MEDICARE

Continuous Insurance 

before Enrollment 

Associated with Better 

Health and Lower 

Program Spending

Report to Congressional Requesters

December 2013

GAO-14-53

United States Government Accountability Office
United States Government Accountability Office

Highlights of GAO-14-53, a report to 

congressional requesters

December 2013

MEDICARE

Continuous Insurance before Enrollment Associated 

with Better Health and Lower Program Spending

Why GAO Did This Study

Nearly 7 million individuals aged 55 to 

64—more than 18 percent of the preMedicare population—lacked health 

insurance coverage in the first half of 

2012. Health insurance protects 

individuals from the risk of financial 

hardship when they need medical care, 

and uninsured individuals may refrain 

from seeking necessary care because 

of the cost. If they forgo medical care

beforehand, these individuals may be 

in worse health and need costlier 

medical services after enrolling in 

Medicare compared to those with prior 

insurance.

GAO was asked to review the effects 

of having prior health insurance 

coverage on Medicare beneficiaries. 

This report examines the health status, 

program spending, and use of services 

of Medicare beneficiaries with and 

without continuous health insurance 

coverage before Medicare enrollment. 

To examine the effects of beneficiaries’ 

prior insurance coverage, GAO used 

data from the Health and Retirement 

Study and Medicare claims to conduct 

two types of multivariate analysis. GAO 

predicted probabilities of beneficiaries’ 

reporting being in good health or better 

and values for program spending and 

beneficiaries’ use of services.

In comments on a draft of this report, 

the Department of Health and Human 

Services highlighted a key finding in 

GAO’s report that beneficiaries with 

prior insurance used fewer or less 

costly medical services in Medicare 

compared with those without prior 

insurance.

What GAO Found

Beneficiaries with continuous health insurance coverage for approximately 

6 years before enrolling in Medicare were more likely than those without prior 

continuous insurance to report being in good health or better during the first 

6 years in Medicare. In particular, having prior continuous insurance raised the 

predicted probability that a beneficiary reported being in good health or better by 

nearly 6 percentage points during the first 6 years in Medicare.

Beneficiaries with prior continuous insurance had lower total program spending 

during the first year in Medicare compared with those without prior continuous 

insurance. Specifically, during the first year in Medicare, beneficiaries with prior 

continuous insurance had approximately $2,300, or 35 percent, less in average 

predicted total spending than those without prior continuous insurance. Similarly, 

beneficiaries with prior continuous insurance had lower institutional outpatient 

spending—for example, spending for services provided in a hospital outpatient 

setting—during the first and second years in Medicare compared with those 

without prior continuous insurance. In contrast, physician and other 

noninstitutional spending—spending for services provided by physicians, clinical 

laboratories, free-standing ambulatory surgical centers, and other noninstitutional 

providers—were similar during the early years in Medicare for beneficiaries with 

and without prior continuous insurance. However, during the fourth and fifth 

years in Medicare, beneficiaries with prior continuous insurance had physician 

and other noninstitutional spending that was about 30 percent higher than 

beneficiaries without prior continuous insurance.

Beneficiaries with prior continuous insurance had more physician office visits 

during the first 5 years in Medicare compared with those without prior continuous 

insurance. Specifically, during the first 5 years in Medicare, the difference in the 

average predicted number of physician office visits between beneficiaries with 

and without prior continuous insurance ranged from 1.3 to 2.5, or 23 to 

46 percent. This utilization pattern may indicate that, even after Medicare 

enrollment, beneficiaries with prior continuous insurance continued to access 

medical services differently from those without prior continuous insurance. The 

number of institutional outpatient visits was similar for beneficiaries with and 

without prior continuous insurance for the first 5 years after Medicare enrollment.

Taken together, GAO’s results show that, consistent with those of some other 

researchers, beneficiaries with prior continuous insurance used fewer or less 

costly medical services compared with beneficiaries without such insurance 

during the early years in Medicare, because they either were in better health or 

were accustomed to accessing medical services differently. This suggests that 

the extent to which individuals enroll in private insurance before age 65 has 

implications for beneficiaries’ health status and Medicare spending.

View GAO-14-53. For more information, 

contact James Cosgrove at (202) 512-7114 or 

cosgrovej@gao.gov.
Page i GAO-14-53 Pre-Medicare Insurance Coverage

Letter 1 

Background 6

Beneficiaries with Continuous Insurance before Medicare Were 

More Likely to Report Better Health after Medicare Enrollment 

than Those without Continuous Insurance 8

Beneficiaries with Continuous Insurance before Medicare Had 

Lower Program Spending and More Physician Office Visits after 

Medicare Enrollment than Those without Continuous Insurance 9

Concluding Observations 13

Agency Comments 14

Appendix I Data and Methods 15

Appendix II Comments from the Department of Health and Human Services 28

Appendix III GAO Contact and Staff Acknowledgments 30

Tables

Table 1: Predicted Probability of Beneficiaries with and without 

Prior Continuous Insurance for 6 Years before Medicare 

Reporting Good Health or Better in Medicare 8

Table 2: Predicted Total Medicare Spending for Beneficiaries with 

and without Continuous Private Insurance for 6 Years 

before Medicare 10

Table 3: Predicted Institutional Outpatient and Physician and 

Other Noninstitutional Medicare Spending for 

Beneficiaries with and without Continuous Private 

Insurance for 6 Years before Medicare 11

Table 4: Predicted Service Use for Beneficiaries with and without 

Continuous Private Insurance for 6 Years before 

Medicare 12

Table 5: Multivariate Analysis of the Effect of Prior Continuous 

Insurance on Self-Reported Health Status for 

Beneficiaries in Their First or Second Year of Medicare 

Enrollment 20

Contents
Page ii GAO-14-53 Pre-Medicare Insurance Coverage

Table 6: Multivariate Analysis of the Effect of Prior Continuous 

Insurance on Total Medicare Spending for Beneficiaries in 

Their First Year of Medicare Enrollment 23

Table 7: Beneficiaries in Study Population for Health Status 

Analyses in Their First or Second Year of Enrollment 

Compared with All Medicare Beneficiaries in Their First or 

Second Year of Enrollment, 2003-2010 26

Table 8: Beneficiaries in Study Population for Analyses of 

Spending and Use of Services in Their First Year of 

Enrollment Compared with All Medicare Beneficiaries in 

Their First Year of Enrollment, 2003-2010 27

Figures

Figure 1: Study Populations for Health Status Analyses 17

Figure 2: Study Populations for Analyses of Spending and Use of 

Services 18

Abbreviations

CMS Centers for Medicare & Medicaid Services

HRS Health and Retirement Study

This is a work of the U.S. government and is not subject to copyright protection in the 

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Page 1 GAO-14-53 Pre-Medicare Insurance Coverage

441 G St. N.W.

Washington, DC 20548

December 17, 2013

The Honorable Max Baucus

Chairman

Committee on Finance

United States Senate

The Honorable Tom Harkin

Chairman

Committee on Health, Education, Labor, and Pensions

United States Senate

The Honorable Sheldon Whitehouse

United States Senate

Nearly 7 million individuals aged 55 to 64, the pre-Medicare population, 

lacked health insurance coverage in the first half of 2012, accounting for 

more than 18 percent of this population.1 The health insurance coverage 

of pre-Medicare individuals may have implications for the Medicare 

program. Health insurance protects individuals against the risk of financial 

hardship when they need medical care, and uninsured pre-Medicare 

individuals may refrain from seeking necessary care because of the cost. 

As a result, these individuals may be in worse health and may require 

more costly medical services after Medicare enrollment compared with 

those who were insured. They also may, out of habit, continue to seek 

care differently. Previous research has produced inconclusive results 

concerning the extent to which, if at all, health insurance coverage before 

Medicare enrollment affects beneficiaries’ spending and use of services 

after enrollment.2

 

1

Agency for Healthcare Research and Quality, Table 1: Health Insurance Coverage of the 

Civilian Noninstitutionalized Population: Percent by Type of Coverage and Selected 

Population Characteristics, United States, First Half of 2012, accessed July 12, 2013, 

http://meps.ahrq.gov/mepsweb/data_stats/summ_tables/hc/hlth_insr/2012/t1_a12.pdf. 

2

See, for example, Sandra L. Decker et al., “Health Service Use among the Previously 

Uninsured: Is Subsidized Health Insurance Enough?” Health Economics (October 2012); 

J. Michael McWilliams et al., “Medicare Spending for Previously Uninsured Adults,” Annals 

of Internal Medicine, vol. 151, no. 11 (December 2009).
 

Page 2 GAO-14-53 Pre-Medicare Insurance Coverage

You asked us to provide information on the effects of Medicare 

beneficiaries’ health insurance coverage before enrollment on their health 

status, spending, and use of services after enrollment.3

To examine the effects of continuous health insurance coverage before 

Medicare (our independent variable of interest) on beneficiaries’ health 

status, spending, and use of services (our dependent variables of 

interest), we used data from the Health and Retirement Study (HRS) and 

Medicare claims. HRS is a longitudinal panel study that surveys a 

representative sample of more than 26,000 Americans aged 50 and older 

every 2 years. From HRS, we obtained information from 1996 through 

2010 on beneficiaries’ self-reported health insurance coverage before 

Medicare, self-reported health status in Medicare, and demographic and 

health-related characteristics. From the Medicare data, we obtained 

information from 2001 through 2010 on multiple categories of 

beneficiaries’ Medicare spending (total, institutional outpatient, and 

physician and other noninstitutional spending) and services (institutional 

outpatient and physician office visits).

This report 

compares (1) the health status of Medicare beneficiaries with and without 

continuous health insurance coverage before enrollment and (2) the 

spending and use of services by Medicare beneficiaries with and without 

continuous health insurance coverage before enrollment.

4

 

3

For this report, we use “spending” to refer to Medicare program spending, not beneficiary 

spending.

4

We worked with Acumen, LLC, to link beneficiaries’ HRS data with their Medicare data 

and to conduct statistical analyses of their spending and use of services based on 

programming specifications provided by GAO. HRS, which is administered by the 

University of Michigan with support from the National Institute on Aging and the Social 

Security Administration, partners with Acumen to link Medicare beneficiaries’ HRS data to 

their Medicare data and to provide analytical support for these linked data. Total spending 

refers to Medicare’s spending per beneficiary for all covered services: durable medical 

equipment, home health, hospice, inpatient, institutional outpatient, physician and other 

noninstitutional, and skilled nursing facility. Institutional outpatient spending refers to 

Medicare’s spending per beneficiary for outpatient services provided by institutional 

providers, such as hospital outpatient departments, rural health centers, renal dialysis 

facilities, and outpatient rehabilitation facilities. Physician and other noninstitutional 

spending refers to Medicare’s spending per beneficiary for services provided by certain 

noninstitutional providers, such as physicians, clinical laboratories, and free-standing 

ambulatory surgical centers. Institutional outpatient visits refer to services provided by 

institutional providers on an outpatient basis. Physician office visits refer to services 

provided by noninstitutional providers, such as physicians. We also examined home 

health and institutional inpatient spending and hospital stays, but the number of 

beneficiaries with data for these categories was too low to provide meaningful results.
 

Page 3 GAO-14-53 Pre-Medicare Insurance Coverage

Unlike other studies, we performed our analysis for multiple groups of 

Medicare beneficiaries categorized by their length of Medicare 

enrollment. This approach enabled us to maximize the number of 

beneficiaries in our study groups and to measure the effects of prior 

continuous insurance on health status, spending, and use of services at 

several points in time after Medicare enrollment. About 4,500 HRS 

respondents met our initial criteria that they were in their first, second, 

third, fourth, fifth, or sixth year of Medicare enrollment between 2001 and 

2010 and provided information about their insurance coverage in each of 

the three consecutive HRS surveys preceding Medicare enrollment. 

Unlike some other studies on this topic that have categorized prior 

insurance based on a single point in time, we categorized beneficiaries as 

having prior continuous insurance only if they reported receiving private 

insurance in the three consecutive HRS surveys before Medicare 

enrollment at age 65—a period spanning approximately 6 years.5 We 

excluded additional respondents who were enrolled in Medicare or 

Medicaid prior to Medicare enrollment at age 65 because their enrollment 

in these programs may have been due, at least in part, to poor health, 

which could bias our results.6

Our analyses of health status relied on HRS data that were provided 

every other year. Therefore, for these analyses, we defined three distinct 

groups of beneficiaries who were in (1) their first and second years of 

Medicare, (2) their third and fourth years of Medicare, and (3) their fifth 

and sixth years of Medicare from 2001 through 2010 (see fig. 1 in app. I). 

We classified beneficiaries as being in good health or better if they 

We also excluded respondents who had

missing or incomplete data for important variables. Our final study sample 

size ranged from 3,201 to 1,152, depending on the analysis.

 

5

Approximately 80 percent of the beneficiaries in our study populations were categorized 

as having prior continuous insurance.

6

Researchers have noted that because declines in health may lead to changes in 

employment and health insurance status, there is a strong possibility of a reverse 

relationship between health and health insurance status. See Decker et al., “Health 

Service Use among the Previously Uninsured,” 1155-1168. 
 

Page 4 GAO-14-53 Pre-Medicare Insurance Coverage

reported in HRS that they were in excellent, very good, or good health.7

Our analyses of spending and use of services used Medicare data that 

were available each year. Therefore, for these analyses, we defined five 

distinct groups of beneficiaries who were in their first, second, third, 

fourth, and fifth years of enrollment between 2001 through 2010 (see 

fig. 2 in app. I). We used generalized linear models to estimate 

beneficiaries’ spending and use of services and predict values for these 

variables assuming both that they did and that they did not have prior 

continuous insurance.

We used logistic regression analysis to estimate these beneficiaries’ selfreported health status and predict probabilities of their reporting being in 

good health or better assuming both that they did and that they did not 

have prior continuous insurance.

We included the following independent variables in all of our analyses: 

prior continuous insurance, demographic characteristics (census division, 

education level, income, marital status, race, and sex), potential health 

risk factors (body mass index and smoking status), and ever having had a 

diagnosis of any of eight health conditions (arthritis, cancer, diabetes, 

heart problems, high blood pressure, lung problems, psychological 

problems, and stroke). For our analyses of spending and use of services, 

we also included a variable for the number of months a beneficiary was 

alive during the year to control for partial-year spending and use of 

services. In addition, for our spending analyses, we adjusted spending to 

calendar year 2011 constant dollars. Differences in health status, 

spending, and use of services that are discussed in the text of this report 

are based on results that were statistically significant at a 95 percent 

 

7

We chose to use the self-reported health status measure alone for its clarity of meaning 

and ease of interpretation. Some researchers have noted that beneficiaries without prior 

insurance have a higher rate of mortality than those with prior insurance—and that 

therefore mortality should be included in measures of health status. See Daniel Polsky et 

al., “Response to McWilliams Commentary: ‘Assessing the Health Effects of Medicare 

Coverage for Previously Uninsured Adults: A Matter of Life and Death?’” Health Services 

Research, vol. 45, no. 5 (October 2010). Other researchers have noted that combining the 

HRS self-reported health status measure with mortality may produce misleading results. 

See J. Michal McWilliams et al., “Commentary: Assessing the Health Effects of Medicare 

Coverage for Previously Uninsured Adults: A Matter of Life and Death?” Health Services 

Research, vol. 45, no. 5 (October 2010). We checked our sample to see if mortality was 

associated with not having prior continuous insurance and determined that there was not 

a consistent pattern and that inclusion of mortality in our health status analyses was not 

warranted.
 

Page 5 GAO-14-53 Pre-Medicare Insurance Coverage

confidence level. The tables display all of our analytical results—whether 

or not the results were statistically significant at conventional confidence 

levels—and indicate the level of statistical significance.

Our methodology had some important limitations. Because we used 

multiple exclusion criteria to define our study populations, our results 

might not be representative of the entire Medicare population. However, 

we compared certain characteristics of our study populations with those 

of the entire Medicare population and noted only small differences. In 

addition, like other researchers, we were limited in our ability to control for 

instances where individuals’ poor health led to the loss of insurance 

rather than the loss of insurance leading to poor health. To address this 

issue, we controlled for potential health risk factors and diagnoses of 

eight health conditions in all of our analyses, and we excluded 

beneficiaries who were enrolled in Medicare or Medicaid before age 65 

because their enrollment in these programs may be due, at least in part, 

to poor health. Furthermore, because HRS does not collect health 

insurance plan information, we were unable to control for variations in 

health plan benefits and coverage options in our analyses. Moreover, 

although we structured our analyses to capture as many beneficiaries as 

possible, the number of beneficiaries in our study populations may not be 

large enough to find significant differences for some variables. We

ensured the reliability of the HRS and Medicare data used in this report 

by reviewing related documentation, performing appropriate electronic 

data checks, and discussing the data with officials from Acumen, LLC. 

We found the data were sufficiently reliable for the purpose of our 

analyses. (See app. I for additional details about our scope and 

methodology.)

We conducted this performance audit from July 2011 to December 2013 

in accordance with generally accepted government auditing standards. 

Those standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

findings and conclusions based on our audit objectives. We believe that 

the evidence obtained provides a reasonable basis for our findings and 

conclusions based on our audit objectives.
 

Page 6 GAO-14-53 Pre-Medicare Insurance Coverage

Among the pre-Medicare population, the primary source of health 

insurance is private coverage. In the first half of 2012, nearly 69 percent 

of individuals in this population were privately insured. An additional 

13 percent of individuals obtained coverage through government 

programs such as Medicaid. However, a significant portion—more than 

18 percent—was uninsured.8

Previous research has demonstrated that individuals with health 

insurance coverage tend to be in better health than individuals without 

coverage.9 However, research regarding the extent to which having prior 

health insurance coverage affects spending and use of medical services 

after enrolling in Medicare has produced inconsistent results. For 

example, one group of researchers found that having prior insurance was 

linked to lower spending and lower rates of hospitalization after enrolling 

in Medicare,10 while another group of researchers found that having prior 

insurance had no effect on beneficiaries’ spending or rates of 

hospitalization after Medicare enrollment.11

 

8

Agency for Healthcare Research and Quality, Table 1: Health Insurance Coverage of the 

Civilian Noninstitutionalized Population: Percent by Type of Coverage and Selected 

Population Characteristics, United States, First Half of 2012. 

This latter group of 

researchers found, however, that beneficiaries without prior insurance 

were less likely to visit physician offices and more likely to visit hospital 

emergency and outpatient departments after enrolling in Medicare, which 

could indicate that beneficiaries without prior insurance continued to 

access the health care system differently after Medicare enrollment.

9

See Institute of Medicine, America’s Uninsured Crisis: Consequences for Health and 

Health Care (Washington, D.C.: 2009).

10See McWilliams et al., “Medicare Spending for Previously Uninsured Adults,” 757-766. 

The researchers found that adjusted annual total Medicare spending was $1,023 higher 

for beneficiaries without prior insurance ($5,796 vs. $4,773). Additionally, among relevant 

clinical subgroups, beneficiaries without prior insurance had higher adjusted annual 

hospitalization rates for complications related to cardiovascular disease or diabetes 

(9.1 percent vs. 6.4 percent) and for joint replacements (2.5 percent vs. 1.3 percent).

11See Decker et al., “Health Service Use among the Previously Uninsured,” 1155-1168. 

Although the researchers did not find statistically significant differences in Medicare 

expenditures or in the number of hospitalizations for beneficiaries with and without prior 

insurance, they found that beneficiaries without prior insurance had 16 percent fewer 

physician offices visits but 18 percent and 43 percent more hospital emergency room 

visits and outpatient department visits, respectively.

Background
 

Page 7 GAO-14-53 Pre-Medicare Insurance Coverage

Subsequent commentary and analysis by both research groups suggests 

that the conflicting results may be primarily attributable to different 

definitions of prior insurance and different analytical approaches to control 

for differences in beneficiaries with and without prior insurance.12 The 

group that found that having prior insurance was linked to lower spending 

used a more rigorous definition of prior insurance based on a longitudinal 

assessment of insurance coverage before age 65 rather than a point-intime assessment. This group included beneficiaries who were enrolled in 

Medicare, Medicaid, and other government health programs before age 

65 in its analysis and used a statistical weighting methodology to control 

for the possibility of reverse causality between health status and 

insurance coverage. More specifically, some individuals may have 

experienced declining health before age 65 that led to loss of 

employment, loss of private insurance coverage, and subsequent 

enrollment in government health programs. The group that did not find 

that having prior insurance was linked to lower spending criticized the 

inclusion of these beneficiaries, noting that many individuals transition to 

government health programs before age 65 because of poor health, 

thereby resulting in an overestimate of the effect of having prior insurance 

on their Medicare spending after age 65. These researchers also 

criticized the statistical weighting methodology used to control for the 

possibility that beneficiaries entered these programs because of poor 

health, contending that the data used in the weighting methodology were 

not sufficiently detailed to adequately adjust for this possibility.

 

12See Daniel Polsky and Sandra L. Decker, “Would Insuring Near-Elderly Persons 

Reduce Medicare Spending in Patients Aged 65 Years or Older?” Annals of Internal 

Medicine, vol. 152, no. 7 (April 2010) and J. Michael McWilliams et al., “In Response: 

Would Insuring Near-Elderly Persons Reduce Medicare Spending in Patients Aged 

65 Years or Older?” Annals of Internal Medicine, vol. 152, no. 7 (April 2010).
 

Page 8 GAO-14-53 Pre-Medicare Insurance Coverage

Beneficiaries with prior continuous insurance were more likely than those 

without prior continuous insurance to report being in good health or better 

in the 6 years after Medicare enrollment. On average, the predicted 

probability of reporting being in good health or better in the first 2 years in 

Medicare was approximately 84 percent for beneficiaries with prior 

continuous insurance and approximately 79 percent for beneficiaries 

without prior continuous insurance. Although the predicted probabilities of 

beneficiaries who reported being in good health or better decreased over 

time for both those with and without prior continuous insurance, the 

percentage point difference increased slightly. In total, having prior 

continuous insurance raised the predicted probability that a beneficiary 

reported being in good health or better by nearly 6 percentage points in 

the first 6 years after Medicare enrollment. (See table 1.)

Table 1: Predicted Probability of Beneficiaries with and without Prior Continuous Insurance for 6 Years before Medicare 

Reporting Good Health or Better in Medicare

Reporting period

Beneficiaries with prior 

continuous insurance (percent) 

Beneficiaries without prior 

continuous insurance (percent) 

Percentage point 

difference 

First and second years in Medicare 84.2%a 78.7%a 5.6a

Third and fourth years in Medicare 82.9a 77.2a 5.7a

Fifth and sixth years in Medicare 81.0a 75.1a 5.9a

Source: GAO analysis of Health and Retirement Study (HRS) data.

Notes: The table is a summary of results from three models. The models included the following 

independent variables: prior continuous insurance, demographic variables (census division, education 

level, income, marital status, race, and sex), potential health risk factors (body mass index and 

smoking status), and ever having had a diagnosis of any of eight health conditions (arthritis, cancer, 

diabetes, heart problems, high blood pressure, lung problems, psychological problems, and stroke). 

The number of beneficiaries in each group ranged from 3,201 for the first and second years in 

Medicare to 2,001 for the fifth and sixth years in Medicare.

a

Effect of prior continuous insurance significant at the .01 level.

According to previous research, there are reasons why Medicare 

beneficiaries with prior continuous insurance may be healthier than those 

without prior continuous insurance. Because of financial constraints, 

beneficiaries without prior continuous insurance may have difficulty 

accessing medical services that could help them improve their health 

before they enroll in Medicare. In addition, being uninsured before 

Medicare may have effects on beneficiaries’ health that remain for some 

time. For example, if a beneficiary without prior continuous insurance is 

diagnosed with diabetes and has inadequate access to care before 

Medicare, the beneficiary may develop complications that increase the 

risk for adverse health events for years to come, even after the diabetes 

is controlled.

Beneficiaries with 

Continuous Insurance 

before Medicare 

Were More Likely to 

Report Better Health 

after Medicare 

Enrollment than 

Those without 

Continuous Insurance
 

Page 9 GAO-14-53 Pre-Medicare Insurance Coverage

There were differences in Medicare spending and use of services 

between beneficiaries with and without prior continuous insurance. In 

particular, compared with beneficiaries without prior continuous 

insurance, beneficiaries with prior continuous insurance had significantly 

lower total spending during the first year in Medicare.13

Beneficiaries with prior continuous insurance had lower total program 

spending during the first year in Medicare compared with those without 

prior continuous insurance.14

 

13Differences in health status, spending, and use of services that are discussed in the text 

of this report are based on results that were statistically significant at a 95 percent 

confidence level. The tables display all of our analytical results—whether or not the results 

were statistically significant at conventional confidence levels—and indicate the level of

statistical significance.

Specifically, during the first year in 

Medicare, average predicted total spending for beneficiaries with and 

without prior continuous insurance was $4,390 and $6,733, respectively—

a difference of $2,343, or 35 percent. Because the difference in total 

spending was the greatest during the first year in Medicare, it is possible 

that beneficiaries without prior continuous insurance had a pent-up 

demand for medical services in anticipation of coverage at age 65. 

Table 2 shows predicted spending, as well as the difference in predicted 

spending, during the first 5 years in Medicare for beneficiaries with and 

without prior continuous insurance.

14Total spending included inpatient, institutional outpatient, durable medical equipment, 

skilled nursing facility, home health, hospice, and physician and other noninstitutional 

spending.

Beneficiaries with 

Continuous Insurance 

before Medicare Had 

Lower Program 

Spending and More 

Physician Office Visits 

after Medicare 

Enrollment than 

Those without 

Continuous Insurance

Beneficiaries with Prior 

Continuous Insurance Had 

Approximately $2,300 

Less in Estimated Total 

Spending during the First

Year in Medicare than 

Those without Prior 

Continuous Insurance
 

Page 10 GAO-14-53 Pre-Medicare Insurance Coverage

Table 2: Predicted Total Medicare Spending for Beneficiaries with and without Continuous Private Insurance for 6 Years 

before Medicare

Average predicted spending by year of Medicare enrollment (dollars)

Type of spending First year Second year Third year Fourth year Fifth year

Beneficiaries with prior continuous insurance $4,390 $5,223 $6,129 $6,093 $6,068

Beneficiaries without prior continuous insurance 6,733 6,316 7,311 5,227 6,630

Difference (2,343)a (1,093)b (1,183) 865 (562)

Source: GAO analysis of Health and Retirement Study (HRS) and Centers for Medicare & Medicaid Services (CMS) data.

Notes: The table is a summary of results from five models and compares average predicted 

spending, by year of Medicare enrollment, for beneficiaries who reported having continuous private 

insurance in the 6 years before Medicare with that for beneficiaries who reported not having 

continuous private insurance. For example, during the first year in Medicare, predicted total spending 

for beneficiaries with prior continuous insurance would be, on average, $2,343 less than for

beneficiaries without prior continuous insurance.

The models included the following independent variables: prior continuous insurance, demographic 

variables (census division, education level, income, marital status, race, and sex), potential health risk 

factors (body mass index and smoking status), the number of months a beneficiary was alive during 

the year, and ever having had a diagnosis of any of eight health conditions (arthritis, cancer, diabetes, 

heart problems, high blood pressure, lung problems, psychological problems, and stroke). The 

number of beneficiaries in each group ranged from 1,592 for the first year of enrollment to 1,152 for 

the fifth year of enrollment.

Total spending includes inpatient, institutional outpatient, durable medical equipment, skilled nursing 

facility, home health, hospice, and physician and other noninstitutional spending.

a

Effect of prior continuous insurance significant at the .01 level.

b

Effect of prior continuous insurance significant at the .10 level.

Similar to our results for total spending, beneficiaries with prior continuous 

insurance had lower institutional outpatient spending during the first and 

second years in Medicare compared with those without prior continuous 

insurance. Specifically, during the first year in Medicare, average 

predicted institutional outpatient spending was $513 (or 32 percent) less 

for beneficiaries with prior continuous insurance (see table 3). During the 

second year in Medicare, average predicted institutional outpatient 

spending was $609 (or 33 percent) less for beneficiaries with prior 

continuous insurance.
 

Page 11 GAO-14-53 Pre-Medicare Insurance Coverage

Table 3: Predicted Institutional Outpatient and Physician and Other Noninstitutional Medicare Spending for Beneficiaries with

and without Continuous Private Insurance for 6 Years before Medicare

Average predicted spending by year of Medicare enrollment (dollars)

Type of spending First year Second year Third year Fourth year Fifth year

Institutional outpatient

Beneficiaries with prior continuous insurance $1,068 $1,229 $1,354 $1,063 $1,400

Beneficiaries without prior continuous insurance 1,580 1,838 1,544 1,038 1,628

Difference (513)a (609)a (190) 26 (229)

Physician and other noninstitutionalb

Beneficiaries with prior continuous insurance 1,870 2,161 2,235 2,522 2,320

Beneficiaries without prior continuous insurance 2,251 1,944 2,071 1,934 1,808

Difference (381)c 217 163 589d 511d

Source: GAO analysis of Health and Retirement Study (HRS) and Centers for Medicare & Medicaid Services (CMS) data.

Notes: The table is a summary of results from 10 models and compares average predicted spending, 

by year of Medicare enrollment, for beneficiaries who reported having continuous private insurance in 

the 6 years before Medicare with that for beneficiaries who reported not having continuous private 

insurance. For example, during the first year in Medicare, predicted institutional outpatient spending 

for beneficiaries with prior continuous insurance would be, on average, $513 less than for

beneficiaries without prior continuous insurance.

The models included the following independent variables: prior continuous insurance, demographic 

variables (census division, education level, income, marital status, race, and sex), potential health risk 

factors (body mass index and smoking status), the number of months a beneficiary was alive during 

the year, and ever having had a diagnosis of any of eight health conditions (arthritis, cancer, diabetes, 

heart problems, high blood pressure, lung problems, psychological problems, and stroke). The 

number of beneficiaries in each group ranged from 1,592 for the first year of enrollment to 1,152 for 

the fifth year of enrollment.

a

Effect of prior continuous insurance significant at the .01 level.

b

Physician and other noninstitutional spending refers to Medicare’s per beneficiary spending for 

services provided by noninstitutional providers, such as physicians, clinical laboratories, and freestanding ambulatory surgical centers.

c

Effect of prior continuous insurance significant at the .10 level.

d

Effect of prior continuous insurance significant at the .05 level.

In contrast to our results for total spending and institutional outpatient 

spending, physician and other noninstitutional spending were similar 

during the early years in Medicare for beneficiaries with and without prior 

continuous insurance. However, during the fourth and fifth years in 

Medicare, beneficiaries with prior continuous insurance had higher 

physician and other noninstitutional spending. Specifically, during the 

fourth and fifth years in Medicare, average predicted physician and other 

noninstitutional spending was $589 (or 30 percent) and $511 (or 

28 percent) more, respectively, for beneficiaries with prior continuous 

insurance.
 

Page 12 GAO-14-53 Pre-Medicare Insurance Coverage

Beneficiaries with prior continuous insurance had more physician office 

visits during the first 5 years in Medicare than those without prior 

continuous insurance. Specifically, during the first 5 years in Medicare, 

the difference in the average predicted number of physician office visits 

between beneficiaries with and without prior continuous insurance ranged 

from 1.3 to 2.5, or 23 to 46 percent (see table 4). This utilization pattern 

may indicate that, even after Medicare enrollment, beneficiaries with prior 

continuous insurance continued to access medical services differently 

compared with those without prior continuous insurance. For example, 

beneficiaries with prior continuous insurance may have been more likely 

to have physician office visits before Medicare if their insurance covered 

these visits.

Table 4: Predicted Service Use for Beneficiaries with and without Continuous Private Insurance for 6 Years before Medicare

Average predicted number of services used by year 

of Medicare enrollment

Type of service First year Second year Third year Fourth year Fifth year

Physician office visit

Beneficiaries with prior continuous insurance 6.3 6.8 7.1 7.2 7.8

Beneficiaries without prior continuous insurance 4.9 5.4 5.8 5.3 5.4

Difference 1.4a 1.5a 1.3a 2.0a 2.5a

Institutional outpatient visit

Beneficiaries with prior continuous insurance 2.8 3.1 3.2 3.1 3.5

Beneficiaries without prior continuous insurance 2.9 3.1 3.1 3.0 3.4

Difference (0.1) (0.1) 0.1 0.2 0.0

Source: GAO analysis of Health and Retirement Study (HRS) and Centers for Medicare & Medicaid Services (CMS) data.

Notes: The table is a summary of results from 10 models and compares average predicted service 

use, by year of Medicare enrollment, for beneficiaries who reported having continuous private 

insurance in the 6 years before Medicare with that for beneficiaries who reported not having 

continuous private insurance. For example, during the first year in Medicare, the predicted number of 

physician office visits for beneficiaries with continuous insurance before Medicare would be, on 

average, 1.4 more than that of beneficiaries without continuous insurance. All values in the table are 

rounded to the nearest one-tenth.

The models included the following independent variables: prior continuous insurance, demographic 

variables (census division, education level, income, marital status, race, and sex), potential health risk 

factors (body mass index and smoking status), the number of months a beneficiary was alive during 

the year, and ever having had a diagnosis of any of eight health conditions (arthritis, cancer, diabetes, 

heart problems, high blood pressure, lung problems, psychological problems, and stroke). The 

number of beneficiaries in each group ranged from 1,592 for the first year of enrollment to 1,152 for 

the fifth year of enrollment.

a

Effect of prior continuous insurance significant at the .01 level.

Beneficiaries with Prior 

Continuous Insurance Had 

More Physician Office 

Visits during the First 

5 Years in Medicare than 

Those without Prior 

Continuous Insurance
 

Page 13 GAO-14-53 Pre-Medicare Insurance Coverage

According to our analyses, the number of institutional outpatient visits 

was similar for beneficiaries with and without prior continuous insurance. 

However, because we found that beneficiaries without prior continuous 

insurance had higher institutional outpatient spending, it is possible that 

they required more costly outpatient care than beneficiaries with prior 

continuous insurance.

Previous research regarding the extent to which health insurance 

coverage prior to Medicare enrollment affects beneficiaries’ spending and 

use of services after enrollment has been inconclusive, possibly because 

of different definitions of prior insurance and different approaches for 

dealing with the potential for reverse causality between health status and 

health insurance coverage. Like researchers who did not find significant 

differences in Medicare spending between beneficiaries with and without 

prior insurance coverage, we excluded individuals who were enrolled in 

government health programs prior to age 65 from our analysis because of 

the possibility that they lost insurance coverage because of poor health, 

which could have resulted in an overestimate of the effect of having prior 

insurance on Medicare spending after age 65. However, like researchers 

who did find significant differences in Medicare spending between these 

groups, we used a more rigorous definition of prior insurance based on a 

longitudinal assessment of insurance coverage before age 65 rather than 

a single point in time. Using our methodology, we found significant 

differences in Medicare spending between beneficiaries with and without 

prior continuous insurance.

This study adds to the body of evidence suggesting that beneficiaries with 

prior insurance used fewer or less costly medical services in Medicare 

compared with those without prior insurance, because they either were in 

better health or were accustomed to accessing medical services 

differently. In particular, we found that beneficiaries with prior continuous 

insurance were more likely than those without prior continuous insurance 

to report being in good health or better in the 6 years after Medicare 

enrollment. Additionally, we found that beneficiaries without prior 

continuous insurance had higher total and institutional outpatient 

spending but did not have higher spending for physician and other 

noninstitutional services, suggesting that they required more intensive 

medical services or that they were accustomed to visiting hospitals more 

than physician offices. This suggests that the extent to which individuals 

enroll in private insurance before age 65 has implications for 

beneficiaries’ health status and Medicare spending.

Concluding 

Observations
 

Page 14 GAO-14-53 Pre-Medicare Insurance Coverage

We provided a draft of this report to the Department of Health and Human 

Services for review. In written comments, reproduced in appendix II, the 

department highlighted a key finding in our report that beneficiaries with 

prior insurance used fewer or less costly medical services in Medicare 

compared with those without prior insurance.

As arranged with your offices, unless you publicly announce the contents 

of this report earlier, we plan no further distribution until 30 days from the 

report date. At that time, we will send copies of this report to appropriate 

congressional committees and the Administrator of the Centers for 

Medicare & Medicaid Services (CMS). The report also will be available at 

no charge on GAO’s website at http://www.gao.gov. 

If you or your staffs have any questions regarding this report, please 

contact me at (202) 512-7114 or cosgrovej@gao.gov. Contact points for 

our Offices of Congressional Relations and Public Affairs may be found 

on the last page of this report. GAO staff who made major contributions to 

this report are listed in appendix III. 

James Cosgrove

Director, Health Care

Agency Comments
Appendix I: Data and Methods

Page 15 GAO-14-53 Pre-Medicare Insurance Coverage

This appendix describes the data and methods we used to address our 

research objectives. We used data from the Health and Retirement Study 

(HRS) and Medicare claims. HRS is a longitudinal panel study that 

surveys a representative sample of more than 26,000 Americans over the 

age of 50 every 2 years.1 We used a subset of HRS data from 1996 

through 2010 to obtain information on beneficiaries’ health insurance 

coverage before Medicare, health status in Medicare, demographic 

characteristics, potential health risk factors, and diagnoses of health 

conditions. Because HRS data are survey data, these data were selfreported. We also used data from the Medicare Beneficiary Annual 

Summary Files and the Medicare Denominator Files from 2001 through 

2010 to obtain information on Medicare spending and use of services. We 

worked with Acumen, LLC, to link beneficiaries’ HRS data with their 

Medicare data and to conduct statistical analyses of their spending and 

use of services.2 We assessed the reliability of the HRS and Medicare 

data and determined that the data were adequate for our purposes. We 

conducted our work from July 2011 to December 2013 in accordance with 

generally accepted government auditing standards.

To determine whether Medicare beneficiaries had continuous health 

insurance coverage before Medicare, we used HRS data to develop a 

composite measure. We categorized beneficiaries as having prior 

continuous insurance if they reported receiving private insurance through 

their employer or their spouse’s employer in the three consecutive HRS 

surveys before Medicare enrollment at age 65—a period spanning 

approximately 6 years. To analyze beneficiaries’ health status in 

Medicare, we collapsed the HRS self-reported health status measure, 

which uses a scale from 1 (excellent) to 5 (poor), to two categories. We 

classified beneficiaries as being in good health or better if they reported 

being in excellent, very good, or good health. We also used HRS data to 

 

1

HRS is administered by the University of Michigan with support from the National Institute 

on Aging and the Social Security Administration. The RAND Center for the Study of Aging 

prepares a publicly available subset of HRS data for use by researchers.

2

HRS partners with Acumen, LLC, to link Medicare beneficiaries’ HRS data to their 

Medicare data and to provide analytical support for these linked data. Precautions were 

taken to ensure compliance with applicable confidentiality agreements with HRS.

Appendix I: Data and Methods

Data Sources

Health and Retirement 

Study
Appendix I: Data and Methods

Page 16 GAO-14-53 Pre-Medicare Insurance Coverage

develop a set of independent variables for our analyses. Specifically, we 

used data on demographic characteristics (census division, education 

level, income, marital status, race, and sex), potential health risk factors 

(body mass index and smoking status), and ever having had a diagnosis 

of any of eight health conditions (arthritis, cancer, diabetes, heart 

problem, high blood pressure, lung problem, psychological problem, and 

stroke).

To analyze beneficiaries’ spending and use of services, we used data 

from the Medicare Beneficiary Annual Summary Files. In particular, we 

obtained data on total, institutional outpatient, institutional inpatient, home 

health, and physician and other noninstitutional spending; institutional 

outpatient and physician office visits; and hospital stays.3 We also used 

enrollment data from the Beneficiary Annual Summary Files and 

Medicare Denominator Files to determine which beneficiaries to include in 

our analyses of spending and use of services.

Because we used HRS data on beneficiaries’ self-reported health status 

that were collected about every 2 years, we defined three groups of 

beneficiaries, drawn from multiple survey years spanning 2001 through 

2010, who were in (1) their first and second years of Medicare, (2) their 

third and fourth years of Medicare, and (3) their fifth and sixth years of 

Medicare (see fig. 1). This approach allowed us to measure the effect of 

prior continuous insurance on self-reported health status at three points in 

time after Medicare enrollment.

 

3

Total spending refers to Medicare’s spending per beneficiary for all covered services: 

durable medical equipment, home health, hospice, inpatient, institutional outpatient, 

physician and other noninstitutional, and skilled nursing facility. Institutional outpatient 

spending refers to Medicare’s spending per beneficiary for outpatient services provided by 

institutional providers, such as hospital outpatient departments, rural health centers, renal 

dialysis facilities, and outpatient rehabilitation facilities. Physician and other 

noninstitutional spending refers to Medicare’s spending per beneficiary for services 

provided by certain noninstitutional providers, such as physicians, independent clinical 

laboratories, and free-standing ambulatory surgical centers. Institutional outpatient visits 

refer to services provided by institutional providers on an outpatient basis. Physician office 

visits refer to services provided by noninstitutional providers, such as physicians.

Medicare Data

Study Populations

Health Status Analyses
Appendix I: Data and Methods

Page 17 GAO-14-53 Pre-Medicare Insurance Coverage

Figure 1: Study Populations for Health Status Analyses

Because we used Medicare data on beneficiaries’ program spending and 

use of services that were collected every year, we defined five groups of 

beneficiaries who were in their first, second, third, fourth, and fifth years of 

enrollment from 2001 through 2010 (see fig. 2). This approach allowed us 

to measure the effect of prior continuous insurance on spending and use 

of services for beneficiaries in each of the first 5 years of Medicare 

enrollment.

Analyses of Spending and 

Use of Services
Appendix I: Data and Methods

Page 18 GAO-14-53 Pre-Medicare Insurance Coverage

Figure 2: Study Populations for Analyses of Spending and Use of Services

For all of our analyses, we excluded beneficiaries from our study 

populations because of missing data and design and methodological 

issues. Specifically, we excluded beneficiaries who died before age 65; 

beneficiaries who were over age 65 as of January 31, 2001; beneficiaries 

who did not participate in all three HRS surveys in their pre-Medicare 

period; and beneficiaries who did not respond to relevant HRS questions 

Exclusion Criteria
Appendix I: Data and Methods

Page 19 GAO-14-53 Pre-Medicare Insurance Coverage

about insurance during their pre-Medicare period. We excluded 

beneficiaries who were enrolled in Medicare or Medicaid before age 65 

because their enrollment in these programs may have been due, at least 

in part, to poor health, which would indicate that their health status 

affected their insurance coverage rather than the other way around. We 

chose to exclude these beneficiaries to avoid overestimating the effects of 

having prior continuous insurance on health status, spending, and use of 

services. In addition, we excluded beneficiaries who reported receiving 

coverage from the Veterans Health Administration before age 65 because 

their Medicare spending and use of services might not fully represent 

their overall use of medical services.

For our analyses of spending and use of services, we applied additional 

exclusion criteria to define our study populations. We excluded Medicare 

Advantage beneficiaries because they did not have fee-for-service data 

that could be linked to HRS data.4

After the exclusions, the number of beneficiaries in our three study 

populations for our health status analyses ranged from 3,201 for the first 

group to 2,001 for the third group. The number of beneficiaries in our five 

study populations for our analyses of spending and use of services 

ranged from 1,592 for the first group to 1,152 for the fifth group.

In addition, we excluded beneficiaries 

who were not enrolled in both Medicare Parts A and B for all months they 

were alive during a given year because we did not have complete 

information on their spending and use of services.

To examine the relationship between Medicare beneficiaries’ prior 

continuous insurance and their self-reported health status, we used 

logistic regression analysis. In particular, we modeled beneficiaries’ selfreported health status during three periods after Medicare enrollment. We 

also predicted probabilities of their reporting being in good health or better 

assuming both that they did and that they did not have prior continuous 

insurance. In all of our analyses, we included the following independent 

variables: prior continuous insurance, demographic characteristics, 

 

4

About three out of four beneficiaries are enrolled in Medicare’s traditional fee-for-service 

program, and the rest are enrolled in private health plans under the Medicare Advantage 

program. Medicare fee-for-service consists of Medicare Part A, which covers hospital and 

other inpatient services, and Medicare Part B, which is optional insurance and covers 

physician, outpatient hospital, home health care, and certain other services.

Modeling Health 

Status
Appendix I: Data and Methods

Page 20 GAO-14-53 Pre-Medicare Insurance Coverage

potential health risk factors, and ever having had a diagnosis of any of 

eight health conditions. See table 5 for an example of results from one of 

the three models that we conducted for our analyses of health status. 

Table 5: Multivariate Analysis of the Effect of Prior Continuous Insurance on Self-Reported Health Status for Beneficiaries in 

Their First or Second Year of Medicare Enrollment

Variable Measure of variable Coefficient Significance level

Prior insurance coverage Continuousa 0.4590 0.0009

Not continuous (reference group) n/ab n/ab

Sex Male -0.3194 0.0049

Female (reference group) n/ab n/ab

Race White 0.2790 0.0532

Nonwhite (reference group) n/ab n/ab

Education level High school graduate 0.7699 <.0001

Not a high school graduate (reference group) n/ab n/ab

Marital status Married -0.2572 0.0566

Single (reference group) n/ab n/ab

Smoking status Smoker -0.8466 <.0001

Nonsmoker (reference group) n/ab n/ab

Body mass indexc Continuous -0.0219 0.0403

Diagnosed with diabetesd Yes -1.1175 <.0001

No (reference group) n/ab n/ab

Diagnosed with heart problemd Yes -0.8250 <.0001

No (reference group) n/ab n/ab

Diagnosed with high blood pressured Yes -0.3419 0.0028

No (reference group) n/ab n/ab

Diagnosed with stroked Yes -1.1711 <.0001

No (reference group) n/ab n/ab

Diagnosed with arthritisd Yes -0.6312 <.0001

No (reference group) n/ab n/ab

Diagnosed with cancerd Yes -0.4766 0.0036

No (reference group) n/ab n/ab

Diagnosed with lung problemd Yes -0.8484 <.0001

No (reference group) n/ab n/ab

Diagnosed with psychological problemd Yes -0.6955 <.0001

No (reference group) n/ab n/ab
Appendix I: Data and Methods

Page 21 GAO-14-53 Pre-Medicare Insurance Coverage

Variable Measure of variable Coefficient Significance level

Income quintile 1st (lowest) -1.1602 <.0001

2nd -0.7519 <.0001

3rd -0.3581 0.0548

4th -0.6174 0.0006

5th (reference group) n/ab n/ab

Census divisione New England 0.5489 0.0857

Middle Atlantic 0.5301 0.0164

East North Central 0.5788 0.0035

West North Central 0.5005 0.0395

South Atlantic 0.4725 0.0095

East South Central 0.3128 0.2091

West South Central -0.0258 0.9021

Mountain 0.2602 0.3410

Pacific (reference group) n/ab n/ab

Intercept 2.9111 <.0001

Number of observations 3,201

Source: GAO analysis of Health and Retirement Study (HRS) data.

Notes: We used logistic regression to examine the effect of having prior continuous insurance on 

beneficiaries’ self-reported health status during their first or second year of Medicare enrollment. The 

model also controlled for other variables that could affect beneficiaries’ health status. Data for all of 

the variables were from HRS. The following variables were measured as of the last HRS survey prior 

to Medicare enrollment: marital status, smoking status, body mass index, health conditions, income 

quintile, and census division.

a

We defined prior continuous insurance coverage as self-reported continuous private health 

insurance coverage during approximately 6 years before Medicare enrollment.

b

Not available because the method calculates coefficients for the included groups relative to the 

reference group.

c

Body mass index is a measure of body fat based on height and weight.

d

Respondents reported whether or not a physician ever told the respondent that he or she had a 

particular health condition.

e

Census divisions are groupings of states that subdivide the United States.
Appendix I: Data and Methods

Page 22 GAO-14-53 Pre-Medicare Insurance Coverage

To examine the relationship between Medicare beneficiaries’ prior 

continuous insurance and their spending and use of services, we used 

generalized linear models because our spending and service variables 

had skewed distributions and a high proportion of zero values.5 For 

example, for beneficiaries in their first year of Medicare enrollment, 

30 percent of beneficiaries in our study population had no institutional 

outpatient visits and therefore no institutional outpatient spending. We 

modeled total, institutional outpatient, and physician and other 

noninstitutional spending and institutional outpatient and physician office 

visits for beneficiaries in each of the first 5 years of Medicare enrollment.6

We predicted values for these variables assuming both that beneficiaries 

did and that beneficiaries did not have prior continuous insurance. In all of 

our analyses, we included the following independent variables: prior 

continuous insurance, demographic characteristics, potential health risk 

factors, ever having had a diagnosis of any of eight health conditions, and 

the number of months a beneficiary was alive during the year. For our 

spending analyses, we used the price index from the Personal Health 

Care Expenditure component of the CMS National Health Expenditure 

Accounts to express all spending in 2011 dollars. This approach adjusted 

for inflation by removing the effects of health care price-level changes 

between 2001 and 2010. See table 6 for an example of results from 1 of 

the 25 models that we ran for our analyses of spending and use of 

services. 

 

5

We used a generalized linear model with a log link function with a gamma distribution to 

model spending and a log link function with a negative binomial distribution to model 

service use.

6

We also modeled beneficiaries’ home health and institutional inpatient spending and 

hospital stays, but the number of beneficiaries with data for these categories was too low 

to provide meaningful results.

Modeling Medicare 

Spending and Use of 

Services
Appendix I: Data and Methods

Page 23 GAO-14-53 Pre-Medicare Insurance Coverage

Table 6: Multivariate Analysis of the Effect of Prior Continuous Insurance on Total Medicare Spending for Beneficiaries in 

Their First Year of Medicare Enrollment

Variable Measure of variable Coefficient Significance level

Prior insurance coverage Continuousa -0.4277 0.0002

Not continuous (reference group) n/ab n/ab

Sex Male 0.0147 0.8542

Female (reference group) n/ab n/ab

Race White 0.0317 0.7934

Nonwhite (reference group) n/ab n/ab

Education level High school graduate 0.2478 0.0401

Not a high school graduate (reference group) n/ab n/ab

Marital status Married -0.1107 0.2413

Single (reference group) n/ab n/ab

Smoking status Smoker 0.1030 0.3461

Nonsmoker (reference group) n/ab n/ab

Body mass indexc Continuous 0.0118 0.1414

Diagnosed with diabetesd Yes 0.6338 <.0001

No (reference group) n/ab n/ab

Diagnosed with heart problemd Yes 0.3159 0.0044

No (reference group) n/ab n/ab

Diagnosed with high blood pressured Yes 0.0175 0.8278

No (reference group) n/ab n/ab

Diagnosed with stroked Yes -0.3952 0.1157

No (reference group) n/ab n/ab

Diagnosed with arthritisd Yes 0.4153 <.0001

No (reference group) n/ab n/ab

Diagnosed with cancerd Yes 0.3979 0.0011

No (reference group) n/ab n/ab

Diagnosed with lung problemd Yes 0.6581 <.0001

No (reference group) n/ab n/ab

Diagnosed with psychological problemd Yes 0.2633 0.0351

No (reference group) n/ab n/ab

Income quintile 1st (lowest) -0.1330 0.3566

2nd -0.1737 0.1727

3rd -0.0723 0.5436

4th -0.1775 0.1296

5th (reference group) n/ab n/ab
Appendix I: Data and Methods

Page 24 GAO-14-53 Pre-Medicare Insurance Coverage

Variable Measure of variable Coefficient Significance level

Census divisione New England 0.0744 0.7462

Middle Atlantic 0.0215 0.9013

East North Central -0.2209 0.1467

West North Central -0.1201 0.4881

South Atlantic 0.1686 0.2438

East South Central -0.1622 0.3953

West South Central -0.4300 0.0147

Mountain -0.3703 0.1232

Pacific (reference group) n/ab n/ab

Number of months the beneficiary was alive 

during the year

1 0.6810 0.6240

2 0.3342 0.8101

3 2.6074 0.0621

4 0.3284 0.8152

5 2.1419 0.0301

6 n/af n/af

7 n/af n/af

8 0.9526 0.4951

9 n/af n/af

10 -1.0094 0.4669

11 2.0772 0.0367

12 (reference group) n/ab n/ab

Intercept 7.8474 <.0001

Number of observations 1,592

Source: GAO analysis of Health and Retirement Study (HRS) and Centers for Medicare & Medicaid Services (CMS) data.

Notes: We used a generalized linear model to examine the effect of having prior continuous 

insurance on total Medicare spending for beneficiaries in their first year of Medicare enrollment. The 

model also controlled for other variables that could affect beneficiaries’ Medicare spending. Data for 

all of the independent variables other than the number of months the beneficiary was alive during the 

year were from HRS. Data for the number of months the beneficiary was alive during the year were 

from Medicare claims. The following variables were measured as of the last HRS survey prior to 

Medicare enrollment: marital status, smoking status, body mass index, health conditions, income 

quintile, and census division.

a

We defined prior continuous insurance coverage as self-reported continuous private health 

insurance coverage during approximately 6 years before Medicare enrollment.

b

Not available because the method calculates coefficients for the included groups relative to the 

reference group.

c

Body mass index is a measure of body fat based on height and weight.

d

Respondents reported whether or not a physician ever told the respondent that he or she had a 

particular health condition.

e

Census divisions are groupings of states that subdivide the United States.

f

Not available because there were no beneficiaries alive for the corresponding number of months.
Appendix I: Data and Methods

Page 25 GAO-14-53 Pre-Medicare Insurance Coverage

Because we used multiple exclusion criteria to define our study 

populations, our results might not be representative of the entire Medicare 

population. To compare our study populations with the entire Medicare 

population, we examined certain characteristics of these populations—

gender, race, and census division (see tables 7 and 8).7 We selected 

these characteristics because data on these characteristics were 

available in each of the data sources that we used. Because we only had 

access to Medicare Denominator File data for 2003 through 2010, we 

compared characteristics for beneficiaries in their first or second year of 

Medicare enrollment from 2003 through 2010. On the basis of this 

analysis, we determined that our study populations and the entire 

Medicare population were comparable. However, we noted small 

differences between the populations. For example, compared with the 

entire Medicare population, our study populations included slightly higher 

percentages of females.

 

7

Because we could not determine which beneficiaries in the entire Medicare population 

were enrolled in Medicaid or the Veterans Health Administration before age 65, we 

compared the entire Medicare population to our study populations before we excluded 

these individuals. 

Data Reliability

Comparison with the 

Entire Medicare 

Population
Appendix I: Data and Methods

Page 26 GAO-14-53 Pre-Medicare Insurance Coverage

Table 7: Beneficiaries in Study Population for Health Status Analyses in Their First 

or Second Year of Enrollment Compared with All Medicare Beneficiaries in Their 

First or Second Year of Enrollment, 2003-2010

Characteristic

Study population 

(percent)

All Medicare beneficiaries 

(percent)

Gender

Male 41.4% 46.8% 

Female 58.6 53.2

Race

White 84.3 85.3

Nonwhite 15.7 14.7

Census division

New England 4.4 4.9

Middle Atlantic 10.9 13.6

East North Central 16.7 15.8

West North Central 9.1 7.0

South Atlantic 24.9 20.3

East South Central 6.7 6.2

West South Central 9.5 10.6

Mountain 5.7 6.9

Pacific 12.2 14.8

Source: GAO analysis of Health and Retirement Study (HRS) and Centers for Medicare & Medicaid Services (CMS) data.
Appendix I: Data and Methods

Page 27 GAO-14-53 Pre-Medicare Insurance Coverage

Table 8: Beneficiaries in Study Population for Analyses of Spending and Use of 

Services in Their First Year of Enrollment Compared with All Medicare Beneficiaries 

in Their First Year of Enrollment, 2003-2010

Characteristic

Study population 

(percent)

All Medicare beneficiaries 

(percent)

Gender

Male 40.6% 45.4% 

Female 59.4 54.6

Race

White 85.5 87.5

Nonwhite 14.5 12.5

Census division

New England 3.7 4.8

Middle Atlantic 9.3 11.5

East North Central 17.4 17.3

West North Central 9.6 7.3

South Atlantic 27.0 22.1

East South Central 7.3 7.0

West South Central 11.1 11.9

Mountain 4.4 6.5

Pacific 10.3 11.6

Source: GAO analysis of Centers for Medicare & Medicaid Services (CMS) data. 

We excluded Medicare beneficiaries who were enrolled in Medicaid 

before age 65 from our primary analyses because their enrollment in this 

program may have been due, at least in part, to poor health. To 

determine the effect, if any, of removing these beneficiaries from our 

analyses, we conducted supplementary analyses of Medicare spending 

and use of services that included these beneficiaries. Results for most of 

the dependent variables (e.g., total spending, physician and other 

noninstitutional spending, physician office visits, and institutional 

outpatient visits) were similar to our original results. However, 

beneficiaries with prior continuous insurance only had lower institutional 

outpatient spending during the first year in Medicare, rather than during 

the first and second years in Medicare, when we included these 

beneficiaries.

Supplementary Analyses
Appendix II: Comments from the Department 

of Health and Human Services

Page 28 GAO-14-53 Pre-Medicare Insurance Coverage

Appendix II: Comments from the Department 

of Health and Human Services
Appendix II: Comments from the Department 

of Health and Human Services

Page 29 GAO-14-53 Pre-Medicare Insurance Coverage
Appendix III: GAO Contact and Staff 

Acknowledgments

Page 30 GAO-14-53 Pre-Medicare Insurance Coverage

James Cosgrove, (202) 512-7114 or cosgrovej@gao.gov

In addition to the contact listed above, Christine Brudevold, Assistant 

Director; George Bogart; David Grossman; Elizabeth T. Morrison; 

Aubrey Naffis; and Eric Wedum made key contributions to this report.

Appendix III: GAO Contact and Staff 

Acknowledgments

GAO Contact

Staff 

Acknowledgments

(290933)
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