medicine lent credibility to the call for perinatal system reform (Institute of Medicine 1 985) 
Finally, a strong and well-organized coalition of southern states, the Southern Regional Task 
Force on Infant Mortality, drafted a simple but practical proposal to sever the traditional link 
between AFDC and Medicaid eligibility and allow states to target large-scale Medicaid 
expansions to pregnant women and infants (Hill, 1987). 

Embraced by the nation's Governors and lobbied for effectively in Congress, the proposal was 
signed into law m December 1986 as part of the Omnibus Budget Reconciliation Act of 1986 
(OBRA-86). Specifically, OBRA-86 gave states the option to expand Medicaid income 
eligibility thresholds for pregnant women and infants above Af DC levels to 100 percent of the 
federal poverty level. In subsequent years, Congress continued to pass legislation allowing 
and then requiring, states to further liberalize their Medicaid coverage of these priority 
populations, as summarized below. 

■ The Omnibus Budget Reconciliation Act of 1 987 (OBRA-87) further expanded 
states' flexibility by allowing them to raise Medicaid income thresholds for 
pregnant women and infants up to 185 percent of poverty. 

■ The Medicare Catastrophic Coverage Act of 1 988 (MCC A) mandated, for those 
states that had not already done so voluntarily, minimum coverage of pregnant 
women and infants at 100 percent of poverty. 

■ The Omnibus Budget Reconciliation Act of 1989 (OBRA-89) required states to 
cover, at a minimum, pregnant women and children up to age six at 133 percent 
of poverty. 



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In general, states responded aggressively to the optional authontv presented bv OBR a «a 
OBRA-87: by July 1989. the effective date of MCCVs mandate'. Z^ZslsZ^ ** 
already raised their eligibility thresholds to 100 percent of poverty or higher (Hill. 1990). 

For Florida, the optional authority granted by OBRA-86 presented policymakers with an ideal 
solut.on to their mdigent care crisis. The pressing and complementary needs for expanding 
Medicaid coverage of the uninsured, putting Trust Fund dollars to good use. and addressing the 
state s infant mortality problem were equally addressed by the policy of expandine Medicaid 
eligibility tor pregnant women and infants up to the federal poverty 'level As will be described 
below. Florida joined many states in quickly adopting eligibility expansions not only under 
OBRA-86. but in subsequent years as well. Just as important, however, this section will also 
describe how the state enacted a broad range of strategies to help ensure that the Medicaid 
expansions had their desired impact. Specifically, this section will discuss Florida's efforts to 
simplify and streamline the Medicaid eligibility determination process, implement outreach 
and public information campaigns, adopt policies to recruit greater numbers of obstetrical 
providers into the program, and provide technical assistance to local health departments to 
foster effective enrollment and billing practices. 

A. Expanding Medicaid Fligihility 

In October 1987, Florida became one of the first 15 states to take advantage of OBRA-86 
authority by expanding coverage of pregnant women and infants up to 100 percent of poverty. 
This expansion effectively doubled the income limit for these groups, as the medically needy 
income threshold had stood at just 47 percent of poverty. Nearly two years later, in July 1989. 
the state further expanded coverage of these populations up to 150 percent of poverty using 
OBRA-87 flexibility. Finally, in May 1992, Florida expanded coverage up to the maximum 
allowed by law- 185 percent of poverty (Hill, 1992). 



B. Simplifying the Medicaid Eligibility Prnre^ 

To complement the expansion of financial access to coverage, Florida also adopted several 
strategies to simplify the Medicaid eligibility determination process in October 1987. 
Specifically, the state implemented three new options also initially permitted by OBRA-86: 

■ Dropped Assets Restrictions. Florida eliminated the assets test from its 
application so that eligibility for pregnant women and infants could be based on 
a simple test of income. 

■ Continuous Eligibility. Florida also began granting continuous eligibility to 
pregnant women throughout their pregnancies and a 60-day postpartum period, 
regardless of changes in income. 



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■ Presumptive Eligibility. Florida was one of the first four states to adopt 
presumptive eligibility, a process by which state-selected providers were 
permitted to grant immediate, temporary eligibility to pregnant women based on 
a preliminary assessment of income so that they could receive Medicaid- 
financed prenatal care while their formal application for Medicaid was beine 
reviewed. 

Over a year earlier, however. Florida had implemented two additional strategies to simplify the 
process and facilitate access to coverage. These strategies are described below: 

■ Shortened Application Form. In July 1986. Florida reduced its Medicaid 
application from twelve pages to a single page. This form, a copy of which 
appears in Appendix A, was adapted and streamlined to gather essential income 
and family composition information and was used as an initial screen for not 
only Medicaid eligibility but also eligibility for all federal public assistance 
programs except Food Stamps. 

■ Outposting Eligibility Workers. Also in July 1986, Florida began outposting 
Division of Economic Services eligibility workers at health care provider sites, 
including hospitals. LHDs, and FQHCs. The strategy was intended to facilitate 
families' access to Medicaid coverage by eliminating the need for a separate trip 
to a public welfare office to apply for Medicaid. 

Florida made the most aggressive use of this strategy of any state in the nation 
(Hill, 1992). As illustrated in Table 1, by April 1987, the state had hired at least 
one Economic Services eligibility worker to work at each of 1 10 sites. One year 
later, nearly 500 eligibility workers were distributed across 226 provider sites. 
By April 1990, while the total number of dedicated outposted workers had 
slipped to just over 400, these workers were still distributed across nearly 230 
provider sites. 

Florida officials hoped that these strategies, combined would help translate eligibility 
expansions into real enrollment by making Medicaid coverage more accessible, simple, and 
continuous. 



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Tabie 1 

Number of Sites, by Type, with Outstationed Eligibility Workers 
and Nam ber of Worker, 1987-1990. 



Date 



April 87 



April -88 



November 88 



April "90 



Number of 
Sites 



226 



229 



* At least one worker per site 
Source: HRS/Medicaid, 1994 



Hospitals 



66 



n/a 



n/a 



95 



Type of Site 



LHDs 



19 



n/a 



n/a 



102 



FQHCs 



8 



n/a 



n/a 



Other 



n/a 



n/a 



16 



Number of 
Workers 



a a 



495 



316 



402 



C Promoting \he of Prenatal Care Through Qm aafifa 

While Florida has never implemented a comprehensive statewide outreach campaign to 
promote the importance of prenatal care, the state has engaged in a number of important 
outreach efforts and has periodically targeted selected communities for additional casefmding 
activities. These efforts are summarized briefly below. 

■ Toll-Free MCH Hotline, Following a directive from the federal Title V 
Program, Florida instituted a statewide toll-free MCH Hotline in 1987. Women 
who call the hotline can receive information about where to obtain prenatal care 
in their community, how and where to apply for Medicaid coverage, as well as 
general advice regarding healthy behaviors during pregnancy. Medicaid 
administrative matching dollars have supported the operation of the hotline 
since its inception. 

■ Mass Media Efforts. In collaboration with the Florida Association of 
Broadcasters, the state has periodically waged prenatal care promotion 
campaigns. These efforts, again supported with Medicaid administrative match, 
often used media materials developed by the State of New York featuring the 
character "Stella the Stork" to promote early and frequent use of prenatal care. 

■ Healthy Mothers/Healthy Babies Efforts. Beginning in 1 99 1 , state officials 
delegated much responsibility for perinatal outreach to the various not-for-profit 
Healthy Mothers/Healthy Babies Coalitions in existence in communities across 
Florida. These campaigns varied in their timing and intensity based on the 
initiative of community members and local officials. 



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■ Casefinding in Target Communities. Judging that certain communities were 
more disadvantaged than others, and anticipating that women in these 
communities might need extra help in understanding the importance of prenatal 
care and the availability of Medicaid coverage, Florida hired professional social 
workers to perform casefinding activities in target counties. 2 These social 
workers have engaged in a variety of activities to identify and recruit women 
into care, including door-to-door canvassing and networking with community 
agencies and providers likely to serve needy pregnant women. 

Once again, the various outreach efforts implemented in Florida were designed to bolster the 
Medicaid expansions by advertising the availability of enhanced Medicaid coverage and to 
promote the broader message of the importance of prenatal care. 



D. Improving Physician Participation in Medicaid 

Florida officials understood that the impact of their Medicaid expansions could be severely 
undermined if there was not an adequate supply of obstetrical providers from which newly- 
eligible pregnant women could obtain prenatal care. To address the state's long-standing 
problem of insufficient private provider participation, Florida implemented a number of 
strategies to make the Medicaid program more attractive to physicians. These efforts, which 
are summarized below, involved significant increases in provider fees, initiatives to minimize 
malpractice liability exposure, and efforts to create a more user-friendly administrative system. 

■ Raising Provider Fees. When Florida first expanded coverage for pregnant 
women, the state paid one of the lowest global obstetrical fees in the nation, 
reimbursing obstetricians just $315 for all care provided to a Medicaid-eligible 
mother, including both prenatal and delivery services. Recognizing that such a 
low fee was undermining the program's ability to attract larger numbers of 
physician participants, the state has systematically increased reimbursement 
rates and brought them to approximate parity with private payer rates. 

As illustrated in Table 2, the largest single increase occurred in 1988 when the 
global fee was raised more than 250 percent, to $800. That same year, the 
program established a new, separate global fee to reimburse OBs who treat 
women determined to be high-risk; this fee was set at $1 ,200, a rate nearly four 
times higher than the previous $315 fee. Another increase was made in 1989 
when the base global rate was raised to $1,000. Finally, in 1992, fees were 
raised once again by a significant amount. That year, the base global fee was 
increased to $1,500, while the global fee for high-risk women was increased to 
$2,000. 



2 



In 1986 and 1987, social work staff were placed in Gadsden, Columbia, Clay, Pinnellas, Manatee, Oseola, 
Martin, Palm Beach, Broward, and Dade Counties. In 1988 and 1989, social workers were placed in Leon and 
Putnam Counties. 



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Table! 
Medicaid Obstetrical Global Fees, 


1986-1992 


Year 


Global Fee 


Global-High Risk 


1986 


$315 


n/a 


1988 


S800 


$1,200 


1989 


$1,000 


$1,200 


1992 


$1,500 


$2,000 


Source: 


HRS/Medicaic 


L 1994 





Limiting Malpractice Liability. The State of Florida established the 
Neurological Injury Compensation Association in January 1989. Under the 
program, "no-fault" liability coverage for newborn birth-related injuries is 
extended to physicians who elect to pay $5,000 per year into a compensation 
fund. Participation is completely voluntary and carries with it no obligation to 
participate in Medicaid. To help support the fund, a general tax of $250 per 
year is levied on all physicians practicing in the state, as well as a $50 per 
delivery tax on all of Florida's private hospitals. 

Under the system, physicians are indemnified only in cases where very severe 
injuries occur. For example, liability coverage only exists for babies born over 
2,500 grams who sustain permanent and substantial mental and physical injuries 
during labor, delivery, or resuscitation. Awards granted under the compensation 
fund cannot exceed $100,000 plus expenses for medical care incurred over the 
injured child's lifetime. 

By 1992, the compensation fund maintained a balance of approximately $90 
million and had 700 participating physicians. Twenty-five claims had been 
made against the fund, 14 of which were judged to be compensable. The fund 
did not seem to significantly affect malpractice premiums; just two carriers in 
the state (out of approximately 15) had reduced by $5,000 their premiums for 
physicians participating in the fund to offset the cost of that participation. 

■ Creating New Initiatives in the Provider Relations Office. Beginning 
in 1 989, the Medicaid program placed new emphasis on the role of its 
Provider Relations Office and began several initiatives aimed at making 
Medicaid administrative systems more responsive to the needs of 
physicians. First, the office designed and distributed a new provider 
recruitment brochure. Unfortunately, while it was endorsed by the 
Florida Medical Association, the brochure was generally regarded as a 
failure. Next, the office expanded and increased publicity for its existing 
toll-free hotline through which physicians can receive personal 



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assistance in answering billing questions and/or resolving billing 
disputes. This efforts has been viewed as highly successful. .Another 
strategy employed by the office was to send designated staff to 
approximately 20 communities per year to recruit physicians and to 
provide hands-on technical assistance to providers regarding their 
treatment and billing practices. These two-day conferences, conducted 
in collaboration with the Medicaid fiscal agent, enjoyed wide 
participation by physicians and their business managers. 3 

The strategies described above were all designed to attract greater numbers of private 
obstetrical providers into the Medicaid program and broaden the base of providers from whom 
Medicaid recipients could choose to receive their prenatal care. A major objective of state 
policymakers was to create a system that more effectively blended public and private resources 
in serving low-income families. 



E. Providing Technical Assistance to Co unties to Facilitate Effective Implementation 

The single strategy that is most often credited by Florida officials as having the greatest impact 
on the state's ability to implement effective programs for Medicaid pregnant women was the 
creation and deployment of Technical Assistance and Coordination Teams (TACTs) between 
1988 and 1990. The TACT concept, established by the same law that originally expanded 
Medicaid eligibility to 100 percent of poverty, was designed to provide hands-on assistance to 
county and district staff with the implementation of their indigent care programs. Composed of 
central office staff from Health Services. Economic Services, Children's Medical Services. 
Medicaid, and Aging and Adult Services, the TACTs visited each district each year for a three- 
vear period. During their week-long site visits, the TACTs worked with district and local staff 
to assess their progress, diagnose their problems, recommend solutions, and identify innovative 
practices to better serve clients (TACT Report, 1989). At the conclusion of their visits. TACTs 
would prepare detailed site visit reports describing their findings and outlining their 
recommendations for operational improvements. TACT reports were distributed to all districts 
to further foster the sharing of information across the state. 

During their tenure, TACTs tended to focus the majority of their efforts on helping counties 
resolve issues in two main program areas: Medicaid eligibility and Medicaid billing. In the 
area of Medicaid eligibility, TACT members worked with local staff to identify appropriate 
sites for outstationed eligibility workers, smooth operational problems between the systems 
and staff involved with presumptive eligibility and formal Medicaid eligibility determination, 
and build stronger links between eligibility and health care provider staff. 



3 It is important to note that the Provider Relations Unit was formed to serve all physician groups participating 
in Medicaid and did not focus its efforts solely on obstetrical providers. 

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In the area of billing, TACT members worked closely with local public health units to ensure 
they were maximizing Medicaid revenues when serving Medicaid-eligible clients. The TACTs 
were greatly assisted in this effort by the Medicaid program's development of a Medicaid 
Reimbursement Guide for HRS County Public Health Units in 1989. The Guide provided 
simple, step-by-step instructions on enrolling as a Medicaid provider, determining Medicaid 
eligibility, understanding what services Medicaid will cover, preparing claims, and obtaining 
assistance with billing problems. Florida officials credit the Guide, coupled with hands-on 
assistance from the TACTs, with dramatically improving local public health units' ability to 
capture Medicaid revenues to support their operations. 4 



Despite this improvement, local public health units are still unable to bill Medicaid for a large portion of the 
services they provide. For example, unlike most states, Florida never expanded its Medicaid benefit package to 
cover non-medical psychosocial support services such as care coordination, nutritional counseling, social work 
services, and health education. As a result, LHDs have never had the ability to bill Medicaid for these 
traditional public health services and, instead, has financed these services with federal Title V dollars and state 
general revenue appropriations. 

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V. Key Findings and Implications for the Evaluation 

At a number of levels, the Medicaid expansions for pregnant women appear to have been a 
success in the State of Florida. By coupling income eligibility expansions with a broad set of 
innovative strategies to streamline the enrollment process, promote the importance and use of 
prenatal care, and recruit physicians into the program. Florida appears to have succeeded in 
providing more low-income women with insurance coverage for their maternity care. In 
addition, in the period following the Medicaid expansions, statewide rates of women who 
received late, no. or inadequate prenatal care declined. Most important, Florida officials can 
point to a promising improvement in the health of newborns since the Medicaid expansions 
were enacted. 

As will be described below, state program and public health vital records data illustrate a 
number of desirable trends with regard to Medicaid enrollment and expenditures, prenatal 
Medicaid revenues for LFIDs, prenatal care access and utilization, and infant health. Further. 
Florida officials from a broad range of agencies and programs indicated during interviews with 
the RAND/HSR research team that these positive outcomes can be attributed to the state's 
concerted efforts not only to expand financial access to care, but also to facilitate the 
implementation of accessible and effective programs at the local level. Many of the lessons 
learned by Florida officials in building these systems should prove valuable to other states 
working to improve systems of care for pregnant women. 



A. Improvements in Enrollment. Fxpenditures. Reven ues, and Outcomes 

By observing trend data from a variety of secondary sources, it is possible to describe several 
preliminary effects of the Medicaid expansions for pregnant women. Specifically, these data 
illustrate dramatic increases in the number of pregnant women enrolled in Medicaid, large 
increases in Medicaid expenditures related to maternity care, and a steady increase in Medicaid 
revenues for prenatal care provided in local health departments. Over the same period that 
these trends occurred, vital records data show a steady improvement in several of the key 
maternal and child health indicators of concern to policymakers. 



It should be noted, however, that several of the trends presented below are drawn from the 
HCFA 2082 Database. This source, while valuable in its ability to provide general descriptive 
data on state Medicaid program recipients and expenditures, is limited in that it aggregates 
information into broad eligibility and covered service categories. Therefore, the 2082 do not 
always permit as precise measurement as researchers would prefer. In the following analysis, 
for example, data are presented for "Pregnant Women and Caretaker Relatives" made eligible 
through the various federal statutory changes of the late 1980s. These data therefore do not 
report on the entire universe of Medicaid pregnant women in Florida, as they exclude those 
who were eligible under other categories such as "AFDC Adult" or "Medically Needy Adult," 
nor do they permit pregnant women who are AFDC- or Medically Needy-eligible to be 
disaggregated from their broader reporting categories. Similarly, the "Pregnant Women and 
Caretaker Relatives" category includes certain recipients who were not pregnant, although 

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according to Florida officials, "caretaker relatives" make up a tiny proportion of the recipients 
reported on this line of the 2082. Recognizing these limitations, the 2082 still permits analysts 
to draw at least general conclusions regarding how the Medicaid expansions for pregnant 
women affected program enrollment and expenditures in Florida. These trends are described in 
detail below. 



1 . Increases in Medicaid Enrollment of Pregnant Women 

An analysis of the HCFA 2082 data from the State of Florida illustrates how the Medicaid 
expansions have led to dramatic increases in the number of pregnant women enrolled in the 
program. During federal fiscal year (FFY) 1988, when the state first expanded eligibility for 
pregnant women to 100 percent of poverty, over 30,000 women eligible under the new 
authority received Medicaid-financed services. The following year, the number of such 
pregnant women grew to over 48,000, an increase of 58 percent. During FFY 1990, the year in 
which the effects of the state's expansion to 150 percent of poverty are reflected, nearly 76,000 
pregnant women eligible under the expansions received Medicaid services. In 1991, this figure 
grew by another 24 percent to 94,000. 

In every year following the expansions, annual growth in pregnant women recipients eligible 
under the expansions outstripped growth in Medicaid recipients overall. Still, such Medicaid 
pregnant women continue to represent a small proportion of the overall program population; 
between FFYs 1988 and 1991, pregnant women grew as a percentage of total Medicaid 
recipients from 4.0 to 7.5 percent. 



Table 3 

Medicaid Pregnant Women Eligible Under the Expansions 

a» a Percent of Total Medicaid Recipients 

Federal Focal Yean 1987-1991 



Year 



Medicaid Pregnant 

Women Under the 

Expansions 



1987 



1988 



1989 



1990 



1991 



14,000< 



30,400 



48,200 



75,900 



94,000 



Percent 
Growth 



117% 



58% 



58% 



24% 



Total Medicaid 
Recipients 



639,900 



768,200 



875,600 



1,038,400 



1,248,900 



Percent 
Growth 



20% 



14% 



19% 



20% 



Ratio of Pregnant 
Women/Total 



1.5% 



4.0% 



5.5% 



7.3% 



7.5% 



1987. 



HRS Medicaid officials estimate that approximately 14,000 pregnant women were on Medicaid in 



Sources: HCFA, 2082 Data, 1987-1991; HRS Medicaid, 1987. 



20 



Health Systems Research, Inc. 



2. Increases in Medicaid Expenditures for Pregnant Women 

Data from the HCFA 2082 also illustrate that Medicaid expenditures on behalf of pregnant 
women made eligible under the expansions also rose significantly as the program expanded its 
coverage. As shown in Table 4, expenditures for such pregnant women in FFY 1988 totaled 
just under $24 million. That total rose by 179 percent the next year to nearly $67 million 
While the rate of growth slowed somewhat over the next two years, expenditures for pregnant 
women eligible under the expansions reached over $157 million by FFY 1991. As was the 
case with recipient data, the annual rate of growth in program expenditures for these pregnant 
women far exceeded overall growth in Medicaid expenditure during the same period. Yet this 
population accounts for an even smaller proportion of total expenditures than it does of total 
recipients. Between FFYs 1988 and 1991, expenditures for pregnant women eligible under the 
expansions as a proportion of total Medicaid expenditures rose from 1.6 to 5.3 percent. 



Year 



1987 



1988 



1989 



1990 



1991 



Table 4 

Medicaid Expenditures for Pregnant Women Eligible Under the Expansions 

as a Percentage of Tola! Medicaid Expenditures, 1987-1991 (in thousands) 



Medicaid 

Expenditures for 
Expansion Group 
Pregnant Women 



$11,400' 



$23,900 



$66,700 



$119,100 



$157,300 



Percent 
Growth 



110% 



179% 



79% 



32% 



Total Medicaid 
Expend tames 



$1,178,000 



$1,493,300 



$1,912,000 



$2,360,700 



$2,944,400 



Percent 
Growth 



27% 



28% 



23% 



25% 



Ratio of Pregnant 
Women/Total 
Expenditures 



1.0% 



1 .6% 



3.5% 



5.0% 



5.3% 



* Represents expenditures for Medically Needy Adults, not all of which are for pregnant women 
Source: HCFA, 2082 Data, 1987-1991 



21 



Health Systems Research, Inc. 



3. Increases in Medicaid-Financed Deliveries 

Analysis of HC FA 2082 data reveals that slightly less than one-half of all pregnant women 
eligible under the Medicaid expansions use inpatient hospital services during any given year 
For this population, we assume that inpatient hospital services represent deliveries Therefore 
inpatient hospital users and expenditures for this eligibility group can serve as a proxy measure 
of Medicaid-financed deliveries. To the extent that pregnant women may be hospitalized for 
other reasons, these results will represent an overestimate of expenditures for deliveries. 

Table 5 illustrates the growth between 1988 and 1991 in the number of Medicaid pregnant 
women made eligible under the expansions who used inpatient hospital services and the 
expenditures they accounted for. In 1988, there were 9,700 of these pregnant women who used 
inpatient hospital care, for whom Medicaid paid just under $15 million. By 1991, there were 
nearly 43,000 of such pregnant women using inpatient services at a total cost of over $82 
million. Once again, these figures provide a proxy measure for growth in the number of 
Medicaid-financed deliveries during and after the Medicaid expansions. 





Table 5 

Growth in Pregnant Women Eligible Under the Expansions 

Who Used Inpatient Hospital Services, 

and Related Expenditures, 1987-1991 


Year 


Pregnant Women 
Under the Expansions 
Using Inpatient 
Hospital Services ■ 


Percent 
Growth 


Expenditures for 

Expansion Group 

Pregnant Women on 

Inpatient Hospital 
Services 


Percent Growth 


1987 


5,100* 




$9,300,000* 




1988 


9,700 


90% 


$14,700,000 


58% 


1989 


23,600 


143% 


$41,700,000 


184% 


1990 


36,300 


54% 


$71,100,000 


71% 


1991 

* n 


42,900 


18% 


$82,800,000 


16% 



women. 
Source: HCFA 2082 Data, 1 987- 1 99 1 



22 



Health Systems Research, Inc. 



4. Growth in Medicaid Revenues to Local Health Departments 

As described in Section IV, the Medicaid program developed a guide to Medicaid billing for 
local public health units in the late 1980s. With the help of the Technical Assistance and 
Coordination Teams, local health departments made a high priority of billing for Medicaid 
reimbursement and maximizing resources for the delivery of prenatal care services An 
analysis of budget and revenue data from HRS indicates that LHDs were indeed successful in 
implementing this objective. 

As described in Table 6, revenues from the delivery of prenatal care to Medicaid-eligible 
women grew from $7 million in state fiscal year (SFY) 1988 to almost $14 million in SFY 
1991. Not surprisingly, Medicaid's relative role as a payer of LHD-sponsored prenatal care 
also grew over the same period. The proportion of total LHD revenues made up by Medicaid 
rose from essentially zero in SFY 1986 to nearly 30 percent in SFY 1991. 



: :; ' : ; '■ ' 


Table 6 

LHD Prenatal Care Reven oes from Medicaid, as Percent of Total 

Prenatal Revenues, 1987.1992 (is millions) 


Year 


Medicaid Prenatal 
Reven oes 


Total Prenatal 
Revenues 


Ratio of Medicaid/Total 


1987-88 


$n/a* 


$27.5 


n/a% 


1988-89 


$7.0 


$34.4 


20.3% 


1989-90 


$11.0 


$39.3 


28.0% 


1990-91 


$13.0 


$46.1 


28.2% 


1991-92 

* iil:i_ Lin; c i / 


$13.7 


$46.5 


29.5% 



the accurate reporting of this indicator. 
Source: HRS, 1995 



23 



Health Systems Research, Inc. 



5. Improvements in Key Maternal and Child Health Indicators 

Over the period during which Florida expanded its Medicaid program for pregnant women, the 
state experienced overall improvement in several key indicators of infant health and maternal 
utilization of prenatal care. As displayed in Table 7: 

■ The rate of infant mortality fell from 11.0 deaths per 1 ,000 live births in 1 986 to 
8.8 deaths per 1,000 live births in 1992. Over this period, Florida's national 
ranking on this indicator also improved from 35th to 29th among the states. 

■ The rate of babies bom at low birthweight, after rising slightly between 1986 
and 1988, fell to an all-time low for the state of 7.4 percent in 1992. Once 
again, improvement over the period 1986 to 1992 moved Florida up in national 
rankings on this indicator from 40th to 34th. 

■ The percentage of women who received late or no prenatal care during their 
pregnancy fell from 8.6 percent in 1986 to 4.6 percent in 1992. 

■ The proportion of women who received adequate prenatal care, as measured by 
the Kessner index, rose from 62.0 percent in 1986 to 71.6 percent in 1992. 

While these improvements cannot, in this analysis, be directly attributed to the Medicaid 
expansions, they provide strong support for the conclusions that women in Florida are 
receiving earlier and greater amounts of prenatal care and that birth outcomes are improving. 



Table 7 
Selected Maternal and Child Health Indicators, 1985-1992 


Indicator 


J986 


1987 


198S 


1989 


1990 


1991 


1992 


Infant Mortality 
(Deaths/1000 Births) 


11.0 


10.6 


10.6 


9.8 


9.6 


9.0 


8.8 


Low Birthweight 
(Percent) 


7.6 


7.7 


7.7 


7.4 


7.4 


7.4 


7.4 


Late/No Prenatal Care 
(Percent) 


8.6 


8.2 


8.2 


8.1 


7.1 


5.9 


4.6 


Adequate Prenatal Care 
(Percent) 


62.0 


62.8 


62.8 


64.5 


66.6 


69 


71.6 



Source: NCHS, 1986-1992, 1990, 1991, 1992, 1994 



24 



Health Systems Research, Inc. 



B. Qualitative Impressions of Program Im pact and Lessons Lamed 

During extensive interviews, officials representing a broad cross-section of Florida programs 
summarized their impressions of the effects of the Medicaid expansions for pregnant women 
and pointed to a number of lessons they learned while working to implement effective 
programs at the local level. The key points raised during these discussions are summarized 
below. 

■ Florida officials are well aware of the dramatic increases that have occurred in 
Medicaid enrollment of pregnant women since the program expanded its income 
limits. They note that never before in the program's history has there been such 
a significant and rapid response to a change in eligibility policy. In fact, Florida 
Medicaid had had a long tradition of being underused by low-income 
individuals and families prior to 1986. For example, the Indigent Health Care 
Study conducted in 1985 found that, in addition to the roughly 300,000 persons 
who would be made eligible for Medicaid through expansions of categorical and 
medically needy coverage in '85/'86, there were also another 300,000 persons 
who were already eligible for Medicaid by virtue of meeting either AFDC or 
SSI criteria but were not enrolled in the program (Lou Harris and Associates, 

1 985). Data from the HCFA 2082 demonstrate that large increases in 
enrollment directly correspond to expansions of income eligibility thresholds for 
pregnant women. 

■ In part, this enrollment trend supports the notion that a great need and demand 
for insurance coverage existed among low-income pregnant women during the 
late 1980s. However, in translating this need into access to care, Florida 
officials point to their efforts to simplify and streamline the Medicaid eligibility 
process as the key influencing factors. In particular, the state's aggressive 
outstationing of eligibility workers at the sites where women sought care is the 
policy that is believed to have had the greatest positive impact on the process. 
Bolstering this policy, the state's use of Technical Assistance and Coordination 
Teams (TACTs) is also cited as the key strategy that helped local agencies and 
providers implement simplified eligibility systems at the local level. 

■ Florida officials are also well pleased with the success that LHDs have had in 
capturing Medicaid reimbursement in support of their delivery of prenatal care. 
Over a short period, the public health system evolved from one that did virtually 
no billing of Medicaid to one that secured more than 30 percent of its prenatal 
care revenue from the program. A key factor in this change was the 
development by Medicaid of the user- friendly Medicaid Reimbursement Guide 
for HRS County Public Health Units. And, once again, the use of TACTs to 
provide hands-on technical assistance in billing practices helped to ensure 
effective local-level implementation. 



25 

Health Systems Research, Inc. 



The influx of Medicaid revenues into the public health system has allowed 
LHDs to expand their capacity to provide prenatal and related care. In 
particular, Florida officials believe that, as Medicaid revenues have increasingly 
supported the delivery of medical prenatal care, public health dollars have been 
redirected toward financing the delivery of non-medical support services such as 
nutritional counseling, health education, and home visiting, as well as medical 
prenatal services for populations not covered by Medicaid, such as migrants. 

Public health officials did note, however, that certain inefficiencies in the 
system have persisted. In particular, the fact that MCH and Medicaid officials 
have never successfully negotiated arrangements to permit Medicaid payments 
for local public health units' provision of psychosocial support services for 
high-risk pregnant women has meant that the state has continued to finance the 
delivery of such care with state funds. 

It is the belief of Florida officials that the Medicaid expansions were 
implemented in a relatively consistent manner across the state and, therefore, 
the potential for examining intrastate variations in implementation and impact 
under this evaluation is low. While the county public health system in Florida 
could be characterized as variable in its capacity to serve low-income families in 
the early 1980s (Clarke, 1986), efforts like the IPO Project and the provision of 
local-level guidance through the TACTs served to "level the playing field" and 
lent an intrastate consistency to the implementation of the Medicaid expansions. 

Florida MCH officials believe that the delivery of prenatal care remained 
largely the domain of public health until 1992, when Medicaid increased its 
obstetrical fees to $1,500 for normal deliveries and $2,000 for high-risk 
deliveries. And while the program had raised OB fees in prior years, Florida 
officials do not believe that significant changes in physician enrollment rates 
occurred until after the 1992 changes. Therefore, while data will show increases 
in Medicaid-financed prenatal care throughout the period of expansion, they 
will not show large increases in care received from the private sector until 
relatively late in the expansion process. 

Finally, Florida officials believe that two related factors were probably most 
important to the state's overall success in implementing the Medicaid 
expansions. First, effective interagency collaboration, under the strong 
leadership of the HRS Deputy Secretary for Health and Deputy Assistant 
Secretaries for Medicaid and Economic Services, enabled a coordinated process 
of development of policies and programs within state government. Second, the 
creation of the Public Medical Assistance Trust Fund and, with it, the tax on 
hospital revenues, resulted from a carefully orchestrated process of consensus- 
building between public and private partners and safeguarded an environment in 



26 

Health Systems Research, Inc. 



which programs for the medically indigent could be developed and financed in a 
fair, equitable, and collaborative manner. 

Overall. Florida stands-out as a state that has aggressively addressed the problems of infant 
mortality and medical indigency by expanding Medicaid coverage of pregnant women in a 
highly effective manner. This case study provides detailed information regarding how the state 
implemented the Medicaid expansions, information that should be helpful in interpreting the 
results of the evaluation's quantitative analyses. It is also hoped that this report will provide 
other states with helpful descriptive information on innovative strategies for implementing 
improved maternal and child health programs. 



27 

Health Systems Research, Inc. 



Works Cited 



Brown. Lawrence D. ••Commissions. Clubs, and Consensus- Florin, o 

Care Reform.- Health Affairs. Summer 1993. ^^ F1 ° nda ^organizes For Health 

Children's Defense Fund. The Health of America s Children- LA„ , ,„ 

Data Book. Washington. DC: 1 989. Maternal and Child Health 

Clarke. Gary. Florida s Health Care Access Acf Radiml <r,„„«. <~ 

Washington, DC: The Intergovernmental He^h £££& ^IST*" ^ 

sss^^r 1 Rehabi,itative Semces - Heaith *•» ™«- 

Florida Department of Health and Rehabilitative Services. Medicaid Office. Tallahassee, FL: 

Florida Department of Health and Rehabilitative Services. TACT Report. Tallahassee, FL: 

Florida Department of Health and Rehabilitative Services. Health Program Office 
Tallahassee, FL: Due January 1995. »wum«. 

Health Care Financing Administration. State Medicaid Program Characteristics Chart 
Baltimore, MD: Health Care Financing Administration. 1984. 

Health Care Financing Administration. "Analysis of State Medicaid Program Statistics, 1984 - 
Health Care Financing Program Statistics. Baltimore, MD: Health Care Financing 
Administration. August 1985. 

Health Care Financing Administration. HCFA 2082 Data Baltimore, MD: Health Care 
Financing Adininistration. 1987. 1988. 1989. 1990. 1991. 

Hill, Ian. Broadening Medicaid Coverage of Pregnant Women and Children: State Policy 
Responses. Washington, DC: The National Governors' Association. February 1987. 

Hill, Ian. "Improving State Medicaid Programs for Pregnant Women and Children." Health 
Care Financing Review. Baltimore, MD: Health Care Financing Administration. 1990 
Annual Supplement 

Hill, Ian. The Medicaid Expansions for Pregnant Women and Children: A State Program 

Characteristics Information Base. Washington, DC: Health Systems Research, Inc. February 
1992. 



Health Systems Research, Inc. 



Hill. Ion. Long. Stephen, and Marquis. Susan, impact of Medicaid Fha h r c 
Innovative Programs for Maternal Health Care Uethodolovv Zi*. J ?' Expan " ^ ^ 
Washington. DC: The RAND Corporation under HC 'a cZ r^T ***""**" 
*)113 9-01. August 24. 1992. cooperative Agreement No. 18-C- 

Insmutec^ted^ne. ftwrtf£»toH,k Washington. DC: National Academy 

Lou Harris and Associates. Medicaid and Indigent Health Care Sunn w r c 

Study. New York, NY. March 1985. ' W Cost Estlma "on 

National Association of Community Health Centers. Access to Commit*, u , t/ ~ 
DmBootim Washington, DC : 1991. ^^s to Community Health Care. A 

National Center for Health Statistics, "'Advanced Report of Final Mortality Statistics " 1990 
Month* Vital Statistics Report. Vol. 41, No. 7 Supplement, HyartsviUe, MD. S^' 

National Center for Health Statistics, "Advanced Report of Final Mortality Statistics "1991 
Monthly Vital Statistics Report. Vol. 42. No. 2 Supplement, HyattsvUle, MD. Public HeT m 

National Center for Health Statistics, "Advanced Report of Final Mortality Statistics " 199? 
Monthly Vital Statistics Report, Vol. 43, No. 6 Supplement, HyattsvUle, MD, Public Health" 

National Center for Health Statistics, Vital Statistics of the United States, 1990 Vol 1 Natalirv 
Washington Public Health Service, 1994. ' ' y ' 

National Center for Health Statistics, Vital Statistics of the United States, 1991 Vol 1 Natality 
To be published 7 " 

National Center for Health Statistics, Unpublished data, 1986-1992. 

Social Security Administration. Program Data for the Aid to Families with Dependent 
Children Program. 1984. 

U.S. Bureau of the Census. March 1986-89 Current Population Suney. Washington, DC. 

Ventura, S.J., Martin, J.A., Taffle, S.M., et al., "Advanced Report of Final Natality Statistics," 
1992, Monthly Vital Statistics Report, Vol. 43, #5 Supplement, Hyattsville, MD, National 
Center for Health Statistics, 1994. 



Htalth Systems Research, Inc. 



APPENDIX A: 

Florida's Shortened Medicaid Application Form 



F l— t-Uck.nrnaU.Ooc "34*1 MiPM 



Health Systems Research, Inc. 



REFERRAL 
SOURCE 



RART 1 - HOUSEHOLD INFORMATION 



NAME 
FIRST 



MIOOLE 



IASI 



STATE OF FLORIDA 

SS^STESlTi* MEALTH AND REHABILITATIVE SERVICES 
APPLICATION FOR PUBLIC ASSISTANCE 



His 



SOCIAl SECURITY 
NUMBER 



IJVING 
ADORE SS 



STREET 



OTY 



DATE 
OF BIRTH 



PHONE AflEACOK 

NUMBER ( ) 



SHELTER 
SITUATION 



RELATIONSHIP 
TO YOU 



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TOTAL ASSETS 



RART 4 - INTERVIEW INFORMATION 



I am applying loi jbbibl..i« i! I ..(hleibljml lh.,1 I «,,« 
lidve lt> yiue line uiIuiiiuiioii itn liws loim II ukJU Ik. 
a Clinic il I he oi liKie inloiiiialion auool my olKjiUl.ly 
loi abbiblan, e 

I ayiue kj lull! in papers lh.,1 ale required lu n»,» 
Hidl I dill eligible e«Lepl loi |,apeib I canno! .jel 
llHOnyll no IjuII ol my own II I Cdllllol Jol papcib 
I ayiee to yiv/e Hie names ol any pursuits m uW. os 
llidl may be contacted loi Hie reqmieu .iiiu,,„ai„„, 

I ayiee Hi.. I Hie Depat lutein ..I Health an. I 
Hellauililalivc Semites Hie Division ,.l l',.i,i. 
Abbiblaik.e haul. .111,1 autlioii/eil Fmltu.ll Anem « . 
may venly Hie iiiIoiiiuIhhi I give on Hub lurm am ,,i 
my inlervrew I agree lli.il lliey may . oniat I ,.,, 

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C-l 



APPENDIX C. EVALUATION OF A MEDICAID ELIGIBILITY EXPANSION IN FLORIDA: 

DEVELOPING THE DATABASE 



Ellen R. Harrison 

Stephen H. Long 

M. Susan Marquis 



INTRODUCTION 

This report documents the construction of the analytic database 
used in the study of the 1989 Medicaid eligibility expansion for 
pregnant women in Florida. The creation of this database was a key 
challenge in the research. The resulting procedures may serve as a 
model for other evaluations of the Medicaid expansions. 

The Medicaid eligibility expansions for pregnant women and children 
were the most important policy changes in the program in the 1980s. Yet 
there are only a limited number of studies of the effect of these 
expansions and it is not clear from these studies whether the expansions 
led to an improvement in prenatal care and birth outcomes. 1 Moreover, 
to understand the full effects of the interventions it is also essential 
to understand how the Medicaid program changes affected other government 
programs that deliver prenatal care and how the expansions affected 
private payers. The effects on prenatal care access and birth outcomes 
are likely to be quite different if Medicaid financed care substitutes 
for care previously financed and provided under other programs, such as 
Title V or private insurance, rather than providing new coverage for 
those who previously lacked insurance or access to other public 
programs. None of the previous studies, however, addresses these 
substitutions . 

The objective of our study was to investigate these interactions 
between the Medicaid program and other sources of financing and 
providing maternal health care, and, with this perspective, to study 
whether pregnant women newly entitled to Medicaid coverage received more 
or earlier prenatal care, and whether their maternal and birth outcomes 
were improved. We studied the experience in Florida. Florida is a good 



1 Alpha Center, The Medicaid Expansions For Pregnant Women and 
Children. Washington, DC: Alpha Center; 1995. 



C-2 



site for this study for a number of reasons. It ranks fourth among the 
states in total population, and there are about 200,000 births each 
year. Florida significantly expanded Medicaid eligibility for pregnant 
women and also aggressively implemented other strategies to ensure that 
women who were made eligible by the expansions gained coverage under the 
program. Florida relies heavily on county public health department 
clinics to provide prenatal care to its low-income women, and hence is a 
good place to study interactions between the Medicaid financing changes 
and the publicly financed direct-delivery system. 

To conduct our analysis, we constructed a linked person-level 
database for the years 1988 through 1991 from vital statistics records, 
hospital discharge abstracts, public health system encounter data, 
Medicaid eligibility files, American Hospital Association annual survey 
data, and data from the 1990 Census. This report first briefly 
describes the content of each database, and then details our file 
linkage procedures and results. 

THE DATA 

Vital Statistics Data (VS) 

Source: Florida Department of Health and Rehabilitative Services 
Years: 1988-1991 

The Vital Statistics data (VS) contain information obtained from 
birth certificates, fetal death certificates, and death certificates 
from 1988 through 1991. They provide a detailed record of every birth 
and fetal death in the state of Florida for those years and define our 
study universe. Table CI presents the total number of birth 
certificates and fetal death records in each of the study years. To 
determine the actual number of women who delivered in Florida, we 
subtracted the 1.2 percent of certificates that correspond to additional 
certificates for the same delivery (multiple births), and also excluded 
the births that took place outside of Florida. For example in 1991, the 
195,756 certificates correspond to 193,393 mothers. After subtracting 
the out-of-state deliveries, we are left with 193,292 deliveries in the 
state of Florida. 



C-3 



Table CI. Live Births and Fetal Deaths from Vital Statistics 

Data, 1988-1991 



Live Births Fetal Deaths Total Certificates 



1388 185,034 1,772 186,806 

1989 193,893 1,833 195,726 

1990 200,334 1,847 202,181 

1991 194,043 1,713 195,756 



The records include information about the pregnancy such as the 
initiation and frequency of prenatal care; measures of birth outcomes 
such as birthweight and complications of delivery; and demographic 
characteristics of the mother and baby. Table C2 presents the key 
variables for analysis and for linking the vital statistics data with 
other databases. Because the mother's Social Security number is unique, 
universally used, and was included on over 95% of the VS records, it is 
the primary linkage variable. The mother's date of birth, name, and 
zipcode as well as the hospital identification number were also used to 
link to other files. 



Table C2. Key Patient-Level Variables for Analysis 
and Matching from Vital Statistics Files 



Mother's Characteristics 

• Name 

• Social Security number 

• Date of birth 

• Zipcode of residence 

• Race 

• Educational attainment 

• Marital status 

Baby's Characteristics 

• Name 

• Birthweight 

• Gestational age 

• Sex 

• Congenital anomalies 

Pregnancy /Delivery Characteristics 

• Mother smoked while pregnant 

• Mother consumed alcohol while pregnant 

• Number of previous births 

• Singleton/multiple birth 

• Initiation of prenatal care 

• Number of prenatal care visits 

• Labor complications 

• Delivery complications 



C-4 



The infant death records enable us to identify those infants who 
did not survive the first year of life. An infant death file for each 
year includes babies born during the year who died within the following 
twelve months. For 1988 and 1989 we were provided with a matched file 
that had already linked the death certificate information with the birth 
certificates. For 1990 and 1991 we created the linked file which 
combined information from the infant death file and the birth 
certificate file by matching death certificate numbers, when available, 
or by matching mother's and baby's name and baby's date of birth. We 
were able to match 97.5 percent of the 1990 infant mortality records and 
95.3 percent of the 1991 records. Table C3 presents the number of 
infant deaths and the infant mortality rate by year. 

Table C3. VS Infant Deaths, 1988-1991 



Infant Deaths % of Live Births 

1988 1,892 1.02% 

1989 1,871 0.97% 

1990 1,883 0.94% 
1991 a 1,441 0.74% 

a We did not have access to 1992 deaths 
so the 1991 infant deaths represent just 
those infants who died in 1991. 

Hospital Discharge Data (HDD) 

Source: Florida Agency for Health Care Administration 
Years: 1988-1991 

The hospital discharge data contain hospital discharge records from 
all non-military acute care hospitals in Florida. We matched records of 
the mother's delivery hospitalization in this file to records from the 
VS file to obtain a number of key variables that were not available 
from other sources. Most important to our analysis was the insurance 
status variable which was defined as the principal payer for the 
hospitalization and had the following values: 



C-5 



• Medicaid 

• Medicare 

• Private 

• Other 

Because women of child-bearing age do not generally qualify for 
Medicare, we combined "Medicare" with "Other" which included Champus, 
Veteran's Administration, other government third-party payers except 
Medicaid, charity, and uninsured. We also collected primary and 
secondary diagnostic codes, procedure codes, and the total charges for 
the delivery. The only person-level identifiers available to us were 
sex and date of birth. 

We obtained all discharge records that had a maternity-related 
principal or secondary diagnosis. Table C4 presents the number of 
discharge records on the resulting HDD file. 

Table C4. HDD Maternity Related Discharge Records, 1988-1991 

1988 1989 1990 1991 
Pregnancy related 24,364 24,764 23,386 21,442 
Delivery related 185,493 193,751 199,145 191,482 

Public Health System Encounter Data (PH) 

Source: Florida Department of Health and Rehabilitative Services 
Years: 1987-1991 

The Public Health System Encounter Data (PH) includes information 
about each public health system client and his/her visits to public 
health department clinics from 1987 through 1991. We included the 1987 
data to capture all of the prenatal care visits for births occurring in 
the first part of 1988. We received over 13 million records for the 
five years of data, so our first task was to select prenatal care 
records--visits in the Improved Pregnancy Outcome program and maternity- 
related Family Planning visits. We identified roughly 4 million 
prenatal care records. We linked all of the prenatal care visits for a 
woman into a single episode of prenatal care. For each episode, we 



C-6 



constructed measures of the number of PH visits and the trimester in 
which prenatal care in the public health system was initiated. 

Individuals are identified in the PH system using Social Security 
number, though 6 percent of the cases did not have valid values. 
Because we matched the PH data to the VS file, we kept only those 
episodes with valid Social Security numbers. Table C5 presents the 
number of prenatal care episodes and total number of encounters per 
year, where year represents the ending date of the prenatal care 
episode. The end date was determined by either the presence of a 
postpartum visit or a lapse of more than 90 days between visits. In 
both cases, the end date was set to the previous visit. 



Table C5. PH Prenatal Care Episodes and 
Total Visits, 1987-1991 



Year 


# Episodes 


Total # Visits 


1987 


35,243 


109,418 


1988 


43,115 


185,495 


1989 


48,817 


263,995 


1990 


62,646 


331,932 


1991 a 


83,299 


497,076 



a The number of 1991 episodes and visits 
are is artificially high because they 
include some prenatal care episodes for 
births occurring in 1992. 

Medicaid Eligibility Data (ME) 

Source: Florida Agency for Health Care Administration 
Years: 1988-1991 

The Medicaid Eligibility (ME) file we received from the Agency for 
Health Care Administration was extracted to provide us with a complete 
account of periods of eligibility for women of childbearing age (12 
through 55) who were enrolled in Medicaid at some time during 1988 
through 1991. It was important to match this file to our other data 
sources to verify the insurance status of the mother from the HDD file, 
to determine the reason for eligibility, and to examine the timing of 
the eligibility relative to the pregnancy. After selecting those 
records with valid Social Security numbers, in order to match to the 



C-7 



other databases, and those with eligibility periods that included any 
portion of our study years, we had roughly 1.3 million records for the 
study period. Table C6 presents the total number of eligibility records 
for each of the years. 



Table C6. Medicaid Eligibility 
Records, 1988-1991 



Year # Eligibility Records 

1988 240,905 

1989 297,347 

1990 364,960 

1991 387,817 



The ME files contain name, Social Security number, Medicaid 
identification number, the periods of Medicaid eligibility, and the 
basis of Medicaid entitlement for each eligibility period. We 
categorized the basis of entitlement into the following groups: 



Aid to Families with Dependent Children (AFDC) 

Medically needy 

Expansion group below 100% of poverty 

Expansion group between 100 and 150% of poverty 

Other 



American Hospital Association Annual Survey of Hospitals (AHA) 

Source: American Hospital Association 
Year: 1991 

The 1991 American Hospital Association Annual Survey of Hospitals 
contains hospital characteristics for all participating hospitals in the 
United States, including 306 Florida hospitals. We supplemented the 
file with information from the 1988 AHA Guide for nine hospitals on our 
files that either closed or merged with other hospitals prior to 1991. 



C-8 



Our primary use of these data was to measure the ownership of each 
hospital in which each delivery occurred. The variable has the 
following categories: 

• Government, nonfederal 

• Nongovernment, non-profit 

• Nongovernment, proprietary 

• Federal 

We also used these data to measure delivery specific 
characteristics of each hospital such as number of births, number of 
newborn days, and presence of a neonatal intensive care unit, as well as 
general information concerning the type of hospital, number of beds, 
number of Medicaid admissions, teaching intensity, and total expenses. 

Census of Population and Housing Summary Data (CEN) 

Source: Bureau of the Census 
Year: 1990 

The Census Bureau produces a summary tape (Summary Tape File 3B) 
for the Census of Population and Housing that provides summary 
information aggregated to the zipcode level based on a 100% sample of 
all persons and housing units in the United States. We created an 
extract of the 826 Florida zipcodes that existed in 1990. Because we 
did not have a measure of income for the women in the study, we used 
incomes in the residence area as a proxy measure. The CEN file was used 
to calculate the percentage of zipcode residents falling into different 
income categories expressed as a percentage of the federal poverty 
level. By merging these data to the VS file, we constructed a proxy 
measure of income for each woman giving birth in a year based on the 
income distribution in the zipcode of residence. 



C-9 



MATCHING PROCEDURES 

Linking Hospital Discharge Data to the Vital Statistics 

Matching Algorithm 

The primary challenge in the linkage process was to match the vital 
statistics record of a birth with the mother's hospital discharge record 
in the absence of a unique identifier on the hospital discharge data. 
Our algorithm matched by hospital first, and then within hospital, by 
mother's date of birth, baby's date of birth, and mother's zipcode of 
residence. 

Both files had a hospital identifier, but because the two sources 
used different coding schemes, we used county and hospital name in our 
matching algorithm. After modifying the two lists to have standard 
abbreviations and punctuations, we matched by county and the first eight 
letters of the hospital name. This task was complicated by hospitals 
that changed names, merged with other hospitals, or closed during the 
study years. To aid in our matching of hospitals with similar names, 
we made separate calculations from the two files of the number of births 
occurring at each hospital and then compared the totals from the 
potential matches. 

For each of the four study years, roughly 94 percent of the births 
on the VS file occurred at hospitals that were candidates to match to 
the HDD file. Over 40 percent of the non-candidate births took place 
at military hospitals, while another 20 percent were performed at 
maternity centers. Neither type of facility is included on the HDD 
database. Table C7 presents the distribution of location of births by 
year. The top row represents the percentage of cases that were eligible 
for the next step of the matching algorithm. 



C-10 



Table C7. Distribution of Location of VS Births and Fetal 

Deaths, By Year 



Location 


1988 


1989 


1990 


1991 


HDD hospital 


94.4 


94.6 


94.1 


94.7 


Military hospital 


2.5 


2.2 


2.4 


2.4 


Maternity center 


0.9 


1.1 


1.2 


1.3 


Non-hospital 


0.7 


0.7 


0.6 


0.6 


Out of Florida 


0.6 


0.5 


0.5 


0.1 


Enroute to hospital 


0.2 


0.2 


0.2 


0.1 


Unknown 


0.7 


0.8 


0.9 


0.9 



Once we made a hospital-level match, we used a patient-level 
matching algorithm. We first identified the variables that were common 
to both f iles--birthdate of patient and zipcode of residence. The 
mother's HDD discharge record also included the date of first surgical 
procedure which is almost always the delivery date, and thus could be 
used as a proxy for the baby's birthdate. This additional linking 
variable increased our ability to find unique matches and increased our 
confidence in the validity of the match. The third data element, zipcode 
of residence, was available on 99% of both the VS and HDD files. We 
used a hierarchy approach in which we first required a match on all 
three linking variables, then subsequently loosened the restrictions 
requiring either an exact match on mother's birthdate and baby's 
birthdate with missing or nonmatching zipcodes, or else a match on 
mother's birthdate and zipcode with the baby's birth falling sometime 
within the time of hospitalization, although not on the procedure date. 

Using this algorithm, we were able to match between 91 percent and 
94 percent of the VS events that occurred at an HDD hospital. If we use 
the entire universe of VS births and fetal deaths as the denominator, 
the match rate ranges from 86 percent for 1988 to 89 percent for 1991. 
Table C8 presents the VS records that had matched to the HDD at the 
hospital level, and identifies the percentage satisfying each of the 
match criteria, as well as those that remain unmatched. 



C-ll 



Table C8. VS Match Rate to HDD File, 1988-1991 



1988 1989 1990 1991 



Match on mother's dob, baby's 

dob, zipcode 73.5% 74.1% 76.9% 77.3% 

Match on mother's dob, baby's 

dob (not zipcode) 12.7% 11.1% 10.6% 11.0% 

Match on mother's dob & 

zipcode, birth w/in 

hospitalization 5.1% 7.6% 6.7% 6.2% 

Unmatched VS record (w/match 

at hospital level) 8.8% 7.2% 5.7% 5.5% 



If we had limited our definition of a successful match to only 
those instances in which there was agreement on all three linkage 
variables, our match rate would have decreased to an average of 75 
percent of the eligible VS records. We felt that it was important to 
allow for some disagreement in variables that either tend to have 
missing values or are coded less reliably such as zipcode. Similarly, 
because procedure date is not a perfect proxy for baby's birthdate, it 
was reasonable to allow some leeway. 

Alternatively, we could have increased our match rate by loosening 
our restrictions or by adding a step in which records were compared 
manually. The former approach would have decreased the reliability of 
the data to a point where we would begin to lose confidence in the data. 
The latter approach of taking the time to manually compare lists of 
records to pick up a few additional matches was a trade-off that we 
rejected given the immense size of the databases and the high match rate 
we were able to achieve using a completely automated approach. 

Duplicate Matches 

Our confidence in the matching algorithm was bolstered because over 
97% of the VS records that matched were one-to-one matches. The non- 
unique matches resulted from two main factors: (1) records for more 
than one mother in one system matching a single record in the other 
system, and (2) multiple births. Because these duplicates accounted for 
only 1.2 percent of the matched VS records in 1988 and less than 0.2 
percent in each of the later years, we decided to maintain all the 
records in our files, but 'randomly assign only one of the matches to be 
used for analyses so that the analysis sample accurately represented the 



C-12 



number of deliveries in Florida. In contrast to the 1989-1991 files, 
the 1988 VS file recorded mother's age rather than birthdate. Because 
age in years is less unique than birthdate, there were more instances of 
multiple records with the same match characteristics. In addition, for 
the larger volume hospitals, the largest of which had over 14,000 
deliveries per year, there were some cases with non-unique matches. 

We also needed to adjust for the 2.3 percent of babies that were 
part of multiple births. These cases had a birth certificate for each 
baby but only one mother's discharge record. Because our unit of 
analysis was the delivery rather than the actual birth, we picked one of 
the birth certificate records at random to be used in analyses. 

Unmatched HDD Records 

Although we used the VS file to define our universe, we also 
examined the nonmatching HDD records. An average of 13 percent of HDD 
records identified as delivery discharges did not match to the VS file. 
Table C9 presents the match rates by year. It is possible that some of 
the non-matches are non-residents. It is also conceivable that some of 
the discharge records that we defined as delivery hospitalizations based 
on the ICD-9 code could have been coded incorrectly and were actually 
other pregnancy-related hospitalizations. 

We examined total charges and insurance status to determine if the 
nonmatches had different characteristics than the matches. The median 
total charge did not differ greatly, but there were significantly more 
nonmatches covered by "other" insurance than matches. 

Table C9. Match Rate for HDD Records, 1988-1991 



1988 1989 1990 1991 



Match to VS 157,620 167,642 173,671 169,069 

(85%) (87%) (87%) (88%) 

Unmatched 27,873 25,929 25,474 22,413 

(15%) (13%) (13%) (12%) 



C-13 



Linking in Medicaid Eligibility Data 

The VS and ME both contain Social Security number and mother's date 
of birth. We linked the files by mother's Social Security number and 
then verified the match by comparing the date-of-birth values. For each 
study year, approximately 9 5 percent of the VS records had valid Social 
Security numbers and were candidates for matching. 

Because the ME had one record for each period of Medicaid 
eligibility, after matching by Social Security number, we needed to 
identify which eligibility period contained the date of baby's birth in 
order to correctly measure whether the mother was covered at the time of 
delivery and the basis of entitlement at that time. 

Of the HDD records with valid Social Security numbers and with 
Medicaid as the primary payer, approximately 80 percent matched to an 
eligibility record on the ME file. Table CIO presents the match rate by 
year. 



Table CIO. Percentage of Medicaid 
HDD Matching to ME File 



Year 


Percentage 


1988 


67% 


1989 


73% 


1990 


79% 


1991 


92% 



Although the key reason for linking to the ME file was to identify 
the basis of Medicaid entitlement, the match to the eligibility file 
also enabled us to identify the potential false positives --women 
identified as being covered by Medicaid on the HDD but not eligible at 
the time of delivery on the ME file. 

For 1991, we were also able to examine the false negatives-- 
Medicaid eligible mothers not identified on the HDD as having a Medicaid 
payer--by linking to the Medicaid inpatient hospital claims data (MC) . 
Claims data with delivery diagnosis codes were used for this 
investigation in order to determine the number of Medicaid mothers who 
had deliveries--that is, the denominator for the estimate of false 
negatives. These records were matched back to the ME using the Medicaid 



C-14 



id, and were then linked to the VS file using the method above. Eighty- 
five percent of the delivery claims on the MC file successfully matched 
to the VS file. 

Linking in Public Health System Encounter Data 

Because the dates in the PH data are dates for prenatal care 
visits, there was no exact date we could use to match to the baby's date 
of birth on the VS file. However, we could not ignore date altogether 
because a number of women gave birth multiple times within the study 
period. In addition, roughly 120 women per year appear on the VS file 
as having delivered twice within the same year. 

To ensure that the episode was matched to the correct delivery, we 
developed a two-stage algorithm. We first matched on mother's Social 
Security number and the year of baby's birth where we used the end of 
the prenatal care episode to define the PH value for year (though for 
episodes ending in 1987 we coded the year as 1988 to match to the 
earliest births in our study) . To verify the matches we compared the 
birthdate to the prenatal care start and end dates and flagged those 
matches in which the birthdate either occurred prior to the first 
prenatal care visit or later than six months after the last visit. 
Flagged records were then placed back in with the pool of unmatched 
records, the birthyear value on the PH record was recoded to one year 
later, and the second stage of the match was performed using mother's 
Social Security number and the alternate birthyear. 

To accurately count the total number of PH visits associated with 
deliveries, we needed to estimate what percentage of the records 
corresponded to a birth during the study years. By examining the 
records that matched to the VS file, we used the relationship between 
the last date of prenatal care and the year of delivery to simulate the 
delivery year for the records we were unable to match. For example, 14 
percent of the prenatal care episodes ending in October 1990 matched to 
a delivery in 1991, so we estimated that 14 percent of the unmatched 
records ending in October 1990 corresponded to births that occurred in 
1991. Because we did not have access to 1992 records, we also estimated 
that 14 percent of the October 1991 episodes corresponded to births 
outside of the study period. Assigning unmatched records in this way, 



C-15 



between 73 and 81 percent of the PH prenatal care visits that 
corresponded to a delivery in 1988 to 1991 were matched to the VS file. 
Table Cll presents the match rate for the PH records by the year of 
delivery. 



Table Cll. Percentage of PH Prenatal 

Care Visits Matched to VS File, By 

Year 



Year 


Percentage 


1988 


77% 


1989 


81% 


1990 


74% 


1991 


73% 



Linking in AHA Data 

The AHA file's hospital identification number was different from 
both the VS and HDD identifiers. We used the same algorithm that was 
used for the hospital level match between the VS and HDD files, although 
we could now compare the AHA name with both the VS and HDD version of 
the hospital name. After most matches were made using an automated 
routine comparing the first letters of the hospital names, the few 
remaining cases were examined manually to identify the correct match. 
Of the 306 hospitals on the AHA file, all but twelve matched to either a 
VS or HDD hospital. An examination of the "number of births" variable 
from the AHA file revealed that none of the unmatched hospitals had any 
deliveries . 

Linking in the CEN Data 

Although there were 4,148 different zipcodes of residence for the 
women on the VS file who gave birth between 1988 and 1991, 95 percent of 
the women lived in the 825 zipcodes that matched to the CEN file. Of 
the VS cases that did not match, 86 percent had zipcodes that were in 
the range of Florida values but were either mispunches or zipcodes that 
did not exist at the time the CEN file was created. The 825 matched 
zipcodes accounted for all but one of the zipcodes on the CEN file. 



C-16 

The Final Linked File 

The final linked file contains one VS record per delivery and 
includes only those that matched to a HDD record. Table C12 presents 
the original number of records and then the number and percentage of 
records with successful matches to the HDD, AHA, and CEN files, 
cumulatively. Thus the final linked file is composed of records that 
represent between 86 and 89 percent of the deliveries to Florida mothers 
between 1988 and 1991. 2 In addition, we were able to match between 79 
and 85 percent of the VS cases to the HDD, AHA, and CEN files--the three 
link files that were applicable to all of the records. 

Table C12. Comparison of Original VS File to Matched Files, By Year 





1988 


1989 


1990 


1991 


Number of deliveries on 










VS file a 


184,798 


193,336 


199,663 


193,393 


Match to HDD (final 


159,077 


169,548 


177,153 


173,033 


linked file) 


(86%) 


(88%) 


(89%) 


(89%) 


Match HDD, AHA 


157,217 


167,587 


174,491 


170,758 




(85%) 


(87%) 


(87%) 


(88%) 


Match HDD, AHA, CEN 


145,203 


158,622 


168,498 


165,333 




(79%) 


(82%) 


(84%) 


(85%) 



a Total number of deliveries includes deliveries to residents that 
took place outside of Florida. 

The final linked file also includes the additional information 
obtained for the subset of Medicaid eligible and low-income women by 
matching to the ME and PH files. As a result of linking the VS file to 
these five additional files, each of which provides useful data that was 
otherwise unavailable, the final linked file represents a database rich 
in information. 



2 Because four to five percent of the records in the final linked 
file have missing values for some of the key outcome measures or 
demographic characteristics, an analysis file containing only those 
records with complete data would be slightly smaller. 



D-l 



APPENDIX D. ESTIMATION FOR AGGREGATE ANALYSIS 



This appendix provides more detail on our procedures for estimating 
the flow of pregnant women through prenatal care and delivery, the 
corresponding use of services, and the flow of payments for this care. 

ANALYTIC FRAMEWORK 

Our method is modeled after the National Health Expenditures 
Accounts, a continuing series currently maintained by the Health Care 
Financing Administration which estimates the flow of funds financing all 
health care in the United States. We develop three matrices to 
investigate the effects of the expansions. The first (see Table 2 in 
the report) categorizes women according the primary payer for their care 
and describes how this changed after the Medicaid expansion. The payer 
categories in the matrix include private insurance, Medicaid, and "other 
payer", which includes the uninsured and those whose care was paid for 
by some other third party-payer such as Medicare, CHAMPUS, or state and 
federal programs that make payments on behalf of a patient receiving 
care. The hospital discharge data--our primary source for payer--does 
not allow us to further classify these other payers. 

The second matrix (see Tables 3 and 4 in the report) shows the 
effects of the expansions on the quantity and type of health care 
services received by pregnant women. The utilization matrix shows the 
number of prenatal care visits and the number of pregnancy related 
hospitalizations in each of the study years and the change in these 
quantities over time. The utilization measures are categorized by both 
payer and site of service. For ambulatory care we distinguish between 
care provided in county health departments, that received in physician 
offices, and care in other settings such as Community Health Centers, 
hospital clinics, and hospital outpatient departments. Hospital 
admissions are categorized by the type of hospital--public, voluntary, 
or proprietary. 

The third matrix (see Table 5 in the report) is a flow of funds 
matrix. The columns of the matrix categorize the expenditures by type 
of service (hospital inpatient, physician and other services) and the 



D-2 



rows by payer. The unit of measure in this matrix is dollars, and the 
dollars that we measure are the direct payments made by the patient or 
by a third-party on behalf of a particular patient. 

ESTIMATING THE THREE MATRICES 

Flow of Women 

The first matrix shows the number of women delivering in each year 
and the primary payer for their maternity care. The vital statistics 
records for all births and fetal deaths registered to Florida residents 
measure the total number of deliveries in each year. This serves as a 
control total for all of our other estimates. These deliveries were 
distributed among the three payer categories based on the distribution 
of primary payer at delivery from the matched hospital discharge file 
and vital statistics file for each year. 

Utilization Matrix 

Ambulatory Prenatal Visits 

The total number of prenatal visits is based on information 
recorded on the birth certificate. We estimated the average number of 
prenatal visits for women in each of the three different payer groups 
from the linked vital statistics and hospital discharge file (see Table 
Dl) . These per case estimates, multiplied by the total number of 
deliveries in each of the three payer groups, yielded our estimate of 
the total number of prenatal care visits by payer. 



Table Dl . Average Number of Prenatal Care 
Visits Per Delivery by Payer 



Period 



Payer 


Baseline 


1991 


Private Insurance 


12.3 


12.8 


Medicaid 


9.8 


10.5 


Other Payer 


9.6 


10.2 



D-3 



We distribute these visits by site of care--county health 
department versus other sites--based on the public health system 
encounter data . Our matrices measure care provided to women who 
delivered in the year of study, irrespective of the year in which the 
service was actually delivered. Therefore, we needed to link the county 
health department visits to the year of delivery of the patient. We did 
this in a two step manner. First, for county health department episodes 
that we were able to link to the vital statistics and hospital discharge 
data, we have a direct measure of the year of delivery. Using the 
relationship between the last date seen in the county health department 
and the year of delivery for these episodes, we then simulated the 
delivery year for episodes that we were unable to match to vital 
records. Then, we counted the total number of prenatal visits to county 
health departments associated with deliveries in the year of study as 
the health department column total in our matrix. This total was 
allocated among the three payer groups based on the distribution of 
payer for the county health department visits that were matched to the 
vital statistics/hospital discharge file from which we can measure the 
primary payer. 

Hospital Admissions 

The total number of hospital admissions for maternity care include 
hospital admissions for delivery as well as inpatient prenatal hospital 
admissions. The former admissions are determined from the vital 
statistics data on place of delivery--i .e. not all deliveries are 
associated with a hospital admission. This count of delivery admissions 
is a control total. We categorize deliveries by both type of hospital-- 
public, voluntary, and proprietary- -and by payer. To do so, we first 
calculate the distribution of deliveries across hospital types for all 
vital statistic records that we are able to link to the AHA data. We 
use this distribution to allocate the total delivery admissions to each 
hospital type. We next estimate the distribution of payer by hospital 
type from the matched vital statistics and hospital discharge file for 
each hospital type to allocate the delivery admissions across payers. 

We estimated the number of pregnancy-related admissions as the 
number of admissions with ICD-9 codes related to prenatal or maternity 



D-4 



care that did not result in a delivery. Because the hospital discharge 
data lacks identifiers, we are not able to track the non-delivery 
hospital admissions of women who gave birth in the study year. We 
therefore approximate these by looking at all prenatal admissions in a 
year, regardless of whether the woman actually gave birth in the year. 
If the number of births is constant over time, then this method should 
provide an unbiased estimate of the number of prenatal admissions for 
women delivering in the study year. We distribute these admissions 
among hospital types and payers using the AHA data on hospital type and 
the discharge record information on payer. 

The Flow of Payments Matrix 

The third matrix we present shows the flow of payments for maternal 
care in the two years. It measures the direct payments for care by 
patients and on account of patients by third-party payers. That is it 
measures what was actually collected by the provider for the care of a 
particular patient. It does not include contributions that are not tied 
to particular patients, such as federal block grants to states for Title 
V programs and general contributions by local governments to public 
hospitals for charity care. 

To measure the payment flows, we start with an estimate of the 
total charges for inpatient hospital services and for physician and 
related services (such as laboratory tests and x-rays) categorized by 
the delivery payer. The total charge estimates for each payer are based 
on estimates of the average charge per quantity of service multiplied by 
our estimates of the units of service. We convert the result matrix of 
charges to payments using estimates of the ratio of payments to charges 
for different payers. The steps are detailed below. 

Estimating Physician and Related Service Charges 

Our calculation of physician and related charges is based on an 
estimate of the total charge for these maternal health services per 
prenatal visit. This per visit charge measure is multiplied by our 
estimate of the total number of prenatal care visits for each payer 
group and site of care to provide an aggregate charge for each payer and 
site. When we calculate payment, we wish to distinguish payments made 



D-5 



by third-parties from those made directly by patients. Therefore, for 
this purpose, we produce an estimate of the number of visits made by 
women in the "other" payer category that were made by uninsured women 
and those made by women with coverage from some other third-party. This 
allocation was based on the distribution of visits between these groups 
as reported in the 1988 National Maternal and Infant Health Survey by 
sample person in Florida. This allocation then permitted us to estimate 
the charges for uninsured patients and for patients with other third- 
party payers. However, because we have only one survey, the same 
allocation factor was used for both the baseline period and 1991. 
Because the Medicaid expansions would be expected to alter the mix, and 
in particular to decrease the share of uninsured patients, our method 
will tend to understate the increase in payments resulting from the 
expansions . 

The per visit charge number is based on data from the 1991 Medicaid 
claims files and on data from two large employers in Florida. The 
Medicaid estimate of charges per visit is the ratio of charges on all 
Medicaid claims for physician and related services (laboratory, x-ray, 
outpatient hospital) to the total number of prenatal care visits as 
recorded on birth certificates for women covered by Medicaid who 
delivered in the last three months of 1991. The estimate is restricted 
to those delivering at the end of 1991 to ensure that we have claims for 
the entire prenatal period in the 1991 claims data file available to 
this study. We include only charges for services provided during the 
prenatal and delivery period. We also restricted the estimate to 
patients who receive their care in the private sector (i.e. for whom we 
do not have a county public health department encounter record) . We do 
this because we are able to estimate payments for visits to the public 
health system directly and so do not need to make a estimate of charges 
for these visits. 

The private claims database covers three years for two large 
employers. Our estimate of the charge per prenatal visit from the 
private payer data is the ratio of charges (in 1991 dollars) for all 
claims for maternity care from physicians or related providers divided 
by our estimate of the average number of prenatal care visits in 1991 by 
women covered by private payers (see Table Dl) . Our estimate of the 



D-6 



average charge per visit from the Medicaid data was $32 6; our estimate 
from the private claims data was $353. Because these estimates were so 
similar, we used the average value of $340 per visit charge for all 
payers . 

Our procedure applies the same estimate of charges relative to 
prenatal care visits for all payers. Estimates of the per delivery 
charges, however, vary by payer type because of differences in the 
average number of prenatal care visits among the payer groups. Our 
procedure assumes that variation in the number of prenatal care visits 
reflects differences in patient needs and service mix. 

Estimating Hospital Charges 

For hospital admissions, estimates of the average charge for women 
in different payer statuses and in different hospital types are from the 
hospital discharge data. For deliveries, these charges are from the 
matched vital statistics and hospital discharge file. For prenatal 
admissions, the charges are for all of the hospital discharge records 
that were identified as prenatal admissions in the year. Appendix Table 
D2 presents the average charges that we used in calculating the 
aggregate charge numbers; the baseline period charges shown here were 
inflated to 1991 dollars for the payment matrix using the hospital 
component of the consumer price index. 



Table D2 . Average Hospital Charges Per Delivery 
By Payer And Type Of Hospital 

(in current dollars) 







Baseline 






1991 




Payer 


Public 


Voluntary 


Proprietary 


Public 


Voluntary 


Proprietary 


Private 














Insurance 


2760 


2772 


2844 


3772 


4012 


4263 


Medicaid 


2968 


2843 


2870 


3598 


3677 


3839 


Other Payer 


2935 


2634 


2830 


3395 


3691 


3653 



To allocate the charges for women in the "other payer" category 
between uninsured women and those with a third-party payer, we used the 
distribution of deliveries among these groups based on the NMIHS data. 
Again, because we use a constant allocation factor over time, we will 



D-7 



understate the increase in payments to hospitals stemming from the 
expansions . 

Calculating Payments From Charges. 

Using charges to estimate payments would result in an overestimate 
of the actual payment flows. Increasingly over the last decade, third- 
party payers have either refused to pay full charges, as has Medicaid, 
or negotiated discounts, as have Blue Cross and Blue Shield and most 
managed care organizations. Moreover, uninsured patients are frequently 
unable to pay much, if any, of a hospital's normal charge for delivery, 
but generally they are not denied care. 

Therefore, we adjusted the estimated aggregate charges for each 
payer using payment-to-charge ratios for each payer category. The 
payment -to -charge ratio is always less than one reflecting deductions 
from gross charges for contractual adjustments and uncompensated care. 

Payment -to -charge ratios for hospital care for each payer were 
provided by the Agency for Health Care Administration in Florida. The 
Medicaid payment-to-charge ratio for physician and related services was 
derived from the Medicaid claims files for the sample of women described 
above in calculating charge per visit ratios . The ratio for private 
payers was based on the maternity claims data from two large Florida 
employers. We also used these claims data to estimate the share of the 
total payment that was made by the insurer and the share paid directly 
by the patient in copayments . Separate estimates were made of the 
copayment share for hospital services and for physician and related 
services . 

Absent other data sources to provide payment-to-charge ratios for 
physician services in Florida for the uninsured and those covered by 
third-party payers other than private insurance and Medicaid, we used 
the hospital ratios. Payments to county health departments were 
measured from state budget and revenue statistics provided by the state 
health department . 



E-l 



APPENDIX E. EXPLANATORY VARIABLES AND REFERENCE POPULATION 



This appendix tables shows the definitions of the demographic 
characteristics included in our regression model and presents the values 
of these characteristics for our reference population- -women enrolled in 
the Medicaid expansion group in 1991. 

Table El. Characteristics of Reference Population 



Value for 
Reference 

Characteristic Population 

Age of mother 

Under age 18 * 0.08 

18-19 0.13 

20-24 0.36 

25-29 0.24 

30-34 0.13 

35 and older 0.06 

Mother's education 

Less than high school * 0.37 

High school graduate 0.44 

Some college 0.16 

College degree 0.03 

Race/ethnicity (1991 regressions) 

White, non-hispanic * 0.66 

Black, non-hispanic 0.15 

Other, non-hispanic 0.01 

Mexican 0.05 

Puero Rican 0.03 

Cuban 0.02 

Central/South American 0.04 

Haitian 0.02 

Other hispanic 0.02 

Race (1988 regressions) 

White * 0.81 

Black 0.18 

Other 0.01 

Marital Status 

Married . 64 

Not married 0.36 

Indicator for no previous live 

births 0.44 

Indicator for singleton 

birth 0.99 

Indicator for any medical risk 
factors (1991 regression) .21 

* Denotes ommitted class in regression model 



F-l 



Appendix F. REGRESSION RESULTS 



This appendix contains the parameter estimates and standard errors 
(S.E.) for the regressions described in the text. The explanatory 
variables indicate whether or not the mother has the characteristics. 
With the exception of the insurance class variables, the indicator was 
coded as one minus the proportion of the 1991 Medicaid expansion group 
with the characteristic if the mother had the characteristic and minus 
the proportion of the 1991 Medicaid expansion group otherwise. (The 
proportion of the 1991 Medicaid expansion population with each 
characteristic, and the omitted subgroup for each characteristic, are 
shown in Appendix E) . The insurance variables are coded or 1 to 
indicate the mother's status, and Medicaid expansion is the omitted group. 
This coding was adopted so that the intercept reflects the value for a 
woman in the Medicaid expansion population with characteristics equal to 
the average value of characteristics for women in the Medicaid expansion 
population in 1991. 



F-2 



Regression Parameter Estimates and Standard Errors for Baseline Period (1) 

July 88 - June 89 



Dependent 








of users: 


of users: 


Variable: 


no prenatal 


care 


initiate 


in 1st 


# of visits 










or 2nd trimester 










Logit 






Logit 






OLS 






Explanatory- 


Parameter 




Parameter 




Parameter 




variable 


Estimate 
-4.2248 





S.E. 
.0719 


Esitmate 
2.5390 





S.E. 
.0369 


Estimate 
10.9651 





S.E. 


Intercept 


.0424 


mother 18-19 yrs 


0.0631 





.0686 


-0.0362 





.0492 


-0.1190 





.0612 


mother 20-24 yrs 


0.0190 





.0644 


0.2408 





.0479 


0.1216 





.0562 


mother 25-29 yrs 


-0.1253 





.0703 


0.5663 





.0538 


0.3768 





.0588 


mother 3 0-34 yrs 


-0.1697 





.0784 


0.7218 





.0616 


0.4689 





.0621 


mother 3 5 and over 


-0.4045 





.1011 


0.7730 





.0778 


0.5529 





.0693 


mother is married 


-0.9785 





.0405 


0.6272 





.0308 


0.9200 





.0311 


12 yrs educ 


-0.5114 





.0375 


0.2924 





.0296 


0.6426 





.0317 


13-15 yrs educ 


-1.0440 





.0664 


0.5135 





.0450 


1.0070 





.0377 


16+ years educ 


-1.6962 





.1373 


1.0160 





.0787 


1.2695 





.0437 


black 


0.2480 





.0380 


0.0566 





.0302 


-0.7411 





.0302 


other race 


0.2405 





.1583 


-0.7321 


0, 


.0958 


-0.8517 


0. 


.0939 


singleton birth 


0.4479 


0. 


.1774 


-0.7846 





.1571 


-1.7584 


0, 


,1006 


no prev live births 


-0.9786 





,0426 


0.6446 


0, 


,0299 


0.7243 


0. 


0239 


medicaid: afdc elig 


0.2774 





,0794 


0.1485 


0, 


,0456 


-0.1046 


0. 


0541 


medicaid: medic needy 


0.5783 


0, 


,1751 


-0.0272 


0, 


,1104 


0.0407 


0. 


1249 


medicaid: other 


0.5145 


0, 


,1717 


0.1799 


0. 


,1362 


0.2272 


0. 


1613 


private, >=30% poor 


-0.6411 


0. 


,1350 


1.0960 


0. 


0774 


0.7333 


0. 


0590 


private, < 3 0% poor 


-0.9802 


0. 


,1045 


1.4384 


0. 


,0560 


0.6934 


0. 


0485 


private, no zip 


-0.4117 


0. 


1977 


1.0345 


0. 


1159 


0.6429 


0. 


0762 


oth ins, >=3 0% poor 


0.9757 


0. 


0794 


0.0438 


0, 


0486 


-1.1984 


0. 


0565 


oth ins, < 3 0% poor 


0.9980 


0. 


0765 


0.1829 


0. 


0443 


-0.4655 


0. 


0493 


oth ins, no zip 


1.3828 


0. 


0994 


-0.1730 


0. 


0730 


-0.6440 


0. 


0863 



F-3 



Regression Parameter Estimates and Standard Errors for Baseline Period (2) 

July 88 - June 89 



Dependent 
variable : 



Explanatory 
variable 



Intercept 
mother 18-19 yrs 
mother 20-24 yrs 
mother 25-29 yrs 
mother 3 0-34 yrs 
mother 3 5 and over 
mother is married 
12 yrs educ 
13-15 yrs educ 
16+ years educ 
black 
other race 
singleton birth 
no prev live births 
medicaid: afdc elig 
medicaid: medic needy 
other 
>=30% poor 

< 3 0% poor 
no zip 
>=30% poor 

< 3 0% poor 
no zip 



medicaid 
private, 
private, 
private, 
oth ins, 
oth ins, 
oth ins. 



inadequate care: inadequate care: 
kotelchuck kessner 



Logit 
Parameter 
Estimate S.E. 



-0.6102 

0.0055 

-0.1511 

-0.4047 

-0.4760 

-0.4973 

-0.5876 

-0.3707 

-0.5992 

-0.9227 

0.2790 

0.4629 

0.1815 

-0.4553 

-0.0568 

0.2354 

-0.0727 

-0.7287 

-0.8405 

-0.7633 

0.2688 

0.0146 

0.2210 



0.0212 
0.0298 
0.0277 
0.0297 
0.0322 
0.0377 
0.0158 
0.0159 
0.0208 
0.0284 
0.0158 
0.0530 
0.0598 
0.0144 
0.0267 
0.0616 
0.0779 
0.0335 
0.0259 
0.0481 
0.0278 
0.0248 
0.0423 



Logit 

Parameter 

Estimate 

-2.3266 

0.0487 
-0.1487 
-0.4235 
-0.5348 
-0.6667 
-0.7868 
-0.3993 
-0.7154 
-1.2423 

0.0987 

0.6349 

0.5075 
-0.7756 
-0.0777 

0.1472 
-0.0369 
-0.9964 
-1.3097 
-0.8831 

0.2591 

0.1643 

0.5524 



S.E. 

0.0330 
0.0411 
0.0393 
0.0436 
0.0492 
0.0626 
0.0248 
0.0237 
0.0370 
0.0668 
0.0241 
0.0838 
0.1107 
0.0248 
0.0396 
0.0952 
0.1092 
0.0663 
0.0489 
0.0992 
0.0410 
0.0380 
0.0587 



F-4 



Regression Parameter Estimates and Standard Errors for Baseline Period (3) 

July 88 - June 89 

Dependent 
variable : 



Explanatory- 
variable 



Intercept 
mother 18-19 yrs 
mother 20-24 yrs 
mother 2 5-29 yrs 
mother 3 0-34 yrs 
mother 3 5 and over 
mother is married 
12 yrs educ 
13-15 yrs educ 
16+ years educ 
black 
other race 
singleton birth 
no prev live births 
medicaid: afdc elig 
medicaid: medic needy 
other 
>=30% poor 

< 3 0% poor 
no zip 
>=30% poor 

< 30% poor 
no zip 



medicaid: 
private, 
private, 
private, 
oth ins, 
oth ins, 
oth ins, 









very 1 


ow 




survive 


low birthweight 


birthweii 


jht 


first 


year 


Logit 






Logit 






OLS 




Parameter 




Parameter 




Parameter 


Estimate 




S.E. 


Estimate 




S.E. 


Estimate 


S.E. 


-2.6303 





.0384 


-4.7118 





.0951 


4.9752 


0.1139 


-0.0118 





.0494 


-0.1117 





.1150 


-0.0294 


0.1401 


0.0942 





.0451 


-0.0335 





.1039 


-0.0971 


0.1280 


0.1914 





.0481 


0.1071 





.1102 


0.0320 


0.1384 


0.3719 





.0516 


0.2603 





.1183 


-0.0453 


0.1491 


0.4920 





.0589 


0.3610 





.1350 


0.0113 


0.1754 


-0.4119 





.0273 


-0.4397 





.0643 


0.4469 


0.0781 


-0.2181 





.0275 


-0.1248 





.0658 


0.3294 


0.0782 


-0.3148 





.0352 


-0.1173 





.0821 


0.2542 


0.0988 


-0.5205 





.0449 


-0.2793 





.1052 


0.4517 


0.1309 


0.6318 





.0256 


0.9220 





.0593 


-0.3338 


0.0741 


0.3131 





.0894 


0.5637 





.1978 


-0.6200 


0.2185 


-2.9266 





,0505 


-2.4450 





.0865 


1.7410 


0.1288 


0.2875 





.0235 


0.3156 


0. 


,0557 


0.0675 


0.0685 


-0.0342 


0. 


.0462 


-0.1351 


0. 


.1116 


0.0314 


0.1363 


0.2739 


0. 


.1032 


0.8264 


0, 


,2018 


-0.6284 


0.2632 


0.4386 


0. 


.1088 


0.3075 


0. 


2588 


0.2891 


0.4269 


-0.2064 


0. 


0562 


0.00985 


0. 


1301 


-0.2277 


0.1563 


-0.2793 


0. 


.0457 


-0.1567 


0. 


1115 


0.1530 


0.1353 


-0.0862 


0. 


0765 


0.2761 


0. 


1705 


-0.3168 


0.2054 


0.0750 


0. 


0484 


0.1105 


0. 


1157 


-0.2184 


0.1402 


-0.0742 


0. 


0451 


-0.00439 


0. 


1102 


-0.0627 


0.1319 


0.1913 


0. 


0740 


0.5703 


0. 


1613 


-0.2111 


0.2156 



F-5 



Regression Parameter Estimates and Standard Errors for Post Period (1) 

1991 



Dependent 








of users: 


of users: 


Variable: 


no prenatal 


care 


initiate 


in 1st 


# of visits 










or 2nd trimester 










Log it 






Logit 






OLS 






Explanatory- 


Parameter 




Parameter 




Parameter 




variable 


Estimate 
-4.3578 





S.E. 
.0495 


Estimate 
3.0054 





S.E. 
.0280 


Estimate 
11.2394 





S.E. 


Intercept 


.0246 


mother 18-19 


-0.0429 





.0777 


0.1057 





.0560 


0.0076 





.0586 


mother 20-24 


-0.1548 





.0731 


0.2470 





.0534 


0.2284 





.0538 


mother 2 5-29 


-0.2784 





.0810 


0.4812 





.0602 


0.4030 





.0566 


mother 3 0-34 


-0.2435 





.0892 


0.7044 





.0693 


0.4447 





.0596 


mother 35 and over 


-0.2808 





.1065 


0.7292 





.0840 


0.5547 





.0651 


mother is married 


-0.8578 





.0483 


0.4500 





.0346 


0.7420 





.0288 


12 yrs educ 


-0.4335 





.0442 


0.2892 





.0334 


0.5002 





.0304 


13-15 yrs educ 


-0.7725 





.0709 


0.4842 





.0507 


0.8707 





.0362 


16+ years educ 


-1.5275 





.1389 


0.8409 





.0859 


0.9979 





.0418 


black, nonhisp 


0.2102 





.0470 


-0.1544 





.0361 


-0.9446 





.0301 


other, nonhisp 


0.1033 





.1840 


-0.7165 





.1101 


-0.7516 





.0875 


mexican ethnicity 


0.2331 





.0888 


-0.7735 





.0587 


-1.5247 


0, 


.0678 


puerto rican 


0.1795 





.1160 


0.0248 


0, 


.0926 


-0.7244 


0, 


,0682 


cuban 


-0.8246 





.1760 


0.7906 





.1284 


-0.5809 


0. 


,0530 


central/south amer 


-0.0200 


0. 


,0882 


-0.3607 


0, 


.0628 


-1.5370 


0. 


0504 


other hisp ethnicity 


-0.0706 


0. 


.1676 


-0.6287 


0, 


.0984 


-0.5811 


0. 


0913 


haitian 


-0.6887 


0. 


.1564 


0.0227 


0, 


,1009 


-1.6555 


0. 


0799 


any med hist factors 


0.5351 


0, 


,0409 


-0.1057 


0, 


,0338 


0.6980 


0. 


0255 


singleton birth 


0.0996 


0. 


,1662 


-0.4930 


0, 


,1554 


-1.5174 


0. 


0959 


no prev live births 


-0.9257 


0. 


0490 


0.6016 


0. 


0338 


0.5870 


0. 


0227 


medicaid: afdc elig 


0.2164 


0. 


0600 


0.0242 


0. 


0392 


-0.0384 


0. 


0368 


medicaid: medic needy 


0.6644 


0. 


1898 


0.3379 


0. 


1681 


-0.1518 


0. 


1181 


medicaid: other 


0.3947 


0. 


1668 


-0.1558 


0. 


1040 


-0.9421 


0. 


1130 


private, >=30% poor 


-0.6109 


0. 


1396 


1.1764 


0. 


0982 


0.9701 


0. 


0487 


private, < 3 0% poor 


-1.0430 


0. 


0958 


1.5520 


0. 


0620 


0.9919 


0. 


0329 


private, no zip 


-0.4194 


0. 


2836 


0.9606 


0. 


1966 


0.5768 


0. 


0947 


oth ins, >=30% poor 


1.0012 


0. 


0718 


-0.1387 


0. 


0542 


-0.6507 


0. 


0545 


oth ins, < 30% poor 


0.9718 


0. 


0640 


0.1474 


0. 


0486 


-0.1600 


0. 


0395 


oth ins, no zip 


1.2251 


0. 


1569 


-0.0470 


0. 


1493 


-0.0351 


0. 


1404 



F-6 



Regression Parameter Estimates and Standard Errors for Post Period (2) 

1991 



Dependent 
variable : 



inadequate care: 
kotelchuck 



inadequate care: 
kessner 



Explanatory 
variable 



Intercept 
mother 18-19 
mother 20-24 
mother 25-29 
mother 3 0-34 
mother 3 5 and over 
mother is married 
12 yrs educ 
13-15 yrs educ 
16+ years educ 
black, nonhisp 
other, nonhisp 
mexican ethnicity 
puerto rican 
cuban 

central /south amer 
other hisp ethnicity 
haitian 

any med hist factors 
singleton birth 
no prev live births 
medicaid: afdc elig 
medicaid: medic needy 
other 
>=30% poor 

< 3 0% poor 
no zip 
>=30% poor 

< 30% poor 
no zip 



medicaid: 
private, 
private, 
private, 
oth ins, 
oth ins, 
oth ins, 



Logit 

Parameter 

Estimate 

-1.2364 

-0.1095 

-0.3071 

-0.5715 

-0.6663 

-0.6721 

-0.5655 

-0.2819 

-0.5282 

-0.9711 

0.2944 

0.5403 

0.6539 

0.1010 

-0.4066 

0.2999 

0.4281 

0.1857 

0.0722 

0.2491 

-0.5742 

-0.0226 

-0.0688 

0.0971 

-1.0981 

-1.4435 

-0.7778 

0.1242 

-0.1562 

0.0610 



S.E. 

0.0146 
0.0313 
0.0297 
0.0328 
0.0363 
0.0426 
0.0179 
0.0177 
0.0251 
0.0402 
0.0187 
0.0636 
0.0365 
0.0461 
0.0509 
0.0338 
0.0589 
0.0494 
0.0178 
0.0707 
0.0174 
0.0209 
0.0754 
0.0615 
0.0428 
0.0276 
0.0831 
0.0301 
0.0249 
0.0813 



Logit 

Parameter 

Estimate 

-2.6858 
-0.0852 
-0.2150 
-0.4084 
-0.5438 
-0.5390 
-0.6149 
-0.3555 
-0.6053 
-1.0496 

0.2363 

0.5214 

0.6068 

0.0372 
-0.7728 

0.2232 

0.4314 
-0.2135 

0.2920 

0.1913 
-0.7159 

0.0164 
-0.0228 

0.2095 
-0.9839 
-1.4373 
-0.8428 

0.4182 

0.2105 

0.4488 



S.E. 

0.0240 
0.0455 
0.0431 
0.0482 
0.0544 
0.0650 
0.0279 
0.0265 
0.0406 
0.0703 
0.0283 
0.0956 
0.0499 
0.0727 
0.1004 
0.0515 
0.0854 
0.0831 
0.0258 
0.1059 
0.0275 
0.0322 
0.1245 
0.0891 
0.0762 
0.0508 
0.1588 
0.0427 
0.0376 
0.1097 



F-7 



Regression Parameter Estimates and Standard Errors for Post Period (3) 

1991 



Dependent 
variable : 



Explanatory 
variable 



low birthweight 

Logit 
Parameter 
Estimate S.E. 



Intercept 

mother 18-19 

mother 20-24 

mother 25-29 

mother 3 0-34 

mother 3 5 and over 

mother is married 

12 yrs educ 

13-15 yrs educ 

16+ years educ 

black, nonhisp 

other, nonhisp 

mexican ethnicity 

puerto rican 

cuban 

central /south amer 

other hisp ethnicity 

haitian 

any med hist factors 

singleton birth 

no prev live births 

medicaid: afdc elig 

medicaid: medic needy 

medicaid: other 

private, >=3 0% poor 

< 3 0% poor 
no zip 
>=30% poor 

< 3 0% poor 
no zip 



private, 
private, 
oth ins, 
oth ins, 
oth ins, 



-2.7418 

0.0647 

0.1155 

0.1969 

0.3550 

0.5372 

-0.2966 

-0.1788 

-0.3649 

-0.4853 

0.6615 

0.1921 

-0.1425 

0.3722 

-0.00827 

0.00849 

0.0528 

0.2784 

0.7065 

-2.9368 

0.2760 

0.0139 

0.4396 

0.0195 

-0.1065 

-0.2345 

0.0149 

0.1273 

-0.1307 

0.5591 



0.0247 
0.0505 
0.0468 
0.0502 
0.0534 
0.0587 
0.0275 
0.0280 
0.0360 
0.0445 
0.0271 
0.0943 
0.0737 
0.0650 
0.0634 
0.0560 
0.0980 
0.0734 
0.0222 
0.0500 
0.0235 
0.0338 
0.1003 
0.1064 
0.0498 
0.0347 
0.0974 
0.0487 
0.0411 
0.1109 



very low 
birthweight 

Logit 
Parameter 
Estimate S.E. 



-4.6821 

-0.1244 

-0.1587 

-0.0346 

0.0500 

0.4116 

-0.3515 

-0.0346 

-0.1691 

-0.1652 

0.8089 

0.4008 

-0.2756 

0.5409 

0.3148 

0.0132 

0.1273 

0.6374 

0.9844 

-2.2392 

0.2807 

-0.1211 

0.8892 

-0.4392 

-0.0572 

-0.2999 

0.3314 

-0.0130 

-0.1451 

0.9049 



0.0582 
0.1124 
0.1041 
0.1114 
0.1194 
0.1276 
0.0638 
0.0657 
0.0838 
0.1019 
0.0618 
0.2068 
0.2017 
0.1461 
0.1401 
0.1424 
0.2350 
0.1557 
0.0488 
0.0864 
0.0546 
0.0772 
0.1872 
0.2906 
0.1104 
0.0815 
0.1935 
0.1139 
0.0956 
0.2083 



survive 
first year 

OLS 

Parameter 
Estimate S.E. 



5.2077 

0.0391 

0.2708 

0.4145 

0.2249 

0.1021 

0.3088 

0.1624 

0.4463 

0.5763 

-0.4870 

-0.3094 

0.5034 

-0.1352 

0.1595 

0.3561 

0.2103 

-0.0951 

-0.5641 

1.4306 

0.0945 

0.2595 

-0.5483 

-0.0652 

-0.0982 

0.2758 

0.3636 

-0.0261 

0.0349 

•0.5026 



0.0784 

0.1494 
0.1430 
0.1579 
0.1684 
0.1881 
0.0913 
0.0908 
0.1235 
0.1581 
0.0894 
0.2948 
0.2698 
0.2307 
0.2302 
0.2154 
0.3589 
0.2504 
0.0743 
0.1622 
0.0804 
0.1098 
0.3010 
0.3509 
0.1551 
0.1161 
0.3883 
0.1593 
0.1304 
0.3455 



F-8 



Regression Parameter Estimates and Standard Errors 
for Medicaid Women with Prenatal Care Visits, 1991 (1) 



Dependent 



Variable: 


initiate 


in 1st 


# of visits 




or 2nd trimester 










Log it 






OLS 






Explanatory 


Parameter 




Parameter 




variable 


Esitmate 
3.2568 





S.E. 
.0439 


Estimate 
11.7617 





S.E. 


Intercept 


.0369 


mother 18-19 yrs 


0.1137 





.0679 


0.0313 





.0761 


mother 20-24 yrs 


0.2592 


o. 


.0659 


0.2631 





.0733 


mother 2 5-29 yrs 


0.4342 





.0750 


0.4537 





.0821 


mother 3 0-34 yrs 


0.5385 





.0870 


0.4403 





.0925 


mother 3 5 and over 


0.5502 





.1108 


0.5646 





.1140 


mother is married 


0.2832 





.0430 


0.5589 





.0441 


12 yrs educ 


0.1664 





.0396 


0.2363 





.0429 


13-15 yrs educ 


0.2602 


0, 


.0642 


0.6319 





.0624 


16+ yrs educ 


0.2845 


0, 


.1535 


0.2841 





.1311 


black, nonhisp 


-0.1094 


0. 


.0418 


-1.2312 





.0451 


other, nonhisp 


-0.7367 





.1582 


-1.3085 


0, 


.2060 


mexican ethnicity 


-0.5607 





.0864 


-1.6128 





.1105 


puerto rican 


0.1002 





.1079 


-1.1148 





.1049 


cuban 


0.5804 





.1634 


-1.7950 





.1196 


central /south amer 


-0.0766 


0. 


,1157 


-2.3343 





.1105 


other hisp ethnicity 


-0.3133 


0. 


,1507 


-0.6277 





.1753 


haitian 


0.1847 


0. 


,1542 


-2.1772 





.1427 


any med hist factors 


-0.0705 


0. 


.0408 


0.5472 





.0442 


singleton birth 


-0.5009 


0. 


,1916 


-1.0481 





.1666 


no previous live births 


0.7139 


0. 


.0439 


0.8257 





.0434 


medicaid: afdc elig 


-0.1296 


0. 


,0590 


-0.0957 





.0552 


>=50% visits @ pubhlth 


-0.5411 


0. 


.0559 


-1.0924 





.0535 


interact afdc & pubhlth 


0.0623 


0, 


,0711 


-0.0492 





.0733 



F-9 



Regression Parameter Estimates and Standard Errors 
for Medicaid Women with Prenatal Care Visits, 1991 (2; 



Dependent 


inadequate 


care: 


inadequate 


care: 


variable: 


kotelchuck 


kessner 




Logit 






Logit 






Explanatory 


Parameter 




Parameter 




variable 


Estimate 
-1.4658 





S.E. 

.0217 


Estimate 
-3.1402 





S.E. 


Intercept 


.0416 


mother 18-19 yrs 


-0.1619 





.0380 


-0.1362 





.0644 


mother 20-24 yrs 


-0.3492 





.0370 


-0.2758 





.0624 


mother 25-29 yrs 


-0.5434 





.0422 


-0.4294 





.0710 


mother 30-34 yrs 


-0.5599 





.0480 


-0.5277 





.0822 


mother 3 5 and over 


-0.5709 





.0602 


-0.4898 





.1034 


mother is married 


-0.2913 


0, 


.0236 


-0.3069 





.0411 


12 yrs educ 


-0.1267 





.0222 


-0.1752 





.0376 


13-15 yrs educ 


-0.2261 


0, 


.0341 


-0.3048 


0, 


.0616 


16+ yrs educ 


-0.2796 


0, 


.0778 


-0.2375 


0, 


.1418 


black, nonhisp 


0.2302 


0. 


.0233 


0.1889 


0. 


.0396 


other, nonhisp 


0.6386 





.1013 


0.6949 


0, 


.1553 


mexican ethnicity 


0.5293 


0. 


.0539 


0.5167 


0. 


.0847 


puerto rican 


0.0105 


0. 


.0568 


-0.1020 


0. 


,1040 


cuban 


-0.1551 


0. 


.0697 


-0.5240 


0. 


,1529 


central/south amer 


0.1653 


0. 


.0604 


0.0923 


0. 


,1105 


other hisp ethnicity 


0.2473 


0, 


,0900 


0.2895 


0. 


,1468 


haitian 


0.1101 


0, 


.0762 


-0.1259 


0. 


1435 


any med hist factors 


-0.0500 


0. 


,0233 


0.1123 


0. 


0384 


singleton birth 


0.2125 


0. 


0914 


0.2438 


0. 


1614 


no previous live births 


-0.5395 


0. 


0235 


-0.7150 


0. 


0418 


medicaid: afdc elig 


0.1576 


0. 


0303 


0.1097 


0. 


0558 


>=50% visits @ pubhlth 


0.3937 


0. 


0296 


0.5064 


0. 


0534 


interact afdc & pubhlth 


-0.0641 


0. 


0387 


-0.0345 


0. 


0677 



F-10 



Regression Parameter Estimates and Standard Errors 
for Medicaid Women with Prenatal Care Visits, 1991 (3) 



Dependent 
variable: 



Explanatory 
variable 



Intercept 

mother 18-19 yrs 

mother 20-24 yrs 

mother 25-29 yrs 

mother 30-34 yrs 

mother 35 and over 

mother is married 

12 yrs educ 

13-15 yrs educ 

16+ yrs educ 

black, nonhisp 

other, nonhisp 

mexican ethnicity 

puerto rican 

cuban 

central/south amer 

other hisp ethnicity 

haitian 

any med hist factors 

singleton birth 

no previous live births 

medicaid: afdc elig 

>=50% visits 8 pubhlth 

interact afdc & pubhlth 









very 


low 


survive 


low birthweight 


birthweight 


first 


year 


Logit 






Logit 




OLS 




Parameter 




Parameter 


Paramet 


er 


Estimate 




S.E. 


Estimate 


S.E. 


Estimate S.E 


-2.5809 





.0326 


-4.5072 


0.0765 


5.1042 


0.1069 


0.0111 





.0624 


-0.0952 


0.1466 


0.2981 


0.1896 


0.0183 





.0604 


-0.1600 


0.1419 


0.4915 


0.1862 


0.1544 





.0679 


-0.0245 


0.1592 


0.7061 


0.2216 


0.3968 





.0750 


0.1707 


0.1753 


0.4881 


0.2462 


0.4430 





.0912 


0.4414 


0.1993 


0.5759 


0.3179 


-0.2291 





.0394 


-0.3229 


0.0952 


0.2294 


0.1340 


-0.1304 





.0364 


-0.0177 


0.0882 


0.1198 


0.1239 


-0.3292 





.0556 


-0.1440 


0.1306 


0.1631 


0.1902 


-0.2692 





.1158 


0.2606 


0.2282 


0.3662 • 


0.4666 


0.5492 





.0376 


0.5531 


0.0899 


-0.3845 


0.1273 


-0.0374 





.1991 


0.0614 


0.4586 


-0.2364 


0.5860 


-0.2590 


0. 


.1158 


-0.2566 


0.2990 


0.5028 


0.4197 


0.2056 


0. 


.0923 


0.1579 


0.2300 


0.0812 


0.3450 


-0.1722 


0. 


,1199 


0.0997 


0.2693 


-0.0056 


0.3892 


-0.2858 


0. 


,1181 


-0.3837 


0.3111 


1.0099 


0.5852 


0.1222 


0. 


1593 


0.5118 


0.3269 


1.2398 


1.0044 


0.2566 


0. 


1170 


0.5761 


0.2421 


-0.5188 


0.3528 


0.6182 


0. 


0335 


0.9774 


0.0754 


-0.5643 


0.1120 


-2.8413 


0. 


0806 


-2.2430 


0.1293 


0.9708 


0.2878 


0.1945 


0. 


0374 


0.2291 


0.0889 


0.2442 


0.1281 


-0.0069 


0. 


0462 


-0.1357 


0.1066 


0.3544 


0.1550 


-0.3659 


0. 


0505 


-0.4666 


0.1201 


0.3322 


0.1616 


0.1025 


0. 


0650 


0.0644 


0.1569 


-0.2203 


0.2148 



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