PRIVATE HEALTH 

INSURANCE

Estimates of 

Individuals with 

Pre-Existing 

Conditions Range 

from 36 Million to 

122 Million

Report to Congressional Requesters

March 2012

GAO-12-439

United States Government Accountability Office

GAO
United States Government Accountability Office

Highlights of GAO-12-439, a report to 

congressional requesters

March 2012

PRIVATE HEALTH INSURANCE

Estimates of Individuals with Pre-Existing 

Conditions Range from 36 Million to 122 Million

Why GAO Did This Study

Individuals who buy coverage directly 

from a health insurer are often denied 

coverage due to a pre-existing 

condition during a process called 

medical underwriting, which assesses

an applicant’s health status and other 

risk factors. Beginning January 1, 

2014, the Patient Protection and 

Affordable Care Act (PPACA) prohibits

health insurers in the individual market 

from denying coverage, increasing 

premiums, or restricting benefits 

because of a pre-existing condition. 

GAO was asked to examine the effect 

of this provision on adults who are 19-

64 years old. GAO examined (1) the 

most common medical conditions that 

would cause an insurance company to 

restrict or deny insurance coverage for 

adults and the average annual costs 

associated with these conditions, 

(2) estimates of the number of adults 

with pre-existing conditions, and (3) the 

geographic and demographic profile of 

adults with pre-existing conditions.

To address these three issues, GAO 

(1) identified four recent studies that

narrowly or more broadly identified five 

lists of conditions likely to result in 

restricted coverage in the individual 

insurance market and (2) used the 

2009 Medical Expenditure Panel 

Survey to generate five separate 

estimates, referred to as estimates 

1 through 5. There is no commonly 

accepted list of pre-existing conditions 

because each insurer determines the

conditions it will use for medical 

underwriting. We also contacted state 

insurance department officials in all 

50 states and the District of Columbia

to confirm information about state

insurance protections that currently 

limit or prohibit medical underwriting. 

What GAO Found

Hypertension was the most commonly reported medical condition among adults 

that could result in a health insurer denying coverage, requiring higher-thanaverage premiums, or restricting coverage. GAO’s analysis found that about 33.2

million adults age 19-64 years old, or about 18 percent, reported hypertension in 

2009. Individuals with hypertension reported average annual expenditures 

related to treating the condition of $650, but maximum reported expenditures 

were $61,540. Mental health disorders and diabetes were the second and third 

most commonly reported conditions among adults. Cancer was the condition with 

the highest average annual treatment expenditures—about $9,000. 

Depending on the list of conditions used to define pre-existing conditions in each 

of the five estimates, GAO found that between 36 million and 122 million adults 

reported medical conditions that could result in a health insurer restricting 

coverage. This represents between 20 and 66 percent of the adult population, 

with a midpoint estimate of about 32 percent. The differences among the 

estimates can be attributed to the number and type of conditions included in the 

different lists of pre-existing conditions. For example, estimate 1, which is the 

lowest estimate, includes adults reporting that they had ever been told they had 

1 or more of 8 conditions. Estimate 3, the midpoint estimate, includes any 

individual reporting they had one of over 60 conditions. Estimate 5, the highest 

estimate, includes any individual reporting a chronic condition in 2009.

Estimates of Adults (Age 19 to 64) with Pre-Existing Conditions, 2009

Note: The 95 percent confidence intervals for estimates in this figure are within +/- 1 percent of the estimates themselves.

The estimated number of adults with pre-existing conditions varies by state, but 

most individuals, 88-89 percent depending on the list of pre-existing conditions 

included, live in states that do not report having insurance protections similar to 

those in PPACA. Compared to others, adults with pre-existing conditions spend 

thousands of dollars more annually on health care, but pre-existing conditions 

are common across all family income levels.

The Department of Health and Human Services reviewed a draft of this report 

and had no substantive or technical comments.

View GAO-12-439. For more information, 

contact John E. Dicken at (202) 512-7114 or 

DickenJ@gao.gov.
Page i GAO-12-439 Pre-Existing Conditions

Letter 1 

Background 6

Hypertension, Mental Health Disorders, and Diabetes Were the 

Most Commonly Reported Conditions among Adults, with 

Average Annual Expenditures for Cancer Nearly $9,000 10

Between 36 and 122 Million Adults in 2009 Reported Pre-Existing 

Conditions, Depending on the Conditions Included in the 

Estimates 12

Pre-Existing Conditions Are Common across States and 

Demographic Groups, but Prevalence Is Higher for Certain 

Populations 14

Agency Comments 26

Appendix I Scope and Methodology 29

Appendix II Number of Adults (Age 19-64) with Pre-Existing Conditions 

in States, Low, Midpoint, and High Estimate, 2009 35

Appendix III State Protections for Individuals with Pre-Existing Conditions, 

as of September 2011 37

Appendix IV Comments from the Department of Health and Human Services 39

Appendix V GAO Contact and Staff Acknowledgments 40

Tables

Table 1: Information on Studies Used to Estimate the Number of 

Adults with Pre-existing Conditions 5

Table 2: Estimates of Adults (Age 19-64) Reporting Specified 

Conditions and Average Expenditures Associated with 

Each Condition for Those with Any Expenditures, 2009 11

Table 3: Percent of Adults (Age 19-64) with Pre-Existing Conditions 

across States, Low, Midpoint, or High Estimate, 2009 16

Contents
Page ii GAO-12-439 Pre-Existing Conditions

Table 4: Percent of Adults (Age 19-64) with Pre-Existing Conditions 

within Race and Ethnicity Groups for Low, Midpoint, and 

High Estimates, 2009 21

Table 5: Distribution of All Adults (Age 19-64) and Those with PreExisting Conditions across Total Family Income 

Categories, Low, Midpoint, and High Estimates, 2009 25

Table 6: Distribution of All Adults (Age 19-64) and Those with PreExisting Conditions across Categories of Family Income as 

Percent of Poverty Level, Low, Midpoint, and High 

Estimates, 2009 26

Figures

Figure 1: Estimates of Adults (Age 19-64) with Pre-Existing Medical 

Conditions, 2009 13

Figure 2: Percent of Adults (Age 19-64) with Pre-Existing 

Conditions by Gender, for Low, Midpoint, and High 

Estimates, 2009 19

Figure 3: Percent of Adults (Age 19-64) with Pre-Existing 

Conditions within Age Groups for Low, Midpoint, and 

High Estimates, 2009 20

Figure 4: Percent of Adults (Age 19-64) with Pre-Existing 

Conditions within Insurance Coverage Groups for Low, 

Midpoint, and High Estimates, 2009 23

Figure 5: Average Annual Health Care Expenditures for Adults 

(Age 19-64) and among the Low, Midpoint, and High 

Estimates of Adults with Pre-Existing Conditions, 2009 24
Page iii GAO-12-439 Pre-Existing Conditions

Abbreviations

AHRQ Agency for Healthcare Research and Quality

FPL federal poverty level

HCERA Health Care and Education Reconciliation Act of 2010

HHS Department of Health and Human Services

HIPAA Health Insurance Portability and Accountability Act of 1998

ICD-9-CM International Classification of Diseases, Ninth Edition, 

 Clinical Modification

MEPS Medical Expenditure Panel Survey

PCIP Pre-Existing Condition Insurance Plan

PPACA Patient Protection and Affordable Care Act

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-12-439 Pre-Existing Conditions

United States Government Accountability Office

Washington, DC 20548

March 27, 2012

Congressional Requesters

Americans obtain health insurance coverage through a variety of private 

and public sources, but a majority—67 percent of adults as of 2010—rely 

on private insurance, most through employer-sponsored group coverage.

Another 16 percent of adults in 2010 had coverage through public 

programs, such as Medicare and Medicaid, and about 22 percent were 

uninsured.1,2 While group health plans and health insurers offering group 

coverage may not condition eligibility based on an individual’s health 

status, such protections generally do not exist for individuals attempting to 

purchase coverage directly through the private individual market, which 

accounted for about 14.6 million adults aged 18-64 years old in 2010.3

 

1

Medicare is a federal health care program that provides health insurance for those aged 

65 and older, certain disabled persons, and persons with end-stage renal disease. 

Medicaid is a joint federal-state program that finances health care coverage for certain 

low-income individuals.

In 

addition, individuals are at risk of losing the protections of employersponsored group coverage if they become unemployed or retire before 

eligibility for Medicare begins at age 65 and they have a break in health 

coverage. With certain exceptions, such individuals and any other 

individual attempting to purchase coverage in the private individual 

market can have coverage denied, offered at a higher-than-average 

premium, or offered with a rider that excludes coverage of a pre-existing 

condition. A pre-existing condition is a health condition that exists before 

someone applies for or enrolls in a new health insurance policy. Each 

insurer develops its own list of pre-existing conditions that influences to 

2

Percentages do not sum to 100 because estimates of coverage types are not mutually 

exclusive and individuals can have more than one type of coverage during the year. Data 

from the Census Bureau on adults is available for 18-64 year olds. See C. DeNavas-Walt, 

B.D. Proctor, and J.C. Smith, U.S. Census Bureau, Current Population Reports, P60-239, 

Income, Poverty, and Health Insurance Coverage in the United States: 2010 (Washington, 

D.C.: 2011).

3

Individuals not eligible to purchase employer-sponsored group coverage may buy 

coverage in the private individual market; these include the self-employed; those whose 

employers do not offer health insurance coverage; individuals not in the labor force; early

retirees who no longer have employment-based coverage and are not yet eligible for 

Medicare; and individuals who lose their jobs and are either ineligible for or have 

exhausted the right to continue their employer-based coverage for 18 months.

 
Page 2 GAO-12-439 Pre-Existing Conditions

whom and under what terms it offers coverage. Pre-existing conditions 

can be conditions that an individual is currently being treated for (such as 

heart disease) or past health problems (such as cancer in remission).

With the enactment of the Patient Protection and Affordable Care Act 

(PPACA) in March 2010, enrollment in private health insurance could 

expand significantly, particularly for individuals and families that do not 

have access to group coverage through their employer.4 PPACA 

provisions that could expand such coverage include income-based 

subsidies to make coverage more affordable for certain individuals, 

penalties for individuals not obtaining coverage, and new insurance 

requirements to increase access to coverage, particularly for individuals 

with pre-existing conditions. Specifically, beginning January 1, 2014, 

health insurers in the individual market will be prohibited from denying 

coverage, increasing premiums, or restricting benefits because of a preexisting condition.5

To better understand the potential impact of PPACA, you asked us to 

examine the demographics of adults with pre-existing conditions. In this 

report, we examine: (1) the most common medical conditions that would 

cause an insurance company to restrict or deny insurance coverage for 

adults and the average annual costs associated with these conditions, 

(2) estimates of the number of adults with pre-existing conditions, and 

(3) the geographic and demographic profile of adults with pre-existing 

conditions. We define adults as age 19-64 years old in this report 

because a PPACA provision prohibiting insurers from denying coverage 

or restricting benefits because of a pre-existing condition for individuals 

under the age of 19 became effective September 23, 2010, and Medicare 

covers individuals 65 and older.

 

4

Pub. L. No. 111-148, 124 Stat. 119 (Mar. 23, 2010), as amended by the Health Care and 

Education Reconciliation Act of 2010 (HCERA), Pub. L. No. 111-152, 124 Stat. 1029 

(Mar. 30, 2010). For purposes of this report, references to PPACA include the 

amendments made by HCERA.

5

Pub. L. No. 111-148, § 1201, 124 Stat. 154 (adding § 2704 to the Public Health Service 

Act (PHSA)). Although a PPACA provision prohibiting denials of coverage or restrictions 

on benefits because of a pre-existing condition for individuals under the age of 19 became 

effective September 23, 2010, insurers can still vary premium rates based on health status 

for these individuals until 2014. See Pub. L. No. 111-148 § 11253 as amended by 

§ 10103(e), 124 Stat. 162, 895.
Page 3 GAO-12-439 Pre-Existing Conditions

To address these three issues, we identified several recent studies that 

listed conditions considered likely to result in restricted coverage in the 

individual insurance market and then used the 2009 Medical Expenditure 

Panel Survey (MEPS) to analyze the conditions listed in each study in 

order to develop estimates of (1) the number of adults reporting and costs 

associated with treating specific pre-existing conditions, (2) size of the 

total affected adult population with pre-existing conditions, and (3) their 

geographic and demographic characteristics. MEPS is a commonly used, 

nationally representative, and publicly available panel survey of 

Americans; 2009 was the most recent year data were available.6 It 

includes information on medical conditions and the costs associated with 

those medical conditions, both self-reported and from a review of medical 

events.7

We identified four recent studies that used different lists of pre-existing 

conditions to develop five estimates of the number of affected individuals. 

Each of these studies identified a set of conditions that would cause an 

insurance company to deny health insurance coverage, offer coverage at 

a higher-than-average premium, or offer coverage with restrictions. The 

sets of conditions run the continuum from narrow (having one of eight 

conditions that would qualify an individual for participation in a high-risk 

pool) to broad (reporting any condition considered chronic).8,9

 

6

A panel survey involves multiple interviews with respondents over time.

Each 

insurer separately determines which conditions will result in restricted 

coverage in the individual insurance market, so lists of conditions may not 

be consistent from insurer to insurer.

7

During interviews, household respondents are asked about medical events, and after 

completing the interview (and obtaining permission), researchers contact a sample of 

medical providers by telephone to obtain information that the respondents may not be able 

to provide accurately, such as visit dates, diagnosis and procedure codes, charges, and 

payments.

8

High-risk pools are designed for individuals who cannot obtain insurance in the individual 

market because of a pre-existing condition, and therefore estimates of individuals 

potentially eligible for high-risk pools can serve as a proxy for individuals with pre-existing 

conditions.

9

A chronic condition is defined as one that lasts 12 months or longer and places limits on 

self-care, independent living, and social interactions and/or results in the need for ongoing 

intervention.
Page 4 GAO-12-439 Pre-Existing Conditions

As shown in table 1, there were important differences across the four 

studies, including the conditions and time frames considered, the 

populations that the estimates were developed for (e.g., children and 

adults under age 65, or solely the uninsured), the data sources used to 

develop the estimates, and whether the study included only individuals 

treated for a condition during a given year or individuals ever diagnosed 

with a condition. We used the set of conditions developed for each study 

to generate estimates of adults with pre-existing conditions using a 

consistent data source (2009 MEPS) and population (19-64 year olds not 

enrolled in Medicare). We assigned each condition list an estimate 

number from 1 to 5 in order to more readily identify which set of study 

conditions each estimate is based on. For example, the condition list in 

the study authored by Harold Pollack is referred to as estimate 1.
Page 5 GAO-12-439 Pre-Existing Conditions

Table 1: Information on Studies Used to Estimate the Number of Adults with Pre-existing Conditions 

Study author

Population 

studied

Estimated 

number of 

population 

studied with 

pre-existing 

conditions 

Included 

conditions 

respondent 

reported as 

occurring 

during the 

survey year

Included 

conditions 

respondent 

reported ever 

being

diagnosed with Data source Data year

Estimate 1 Harold Pollacka Uninsured of 

any age 

4.1 million No Yes National Health 

and Nutrition 

Examination 

Surveyb

2005/2006

Estimate 2c Department of 

Health and 

Human 

Servicesc

Age 0-64 50 million Yes Yes Medical 

Expenditure 

Panel Survey 

(MEPS)d

2008

Estimate 3 Families USAe Age 0-64 57.2 million Yes No MEPS 2007

Estimate 4c Department of 

Health and 

Human 

Servicesc

Age 0-64 129 million Yes Yes MEPS 2008

Estimate 5 GAOf Uninsured of 

any age in 

34 states with 

high-risk health 

insurance 

pools

4.0 million Yes No MEPS 2006

Source: GAO analysis.

Note: High-risk pools are designed for individuals who cannot obtain insurance in the individual 

market because of a pre-existing condition. Therefore, estimates of individuals potentially eligible for 

high-risk pools should be roughly equivalent to those of individuals with pre-existing conditions.

a

H. Pollack, “High-Risk Pools for the Sick and Uninsured under Health Reform: Too Little and Thus 

Too Late,” Journal of General Internal Medicine, published online Sept. 2, 2010.

b

The National Health and Nutrition Examination Survey is sponsored by the Centers for Disease 

Control and Prevention, an agency within the Department of Health and Human Services (HHS).

c

Department of Health and Human Services, “At Risk: Pre-Existing Conditions Could Affect 1 in 2 

Americans: 129 Million People Could Be Denied Affordable Coverage without Health Reform” 

(Washington, D.C.: January 2011). This study produced two separate estimates of individuals with 

pre-existing conditions based on two different condition lists.

d

The Medical Expenditure Panel Survey is sponsored by the Agency for Healthcare Research and 

Quality, an agency within HHS.

e

Families USA, “Health Reform: Help for Americans with Pre-Existing Conditions” (Washington, D.C.: 

May 2010).

f

GAO, Health Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk 

Health Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009).
Page 6 GAO-12-439 Pre-Existing Conditions

To describe the geographic and demographic profile of adults with preexisting conditions, we further analyzed data on the low, midpoint, and 

high estimates of adults with pre-existing conditions. To enable us to 

develop estimates of individuals with pre-existing conditions living in 

states reporting insurance protections similar to those that will be offered 

under PPACA in 2014, we updated information on state insurance 

protections previously reported by the Kaiser Family Foundation by 

contacting state insurance department officials in all 50 states and the 

District of Columbia. Appendix I contains a full description of our scope 

and methodology.

To assess the reliability of the MEPS data, we reviewed the relevant 

documentation, compared our estimates to other published results, and 

interviewed an official at the Agency for Healthcare Research and Quality 

(AHRQ), the federal agency responsible for the MEPS. We determined 

the data are sufficiently reliable for the purposes of our report.

We conducted this performance audit from July 2011 to March 2012 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.

Individuals who buy coverage directly from a health insurer are often 

denied coverage due to a pre-existing condition. We previously reported 

that in the first quarter of 2010, 19 percent of applicants in the individual 

market were denied enrollment and a quarter of insurers had denial rates 

of 40 percent or higher.10

 

10See GAO, Private Health Insurance: Data on Application and Coverage Denials, 

Similarly, a study by America’s Health 

Insurance Plans reported that in 2008, 15 percent of individual insurance 

applications for adults age 18 through 64 that went through medical 

GAO-11-268 (Washington, D.C.: Mar. 16, 2011). The information is based on data 

collected by Department of Health and Human Services (HHS).

Background 
Page 7 GAO-12-439 Pre-Existing Conditions

underwriting were denied coverage.11

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) 

established consumer protections on access, portability, and renewability 

of health insurance coverage.

Medical underwriting is the process 

conducted by insurers to assess an applicant’s health status and other 

risk factors to determine whether and on what terms to offer coverage to 

applicants.

12

• have had at least 18 months of prior creditable coverage with no 

break of more than 63 days;

With respect to individuals leaving group 

coverage and applying for coverage in the individual market, HIPAA 

prohibited health insurers from denying coverage to or imposing any preexisting condition exclusion on individuals who

• have exhausted any available continuation coverage;

• are uninsured and are not eligible for other group coverage, Medicare, 

or Medicaid; and

• did not lose group coverage because of the nonpayment of premiums 

or fraud.13

Unless the practice is prohibited by state law, individuals who do not meet 

these HIPAA eligibility criteria can be denied insurance coverage in the 

individual market due to a pre-existing condition. Additionally, insurers in 

the individual market can accept both HIPAA-eligible and noneligible 

 

11America’s Health Insurance Plans’ Center for Policy and Research, Individual Health 

Insurance 2009: A Comprehensive Survey of Premiums, Availability, and Benefits

(Washington, D.C.: October 2009). America’s Health Insurance Plans is the national trade 

association representing the health insurance industry. According to the study, 84 percent 

of applications were medically underwritten. Just over 1 percent of applications were 

denied before going through medical underwriting, but those denials were unrelated to the 

applicant’s health status.

12See Pub. L. No. 104-191, Title I, 110 Stat. 1936, 1939 et. seq.

13Pub. L. No.104-191, § 111, 110 Stat. 1978 (adding 2741 to the PHSA). Creditable 

coverage is defined for this purpose by §2701(c)(1) of the PHSA as coverage for an 

individual under: a group health plan, health insurance, Medicare Part A or B, Medicaid, 

TRICARE, the Indian Health Service or a tribal organization, a state health benefits highrisk pool, the Federal Employees Health Benefits Program, the Peace Corps health 

benefit plan, or a public health plan as defined in regulations. 
Page 8 GAO-12-439 Pre-Existing Conditions

applicants but offer coverage at a premium that is higher than the 

standard rate based on the presence of a pre-existing condition. A 

medical condition reported by an individual is considered a pre-existing 

condition by the insurer if it exists at the time the individual applies for 

coverage or if an individual was treated for or diagnosed with the 

condition in the past.

States, which have the responsibility for regulating private insurance, 

have in some instances required protections for individuals with preexisting conditions. State protections include the following:

• Guaranteed issue requirements prohibit the denial of coverage to 

individuals based on pre-existing conditions. In some states, all 

products must be guaranteed issue, while in other states guaranteed 

issue requirements are only applicable to some products or to some 

individuals, for instance individuals with 12 months of continuous 

coverage, or to some standard products, such as a basic health plan.

• An insurer of last resort law requires one insurer in the state to issue 

products to individuals regardless of pre-existing conditions.

• Rating restrictions prohibit insurers in the individual market from 

adjusting an individual’s health insurance premiums based on an 

individual’s health status.

• Two types of rating restrictions are pure community rating and 

adjusted community rating. Under the former, insurers may not 

adjust premiums due to health status, age, or gender; under the 

latter, they may adjust premiums according to characteristics such 

as gender or age, depending on the state.

• Rate bands limit the extent to which premiums can vary based on 

an individual’s health status, for example, to a certain percentage 

of the average premium.

• Limitations on the number of years a health insurer can look back at 

an individual’s health history when making its determination as to 

whether and at what price to offer coverage.
Page 9 GAO-12-439 Pre-Existing Conditions

• High-risk health insurance pools that provide coverage to individuals 

whose health status, including the presence of pre-existing conditions, 

limits their access to coverage in the private individual health 

insurance market.14 High-risk insurance pools—typically publicly 

subsidized, state-run nonprofit associations—often contract with a 

private health insurer to administer the pool and offer a range of 

health plan options.

Until 2014, PPACA requires that individuals who have pre-existing 

conditions and have been uninsured for 6 months be offered the 

opportunity to enroll in a temporary national high-risk pool program, 

known as the Pre-Existing Condition Insurance Plan (PCIP).15 PCIP will 

close at the end of 2013, which is when PPACA will begin to require 

insurers to accept every individual who applies for coverage, regardless 

of factors related to health status. States were given the option of running 

their own PCIP with federal funding, or allowing the Department of Health 

and Human Services (HHS) to administer the PCIP in their state. Twentyseven states elected to administer a PCIP for their residents, while 

23 states and the District of Columbia opted to allow HHS to administer 

their PCIPs. Despite similar goals, PCIP and state high-risk pools are 

separate entities and differ from one another in certain ways.16

Beginning in 2014, PPACA prohibits insurers in the private individual 

market from denying coverage, charging higher-than-average premiums, 

or restricting coverage to individuals based on the individual’s health 

status. PPACA will, therefore, make guaranteed issue and adjusted 

community rating national requirements.

 

14Thirty-five states have state high-risk pools: Alabama, Alaska, Arkansas, California, 

Colorado, Connecticut, Florida, Idaho, Indiana, Illinois, Iowa, Kansas, Kentucky, 

Louisiana, Maryland, Minnesota, Mississippi, Missouri, Montana, Nebraska, New 

Hampshire, New Mexico, North Carolina, North Dakota, Oklahoma, Oregon, South 

Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, 

and Wyoming. 

15Pub. L. No. 111-148, § 1101, 124 Stat. 141.

16See GAO, Pre-Existing Condition Insurance Plans: Program Features, Early Enrollment 

and Spending Trends, and Federal Oversight Activities, GAO-11-662 (Washington, D.C.: 

July 27, 2011).
Page 10 GAO-12-439 Pre-Existing Conditions

Hypertension was the most commonly reported medical condition among 

adults during 2009 that could result in a health insurer denying coverage, 

requiring higher-than-average premiums, or restricting coverage with an 

exclusionary rider.17 Our analysis of MEPS data found that about 

33.2 million adults age 19-64 years old, or about 18 percent, reported 

hypertension in 2009. Individuals with hypertension reported average 

annual expenditures of $650 related to treating the condition, though the 

maximum expenditures reported were $61,540.18 (See table 2.) Mental 

health disorders and diabetes were the second and third most commonly 

reported medical conditions by adults age 19-64 years old.19 About 

19.0 million adults, or 10.3 percent, reported mental health disorders, and 

about 11.9 million adults, or about 6.4 percent, reported diabetes. 

Average annual expenditures for these conditions were $1,757 for mental 

health disorders and $1,782 for diabetes. Cancer was the condition with 

the highest average annual treatment expenditures, nearly $9,000 per 

adult. Individuals may have multiple medical conditions, which would 

increase their total expenditures.

 

17Estimates are of individuals who reported that these conditions were the cause of a 

medical event, the reason for a disability day, or bothered a respondent during 2009.

18Expenditure information is reported only for those with expenditures greater than $0 and 

includes expenditures from all sources for hospital inpatient stays, emergency room visits, 

outpatient department visits, office-based medical provider visits, and prescribed 

medicines. Expenditure information does not include amounts for dental expenses and 

other medical expenses, such as durable and nondurable supplies, medical equipment, 

eyeglasses, and ambulance services because these items could not be linked to specific 

conditions. We also did not include expenditures for home health care.

19Mental health disorders are defined as mood and psychotic disorders, which include 

conditions such as depression, bipolar disorder, and schizophrenia.

Hypertension, Mental 

Health Disorders, and 

Diabetes Were the 

Most Commonly 

Reported Conditions 

among Adults, with 

Average Annual 

Expenditures for 

Cancer Nearly $9,000
Page 11 GAO-12-439 Pre-Existing Conditions

Table 2: Estimates of Adults (Age 19-64) Reporting Specified Conditions and Average Expenditures Associated with Each 

Condition for Those with Any Expenditures, 2009

Estimate 

(number)

Range based on 

95 percent 

confidence interval

Percentage 

estimate

Percentage 

range based 

on 95 percent 

confidence 

interval

Average annual 

expenditures 

related to 

condition 

(dollars)

Maximum 

expenditures 

related to 

condition 

(dollars)

Total population 184,648,891 176,372,785 – 192,924,998 100.0% — — — 

Hypertension 33,207,272 31,145,377 – 35,269,167 18.0 17.2 – 18.8 $650 $61,540

Mental health 

disordersa 18,995,244 17,516,845 – 20,473,642 10.3 9.7 – 10.9 $1,757 $98,058

Diabetes 11,899,811 11,007,195 – 12,792,427 6.4 6.0 – 6.9 $1,782 $66,007

Asthma 10,047,807 9,177,963 – 10,917,652 5.4 5.0 – 5.9 $1,234 $63,003

Arthritisb 9,518,122 8,513,144 – 10,523,099 5.2 4.7 – 5.7 $1,875 $78,617

Chronic 

obstructive 

pulmonary disease 9,091,824 8,305,480 – 9,878,167 4.9 4.5 – 5.3 $1,423c $172,583

Cancer 

(excluding skin) 4,150,263 3,588,601 – 4,711,924 2.3 2.0 – 2.5 $8,955 $294,473

Rheumatoid 

arthritis 3,041,838 2,621,846 – 3,461,831 1.7 1.4 – 1.9 $2,691 $39,228

Heart attack 

(myocardial 

infarction) 2,056,226 1,678,883 – 2,433,568 1.1 0.9 – 1.3 $4,013 $53,666

Stroke 1,291,310 1,008,677 – 1,573,943 0.7 0.6 – 0.9 $6,224c $109,324

Source: GAO analysis of Medical Expenditure Panel Survey (MEPS).

Notes: Adults are defined as individuals age 19-64. Adults with Medicare coverage were excluded. 

Estimates are of individuals who reported that these conditions were the cause of a medical event, 

the reason for a disability day, or bothered a respondent during 2009. Estimates were generated only 

for conditions with a cell size of more than 100. Expenditure information is reported only for those with 

expenditures greater than $0 and includes expenditures from all sources for hospital inpatient stays, 

emergency room visits, outpatient department visits, office-based medical provider visits, and 

prescribed medicines. Expenditure information does not include amounts for dental expenses and 

other medical expenses, such as durable and nondurable supplies, medical equipment, eyeglasses, 

and ambulance services because these items could not be linked to specific conditions. We also did 

not include expenditures for home health care.

a

Mental health disorders are defined as mood and psychotic disorders, which include conditions such 

as depression, bipolar disorder, and schizophrenia.

b

Arthritis includes osteoarthritis, rheumatoid arthritis, and infective arthritis.

c

The relative standard error is greater than or equal to 30 percent. Relative standard error is the 

proportion of the standard error divided by the estimate itself.
Page 12 GAO-12-439 Pre-Existing Conditions

The number of adults reporting specific conditions in any given year does 

not include all adults who may have had that condition in the past. For 

instance, there are many individuals who may have had cancer in the 

past who would not report cancer in a given year. Therefore, the number 

of adults who have ever had cancer is higher than the approximately 

4.2 million reporting cancer in 2009. About 11 million adults, or 

6.0 percent, reported ever being told by a health professional that they 

had cancer. Health insurers commonly look at both current medical 

conditions and conditions an individual was treated for or diagnosed with 

in the past when making a decision whether and at what price to offer 

health insurance coverage.

Depending on the list of conditions used to define pre-existing conditions 

in each of five estimates, we found that between 36 million and 

122 million adults (age 19-64) reported having medical conditions in 2009 

that could result in a health insurer denying coverage, requiring higherthan-average premiums, or restricting coverage with an exclusionary rider 

(see fig. 1). This represents from 20 to 66 percent of the adult population, 

with a midpoint estimate of 32 percent.

Between 36 and 122 

Million Adults in 2009 

Reported Pre-Existing 

Conditions, 

Depending on the 

Conditions Included 

in the Estimates
Page 13 GAO-12-439 Pre-Existing Conditions

Figure 1: Estimates of Adults (Age 19-64) with Pre-Existing Medical Conditions, 

2009

Notes: Information on the conditions included in each estimate is detailed in appendix I. Estimate 1 is 

based on the methodology in Harold Pollack’s article “High-Risk Pools for the Sick and Uninsured 

Under Health Reform: Too Little and Thus Too Late,” in the Journal of General Internal Medicine

(published online on September 2, 2010). Estimates 2 and 4 are based on the methodologies in the 

Department of Health and Human Services report “At Risk: Pre-Existing Conditions Could Affect 1 in 

2 Americans: 129 Million People Could Be Denied Affordable Coverage without Health Reform” 

(Washington, D.C.: January 2011). Estimate 3 is based on the methodology in the Families USA 

report “Health Reform: Help for Americans with Pre-Existing Conditions,” published in May 2010. 

Estimate 5 is based on the methodology used in the GAO report Health Insurance: Enrollment, 

Benefits, Funding, and Other Characteristics of State High-Risk Health Insurance Pools, 

GAO-09-730R (Washington, D.C.: July 22, 2009). The 95 percent confidence intervals for estimates 

in this figure are within +/- 1 percent of the estimates themselves.

The differences among the estimates can be attributed to the number and 

type of conditions included in the different lists of pre-existing conditions.

For example, estimate 1, which is the lowest estimate, includes adults 

reporting that they had ever been told they had 1 or more of 8 conditions. 

All 8 conditions were designated as priority conditions by AHRQ because 

of the conditions’ prevalence, expense, or relevance to policy.20

 

20The eight conditions are: angina pectoris, cancer, congestive heart failure, diabetes, 

emphysema, heart attack (myocardial infarction), other heart disease, and stroke.

 

Estimate 3, the midpoint estimate, includes any individual who had one of 
Page 14 GAO-12-439 Pre-Existing Conditions

over 60 conditions commonly used to determine eligibility in state highrisk pools. Estimate 5, the highest estimate, includes any individual 

reporting they had experienced any condition considered chronic during 

2009.21 The list of chronic conditions used for this estimate included 417 

separate conditions. See appendix I for information on the list of 

conditions included in each estimate.

The number of adults with pre-existing conditions varies by state, but 

most individuals with pre-existing conditions live in states that report not 

having insurance protections similar to PPACA. Certain groups had 

higher rates of pre-existing conditions than others, including women, 

whites, and those with public insurance. Compared to others, adults with 

pre-existing conditions spend thousands of dollars more annually on 

health care, but pre-existing conditions are common across all family 

income levels.

 

21A chronic condition is defined as a condition that lasts 12 months or longer and meets 

one or both of the following tests: (a) it places limitations on self-care, independent living, 

and social interactions; and (b) it results in the need for ongoing intervention with medical 

products, services, and special equipment. Examples of chronic conditions include 

malignancies, diabetes, most forms of mental illness, hypertension, many forms of heart 

disease, and congenital anomalies. Nonchronic conditions include conditions such as 

infections, pregnancy, many neonatal conditions, nonspecific symptoms, and injuries. We 

determined which conditions were considered chronic by using the Healthcare Cost and 

Utilization Project’s Chronic Care Indicator, which categorizes medical conditions as either 

chronic or nonchronic conditions. Out of a total of 1,019 3-digit International Classification 

of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes, we identified 417 as 

chronic conditions. ICD-9-CM is a commonly used system to classify and code medical 

conditions.

Pre-Existing 

Conditions Are 

Common across 

States and 

Demographic Groups, 

but Prevalence Is 

Higher for Certain 

Populations 
Page 15 GAO-12-439 Pre-Existing Conditions

We found that the percentage of adults with pre-existing conditions varies 

among states. We analyzed data from the 35 states where MEPS 

generated a reliable estimate.22 Our low estimate (estimate 1) ranged 

from 17 percent in New York and New Jersey to 25 percent in Ohio. For 

the midpoint estimate (estimate 3), the range was from 27 percent in 

Florida to 47 percent in Kentucky. For the high estimate (estimate 5), the 

range was from 58 percent in Georgia to 75 percent in Kentucky and 

Massachusetts. (See table 3). For population estimates for the 35 states, 

see appendix II.

 

22Due to insufficient sample sizes, MEPS data could not be used to provide estimates for 

15 states and the District of Columbia. The 15 states are Alaska, Delaware, Idaho, Maine, 

Montana, North Dakota, Nebraska, New Hampshire, New Mexico, Nevada, Rhode Island, 

South Dakota, Vermont, Wyoming, and West Virginia.

The Number of Adults with 

Pre-Existing Conditions 

Varies by State, but Most 

Adults with Pre-Existing 

Conditions Live in States 

That Report Not Having 

Insurance Protections 

Similar to PPACA
Page 16 GAO-12-439 Pre-Existing Conditions

Table 3: Percent of Adults (Age 19-64) with Pre-Existing Conditions across States, 

Low, Midpoint, or High Estimate, 2009

State 

Low:

estimate 1 

Midpoint:

estimate 3 

High:

estimate 5 

All adults 20 32 66

Alabama — — 69

Alaska — — — 

Arizona — 33 65

Arkansas — — 66

California 18 29 60

Colorado — — 68

Connecticut — — 71

Delaware — — — 

District of Columbia — — — 

Florida 18 27 60

Georgia 21 32 58

Hawaii — — 66

Idaho — — — 

Illinois 18 33 68

Indiana — 36 70

Iowa — — 74

Kansas — — 67

Kentucky — 47 75

Louisiana — — 72

Maine — — — 

Maryland — — 63

Massachusetts — 35 75

Michigan 21 41 74

Minnesota — — 64

Mississippi — — 74

Missouri — 36 70

Montana — — — 

Nebraska — — — 

Nevada — — — 

New Hampshire — — — 

New Jersey 17 30 71

New Mexico — — — 

New York 17 31 64
Page 17 GAO-12-439 Pre-Existing Conditions

State 

Low:

estimate 1 

Midpoint:

estimate 3 

High:

estimate 5 

North Carolina 21 32 63

North Dakota — — — 

Ohio 25 35 69

Oklahoma — — 61

Oregon — — 66

Pennsylvania 20 34 69

Rhode Island — — — 

South Carolina — — 60

South Dakota — — — 

Tennessee — 30 62

Texas 18 30 63

Utah — — 68

Vermont — — — 

Virginia 19 30 63

Washington — 30 71

West Virginia — — — 

Wisconsin — — 64

Wyoming — — — 

Source: GAO analysis of 2009 Medical Expenditure Panel Survey (MEPS).

Notes: Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for the 

Sick and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of General 

Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the methodology 

in the Families USA report “Health Reform: Help for Americans with Pre-Existing Conditions,” 

published in May 2010. Estimate 5 is based on the methodology used in the GAO report Health 

Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). The 95 percent confidence 

intervals for estimates in this table are within +/- 3 percent of the estimates themselves. Due to 

insufficient sample sizes, MEPS data could not be used to provide any estimates for 15 states and 

the District of Columbia. Dashes in the table indicate that the sample size was not sufficient to 

produce an estimate.

We estimate that 88-89 percent of adults with pre-existing conditions live 

in states without insurance protections similar to the PPACA provisions, 

which will become effective in 2014. We classified states as having 

protections similar to PPACA if the state reported having (1) a guaranteed 

issue requirement for some or all products in the individual insurance 

market and (2) pure or adjusted community rating.23

 

23Guaranteed issue, pure community rating, and adjusted community rating are defined 

on pages 6-7.

The only five states 
Page 18 GAO-12-439 Pre-Existing Conditions

reporting such protections are Maine, Massachusetts, New Jersey, New 

York, and Vermont.

While the majority of states do not offer protections similar to what will be 

required nationally in 2014, many states do offer some protection to 

individuals with pre-existing conditions. Insurance department officials in 

12 states reported having a guaranteed issue requirement for some or all 

products in the individual insurance market. Eight states reported either 

pure or adjusted community rating requirements. Appendix III shows the 

various state protections for individuals with pre-existing conditions in the 

50 states and the District of Columbia.

Regardless of the list of conditions used to generate the estimates, we 

found that more women reported a pre-existing condition than men. 

Based on the different definitions of pre-existing conditions we used, from 

21 to 72 percent of women reported a pre-existing condition in 2009.24

 

24Pregnancy was not considered a pre-existing condition in any of the studies we 

reviewed.

From 18 to 59 percent of men reported a pre-existing condition. The 

midpoint estimate for women and men was 37 percent and 28 percent, 

respectively. (See fig. 2.)

Pre-Existing Conditions 

Are More Common Among 

Women, Whites, and Those 

with Public Insurance
Page 19 GAO-12-439 Pre-Existing Conditions

Figure 2: Percent of Adults (Age 19-64) with Pre-Existing Conditions by Gender, for 

Low, Midpoint, and High Estimates, 2009

Note: Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for the Sick 

and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of General 

Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the methodology 

in the Families USA report “Health Reform: Help for Americans with Pre-Existing Conditions,” 

published in May 2010. Estimate 5 is based on the methodology used in the GAO report Health 

Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). Information on the conditions 

included in each estimate is detailed in appendix I. The 95 percent confidence intervals for estimates 

in this figure are within +/- 1 percent of the estimates themselves.

We found that the prevalence of pre-existing conditions among adults 

increases with age (see fig. 3). In the 55- to 64-year-old age group, from 

43 (low estimate) to 84 percent (high estimate) of adults reported a preexisting condition that would cause an insurance company to deny 

coverage, offer coverage at a higher-than-average rate, or restrict 

coverage. In contrast, from 6 percent (low estimate) to 45 percent (high 

estimate) of 19-24 year olds (the youngest age group) reported a preexisting condition. The midpoint estimate for 55-64 year olds was 

48 percent, as compared to a midpoint estimate of 19 percent for 

19-24 year olds.
Page 20 GAO-12-439 Pre-Existing Conditions

Figure 3: Percent of Adults (Age 19-64) with Pre-Existing Conditions within Age 

Groups for Low, Midpoint, and High Estimates, 2009

Note: Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for the Sick 

and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of General 

Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the methodology 

in the Families USA report “Health Reform: Help for Americans with Pre-Existing Conditions,” 

published in May 2010. Estimate 5 is based on the methodology used in the GAO report Health 

Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). Information on the conditions 

included in each estimate is detailed in appendix I. The 95 percent confidence intervals for estimates 

in this figure are within +/- 3 percent of the estimates themselves.

Asian and Pacific Islanders and Hispanics have the lowest reported rates 

of pre-existing conditions in each estimate, significantly lower than the 

rate seen across all adults. For example, for the midpoint estimate, 

15 percent of Asian and Pacific Islanders reported a pre-existing 

condition, compared to 32 percent of all adults. In two of three estimates 

(the low and high estimates), white adults are slightly more likely to report 

a pre-existing condition than the adult population as a whole. This 

difference was statistically significant, but the difference was not 

statistically significant for the midpoint estimate. (See table 4.)
Page 21 GAO-12-439 Pre-Existing Conditions

Table 4: Percent of Adults (Age 19-64) with Pre-Existing Conditions within Race and 

Ethnicity Groups for Low, Midpoint, and High Estimates, 2009

Low:

estimate 1

(percentage)

Midpoint:

estimate 3 

(percentage)

High:

estimate 5

(percentage)

All adults 20 32 66

Asian/Pacific Islander, non-Hispanic 11 15 52

Hispanic 13 26 51

Black, non-Hispanic 19 34 59

White, non-Hispanic 22 35 72

Other, non-Hispanica b 42 67

Source: GAO analysis of Medical Expenditure Panel Survey (MEPS).

Notes: Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for the 

Sick and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of General 

Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the methodology 

in the Families USA report “Health Reform: Help for Americans with Pre-Existing Conditions,” 

published in May 2010. Estimate 5 is based on the methodology used in the GAO report Health 

Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). Information on the conditions 

included in each estimate is detailed in appendix I. The 95 percent confidence intervals for estimates 

in this table are within +/- 6 percent of the estimates themselves.

a

Other, non-Hispanic includes American Indians, Alaskan Natives, and individuals identifying with 

multiple, non-Hispanic races.

b

Sample size was insufficient to generate a reliable estimate.

Compared to individuals with other types of insurance coverage, 

uninsured adults and those with private individual insurance have the 

lowest reported rates of pre-existing conditions (see fig. 4). The lower 

reporting of pre-existing conditions among the uninsured, in part, may 

reflect the fact that they are less likely than the insured to receive timely 

preventive care and some common health problems such as 

hypertension and diabetes often go undetected without routine checkups. 

In addition, the uninsured are also less likely to have regular preventive 

care, including cancer screenings. The lower reporting of pre-existing 

conditions among those with private individual insurance may be a 

reflection of the fact that insurers try to limit the number of people with 

pre-existing conditions that they accept into their plan.25

 

25Due to insufficient sample sizes, we were only able to generate an estimate of 

individuals in the private individual market reporting pre-existing conditions for the high 

estimate (estimate 5).

The greatest 

protections for individuals with pre-existing conditions exist in employer-
Page 22 GAO-12-439 Pre-Existing Conditions

sponsored group insurance and public insurance programs, which are the 

groups that reported the highest rates of pre-existing conditions.26 As 

noted previously, group insurance plans are not allowed to deny 

insurance coverage or increase an individual’s premiums based on health 

status. Such protections may encourage individuals in employer group 

coverage or government insurance to maintain their coverage should they 

be diagnosed with certain medical conditions. We recently reported that 

research has consistently found that after a health diagnosis, workers 

with employer-sponsored coverage were less likely to leave a job or 

reduce their hours compared to workers who did not rely on their 

employer for health coverage.27

 

26Public insurance programs include Medicaid and military health coverage. For the 

purposes of our report, we excluded individuals with Medicare from our analysis.

27GAO, Health Care Coverage: Job Lock and the Potential Impact of the Patient 

Protection and Affordable Care Act, GAO-12-166R (Washington, D.C.: Dec. 15, 2011).
Page 23 GAO-12-439 Pre-Existing Conditions

Figure 4: Percent of Adults (Age 19-64) with Pre-Existing Conditions within 

Insurance Coverage Groups for Low, Midpoint, and High Estimates, 2009

Note: Public insurance category includes Medicaid and military health coverage. Estimate 1 is based 

on the methodology in Harold Pollack’s article “High-Risk Pools for the Sick and Uninsured Under 

Health Reform: Too Little and Thus Too Late,” in the Journal of General Internal Medicine (published 

online on September 2, 2010). Estimate 3 is based on the methodology in the Families USA report 

“Health Reform: Help for Americans with Pre-Existing Conditions,” published in May 2010. Estimate 5 

is based on the methodology used in the GAO report Health Insurance: Enrollment, Benefits, 

Funding, and Other Characteristics of State High-Risk Health Insurance Pools, GAO-09-730R

(Washington, D.C.: July 22, 2009). Estimates are provided only where there was sufficient sample 

size to generate a reliable estimate. The 95 percent confidence intervals for estimates in this figure 

are within +/- 7 percent of the estimates themselves.

a

Only the high estimate for individuals with private, individual insurance had sufficient sample size to 

generate a reliable estimate.
Page 24 GAO-12-439 Pre-Existing Conditions

Adults with pre-existing conditions, on average, spend thousands of 

dollars more for all health care—between $1,504 and $4,844 more per 

year—than other adults. Based on the set of conditions included in 

estimate 1, which included the smallest number of individuals with preexisting conditions, average annual health care expenditures were $8,535 

in 2009, compared to $3,691 for all adults (see fig. 5).28

Figure 5: Average Annual Health Care Expenditures for Adults (Age 19-64) and among the Low, Midpoint, and High Estimates 

of Adults with Pre-Existing Conditions, 2009

The average 

expenditures for the midpoint estimate (estimate 3) were $7,296 and the 

average expenditures for the high estimate (estimate 5) were $5,195. 

Average medical expenditures among those with pre-existing conditions 

decreased as the number of people in the estimate reporting a preexisting condition increased. As more individuals are included in the 

estimate, it is likely that the average severity of the medical conditions 

decreases, thus decreasing the average expenditure estimate.

Note: Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for the Sick 

and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of General 

Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the methodology 

in the Families USA report “Health Reform: Help for Americans with Pre-Existing Conditions,” 

published in May 2010. Estimate 5 is based on the methodology used in the GAO report Health 

Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). Information on the conditions 

included in each estimate is detailed in appendix I. The 95 percent confidence intervals for estimates 

in this figure are within +/- 8 percent of the estimates themselves.

 

28Annual expenditures on health care included expenditures on any medical condition 

during the year. Individuals with pre-existing conditions can have multiple medical 

conditions.

Adults with Pre-Existing 

Conditions Spend 

Thousands of Dollars More 

Per Year on Health Care 

Than Other Adults, but 

Pre-Existing Conditions 

Are Common across All 

Family Income Levels
Page 25 GAO-12-439 Pre-Existing Conditions

The distribution of adults across income groups, whether measured by 

total family income or income as a share of the federal poverty level, is 

similar, regardless of pre-existing condition status (see tables 5 and 6). 

We found that the average annual family income for adults with preexisting conditions was between $64,000 and $71,000, as compared to 

the average family income of all adults, which is about $69,000.

Table 5: Distribution of All Adults (Age 19-64) and Those with Pre-Existing 

Conditions across Total Family Income Categories, Low, Midpoint, and High 

Estimates, 2009

Adults with pre-existing conditions 

(percentage)

All adults 

(percentage)

Low:

estimate 1

Midpoint:

estimate 3

High:

estimate 5

Under $25,000 21 25 25 21

$25,000-$49,999 24 23 24 23

$50,000-$74,999 19 18 18 19

$75,000-$99,999 14 14 14 14 

$100,000 and above 22 21 19 23

Total 100 100 100 100

Source: GAO analysis of Medical Expenditure Panel Survey (MEPS).

Notes: Income includes annual earnings from wages salaries and other sources including: bonuses, 

tips, child support payments, Social Security, worker’s compensation, veterans’ payments, and 

welfare payments from public assistance and related programs. It does not include tax refunds and 

capital gains. Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for 

the Sick and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of 

General Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the 

methodology in the Families USA report “Health Reform: Help for Americans with Pre-Existing 

Conditions,” published in May 2010. Estimate 5 is based on the methodology used in the GAO report 

Health Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). Total may be greater than 

100 percent because of rounding. The 95 percent confidence intervals for estimates in this table are 

within +/- 2 percent of the estimates themselves.
Page 26 GAO-12-439 Pre-Existing Conditions

Table 6: Distribution of All Adults (Age 19-64) and Those with Pre-Existing 

Conditions across Categories of Family Income as Percent of Poverty Level, Low, 

Midpoint, and High Estimates, 2009 

Adults with pre-existing conditions 

(percentage)

Income as a percentage 

of FPL

All Adults 

(percentage)

Low:

estimate 1

Midpoint: 

estimate 3

High:

estimate 5

Less than100% 13 15 15 12

100 to 199% 16 16 17 15

200 to 399% 30 28 30 29

Greater than or equal to 400% 41 42 38 44

Total 100 100 100 100

Source: GAO analysis of Medical Expenditure Panel Survey (MEPS).

Notes: Income includes annual earnings from wages salaries and other sources including: bonuses, 

tips, child support payments, Social Security, worker’s compensation, veterans’ payments, and 

welfare payments from public assistance and related programs. It does not include tax refunds and 

capital gains. Estimate 1 is based on the methodology in Harold Pollack’s article “High-Risk Pools for 

the Sick and Uninsured Under Health Reform: Too Little and Thus Too Late,” in the Journal of 

General Internal Medicine (published online on September 2, 2010). Estimate 3 is based on the 

methodology in the Families USA report “Health Reform: Help for Americans with Pre-Existing 

Conditions,” published in May 2010. Estimate 5 is based on the methodology used in the GAO report 

Health Insurance: Enrollment, Benefits, Funding, and Other Characteristics of State High-Risk Health 

Insurance Pools, GAO-09-730R (Washington, D.C.: July 22, 2009). Total may be greater than 

100 percent because of rounding. The 95 percent confidence intervals for estimates in this table are 

within +/- 2 percent of the estimates themselves.

We provided a draft of this report to HHS for comment, but in its written 

response HHS said that it had no substantive or technical comments. 

HHS noted that PPACA provided individuals with pre-existing conditions 

new protections, including the opportunity to enroll in the Pre-existing 

Condition Insurance Plan and the prohibition on insurers limiting or 

denying insurance coverage because of a pre-existing condition 

beginning in 2014. HHS’s letter is included as appendix IV.

As agreed 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 to the Secretary of Health 

and Human Services, the Administrator of the Centers for Medicare & 

Medicaid Services, and other interested parties. In addition, the report will 

be available at no charge on the GAO website at http://www.gao.gov. 

Agency Comments
Page 27 GAO-12-439 Pre-Existing Conditions

If you or your staff have any questions about this report, please contact 

me at (202) 512-7114 or dickenj@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 key contributions to this report 

are listed in appendix V.

John E. Dicken

Director, Health Care
Page 28 GAO-12-439 Pre-Existing Conditions

List of Requesters

The Honorable Harry Reid

Majority Leader

United States Senate

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 John D. Rockefeller IV

Chairman

Subcommittee on Health Care

Committee on Finance

United States Senate
Appendix I: Scope and Methodology

Page 29 GAO-12-439 Pre-Existing Conditions

To answer all of our research objectives, we (1) identified different sets of 

medical conditions that researchers have used to define the conditions 

that would cause an insurance company to deny health insurance 

coverage, offer coverage at higher-than-average premiums, or restrict 

health insurance coverage; and (2) analyzed data from the 2009 Medical 

Expenditure Panel Survey (MEPS). We chose the MEPS because it is 

nationally representative of the civilian, noninstitutionalized population, 

provides information on medical conditions, medical expenditures, and 

demographics, and has been used by other researchers to answer similar 

research objectives.1 We limited our analysis to adults, defined as 

individuals age 19 to 64, and we excluded approximately 2.7 million 

adults continuously enrolled in Medicare in all 12 months of 2009. Based 

on Medicare eligibility rules, all of these individuals would have a medical 

condition.

We identified four previous studies that used different lists of pre-existing 

conditions to develop five estimates of the number of individuals with preexisting conditions or the number of individuals potentially eligible for 

high-risk pools. Because high-risk pools are designed for individuals who 

cannot obtain insurance in the private individual market because of a preexisting condition, estimates of individuals potentially eligible for high-risk 

pools can serve as a proxy for individuals with pre-existing conditions. 

Each of the previous studies looked at different populations, used 

different years of data, and, in one case, a different source of data. We 

assigned each condition list an estimate number from 1 to 5 in order to 

more readily identify which set of conditions was associated with each 

estimate.2

Estimate 1 is based on the condition list in Harold Pollack’s article “HighRisk Pools for the Sick and Uninsured Under Health Reform: Too Little 

and Thus Too Late,” in the Journal of General Internal Medicine

(published online on September 2, 2010). Pollack considered individuals 

For example, the condition list in the study authored by Harold 

Pollack is referred to as estimate 1.

 

1

During interviews, household respondents are asked about medical events, and after 

completing the interview (and obtaining permission), researchers contact a sample of 

medical providers by telephone to obtain information that the respondents may not be able 

to provide accurately, such as visit dates, diagnosis and procedure codes, charges, and 

payments.

2

One study made both a low and high estimate.

Appendix I: Scope and Methodology

Identifying Pre-Existing 

Conditions 
Appendix I: Scope and Methodology

Page 30 GAO-12-439 Pre-Existing Conditions

to be plausible high-risk pool participants if they had ever been told they 

had emphysema, diabetes, stroke, cancer, congestive heart failure, heart 

disease, angina, or heart attack.

Estimate 2 is described below with the information on estimate 4 

because both estimates came from the same study. Additionally, 

estimate 2 is based on the methodology used in estimate 3.

Estimate 3 is based on the condition list in the Families USA report 

“Health Reform: Help for Americans with Pre-Existing Conditions,” 

published in May 2010. According to a methodology developed by 

researchers from The Lewin Group, individuals were identified as having 

a pre-existing condition if they reported, in the previous year, one of 67 

conditions most commonly included in lists for determining high-risk pool 

eligibility across all the states with high-risk pools. The conditions were: 

acquired immune deficiency syndrome (AIDS), alcohol/drug 

abuse/chemical dependency, Alzheimer’s disease, angina pectoris, 

anorexia nervosa, aplastic anemia, aortic aneurysm, arteriosclerosis 

obliterans, artificial heart valve/heart valve replacement, ascites, brain 

tumor, cancer (except skin), cancer (metastatic), cardiomyopathy/primary 

cardiomyopathy, cerebral palsy/palsy, chronic obstructive pulmonary 

disease (COPD), chronic pancreatitis, cirrhosis of the liver, congestive 

heart failure, coronary artery disease, coronary insufficiency, coronary 

occlusion, Crohn’s disease, cystic fibrosis, dermatomyositis, diabetes, 

emphysema/pulmonary emphysema, Friedreich’s disease/ataxia, 

hemophilia, hepatitis, HIV positive, Hodgkin’s disease, Huntington’s 

chorea/disease, hydrocephalus, intermittent claudication, kidney 

failure/kidney disease with dialysis/renal failure, lead poisoning with 

cerebral involvement, leukemia, Lou Gehrig’s disease/amytrophic lateral 

sclerosis/ALS, lupus erythematosus disseminate/lupus, major organ 

transplant, malignant tumor, mood and psychotic disorders (including 

depression, schizophrenia, and bipolar disorder), motor or sensory 

aphasia, multiple or disseminated sclerosis, muscular atrophy or 

dystrophy, myasthenia gravis, myocardial infarction (heart attack), 

myotonia, obesity, paraplegia or quadriplegia, Parkinson’s disease, 

peripheral arteriosclerosis, polyarteritis, polycystic kidney, postero-lateral 

sclerosis, rheumatoid arthritis, sickle cell anemia/sickle cell disease, 

silicosis, splenic anemia/True Banti’s Syndrome/Banti’s disease, Still’s 

disease, stroke, syringomyelia (spina bifida or myelomeningocele), tabes 

dorsalis, thalassemia (Cooley’s or Mediterranean anemia), ulcerative 

colitis, and Wilson’s disease.
Appendix I: Scope and Methodology

Page 31 GAO-12-439 Pre-Existing Conditions

Estimates 2 and 4 were based on the two condition lists in the 

Department of Health and Human Services’ (HHS) report “At Risk: PreExisting Conditions Could Affect 1 in 2 Americans: 129 Million People 

Could Be Denied Affordable Coverage Without Health Reform” 

(Washington, D.C.: January 2011). This report included two estimates of 

individuals with pre-existing conditions. Estimate 2 replicated the 

methodology developed by The Lewin Group for the Families USA study 

with two exceptions. First, obesity was not included in the list of 

conditions that would cause a denial because HHS researchers did not 

find obesity on the condition lists used by state high-risk pools. Second, 

HHS included individuals who reported that they had ever been 

diagnosed with the following conditions: coronary heart disease, 

myocardial infarction, other heart disease, angina pectoris, stroke, 

emphysema, cancer, and diabetes. HHS’s second estimate, estimate 4, 

included the same conditions as its first estimate with additional 

conditions added based on a review of the underwriting guidelines of 

seven health insurers. In addition to the conditions included in estimate 2, 

estimate 4 included individuals reporting arthritis, asthma, high 

cholesterol, hypertension, or obesity, as well as those who had ever been 

diagnosed with arthritis, asthma, high cholesterol, or hypertension.

Estimate 4 also includes individuals reporting neurotic and related 

disorders, stress and adjustment disorders, conduct disorders, and 

emotional disturbances.

Estimate 5 was based on the methodology used in the GAO report 

Health Insurance: Enrollment, Benefits, Funding, and Other 

Characteristics of State High-Risk Health Insurance Pools, GAO-09-730R

(Washington, D.C.: July 22, 2009). This report used the Healthcare Cost 

and Utilization Project’s Chronic Condition Indicator to identify chronic 

conditions in the 2006 MEPS, which were assumed to make a person 

medically uninsurable and therefore potentially eligible for a state highrisk pool. The Chronic Condition Indicator categorizes all International 

Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) 

codes as chronic or not chronic.3

 

3

ICD-9-CM is a commonly used system to classify and code medical conditions. The 

Chronic Condition Indicator is one in a family of databases and software tools developed 

as part of the Healthcare Cost and Utilization Project, a federal-state-industry partnership 

sponsored by the Agency for Healthcare Research and Quality.

A chronic condition is defined as a 

condition that lasts 12 months or longer and meets one or both of the 

following tests: (a) it places limitations on self-care, independent living, 
Appendix I: Scope and Methodology

Page 32 GAO-12-439 Pre-Existing Conditions

and social interactions; and (b) it results in the need for ongoing 

intervention with medical products, services, and special equipment. 

Individuals reporting any condition considered chronic were included in 

this estimate. We used the three-digit ICD-9-CM codes for medical 

conditions. Of 1,019 three-digit ICD-9-CM codes, the Chronic Condition 

Indicator categorized 417 as chronic.

To standardize the estimates from the different sources, we applied the 

conditions identified by each study to the same population (19 to 64 year 

olds not enrolled in Medicare) and the same year and source of data (the 

2009 MEPS) to construct estimates 1 through 5.

To estimate the number of adults (age 19 to 64) with medical conditions 

that would cause an insurance company to restrict or deny insurance 

coverage and the average expenditures related to these conditions, we 

analyzed MEPS data on medical conditions and expenditures. We 

reported data only for those medical conditions included in at least one of 

the condition lists used for estimates 1 through 5. MEPS respondents 

report medical conditions identified as the reason for a medical event, the 

reason for a disability day, or as something that is “bothering” the 

respondent during the reference year (in this case, 2009).4

We defined expenditures as payments from all sources for hospital 

inpatient care, ambulatory care provided in offices and hospital outpatient 

departments, care provided in emergency departments, and the purchase 

To protect 

respondent privacy, we only reported estimates based on sample sizes of 

100 or more.

 

4

For MEPS, medical conditions were recorded by an interviewer as verbatim text, which 

was then coded by professional coders to five-digit International Statistical Classification 

of Diseases, Ninth Revision codes (ICD-9). ICD-9 codes are a commonly used set of 

codes used to classify medical conditions. The five-digit ICD-9 codes were then 

aggregated into clinically meaningful categories that group similar conditions, known as 

Clinical Classification codes. In addition, MEPS includes the ICD-9 code, but truncates it 

to three-digits to protect the confidentiality of survey participants. When possible, we used 

the Clinical Classification codes in our analysis. When a medical condition did not align 

with the conditions noted with the Clinical Classification codes, we used the three-digit 

ICD-9 code to identify individuals with the condition. 

Identifying the Most 

Common Medical 

Conditions and Estimating 

Treatment Costs
Appendix I: Scope and Methodology

Page 33 GAO-12-439 Pre-Existing Conditions

of prescribed medications.5 We did not include expenditures for dental 

expenses or other medical expenses, such as durable and nondurable 

supplies, medical equipment, eyeglasses, and ambulance services 

because these items could not be linked to specific conditions. We also 

excluded expenses for home health care. We classified expenditures with 

a condition if a visit, stay, or medication purchase was cited as being 

related to the specific condition.

To describe the demographic and geographic profile of adults with preexisting conditions we focused on the low, midpoint, and high estimates 

of adults with pre-existing conditions, which we call estimates 1, 3, and 5, 

respectively. We provided state estimates for the 35 states with sufficient 

sample size in the MEPS data to reliably report an estimate. We did not 

have large enough sample sizes to generate state-level estimates of the 

number of adults with pre-existing conditions in Alaska, Delaware, Idaho, 

Maine, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North 

Dakota, Rhode Island, South Dakota, Vermont, West Virginia, Wyoming, 

and the District of Columbia.

To estimate the number of individuals living in states with insurance 

protections similar to those that will be offered under PPACA in 2014, we 

surveyed state insurance department officials in September 2011, asking 

them to confirm or correct information on guaranteed issue requirements 

and rating restrictions previously reported by the Kaiser Family 

Foundation’s statehealthfacts.org website.6

 

5

Sources of payment include direct payments from individuals, private insurance, 

Medicare, Medicaid, Workers’ Compensation, and miscellaneous other sources. 

Payments for over-the-counter drugs are not included in MEPS total expenditures. Indirect 

payments not related to specific medical events are also excluded.

We asked the state officials to 

confirm information on guaranteed issue requirements and rating 

restrictions in place as of September 2011. We received responses from 

all states and the District of Columbia. Based on those responses, we 

used MEPS’s state-based estimates of adults age 19 to 64 with preexisting conditions to identify the number of individuals living in states 

reporting a guaranteed issue requirement for at least some policies and 

either pure community rating or adjusted community rating—insurance 

6

The Kaiser Family Foundation indicated that the information on this website was 

collected by the Center for Health Insurance Studies, Georgetown University Health Policy 

Institute and was current as of January 2011.

Demographic and 

Geographic Profile of 

Adults with Pre-Existing 

Conditions 
Appendix I: Scope and Methodology

Page 34 GAO-12-439 Pre-Existing Conditions

protections similar to those that will be offered under PPACA in 2014. 

Guaranteed issue requirements prohibit the denial of coverage to 

individuals based on pre-existing conditions. In some states, all products 

must be guaranteed issue, while in other states guaranteed issue 

requirements are only applicable to some individuals, for instance those 

with 12 months of continuous coverage, or some standard product, such 

as a basic health plan. Under pure community rating, insurers may not 

adjust premiums based on health status, age, or gender. Under adjusted 

community rating, insurers may not adjust premiums based on health 

status, but may adjust premiums based on characteristics such as gender 

or age, depending on the state.

There are limitations to our analysis. First, each insurance company 

separately determines which medical conditions will result in a denial, 

limitation in coverage, or an increase in premiums. An individual who may 

be denied by one insurer could obtain coverage from another. Therefore, 

the population of individuals who would be denied by an insurer, offered 

restricted coverage, or offered coverage at higher-than-average 

premiums actually varies by each health insurer. Second, our estimates 

could overstate the adult population with pre-existing conditions because 

of the way in which conditions are aggregated in the MEPS database. To 

protect survey participant confidentiality, five-digit ICD-9-CM codes are 

truncated into a three-digit code, which means that individuals reporting 

other related conditions may also be captured.

To determine the reliability of the MEPS data, we reviewed related 

documentation, compared our estimates to other published results, and 

spoke with an official from the Agency for Healthcare Research and 

Quality, which is the federal agency responsible for MEPS. We 

determined that the MEPS data were sufficiently reliable for the purposes 

of our engagement. The 2009 data are the most recently available for 

MEPS. We conducted this performance audit in accordance with 

generally accepted government auditing standards from July 2011 

through March 2012. 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 based on our audit objectives.

Study Limitations and Data 

Reliability
Appendix II: Number of Adults (Age 19-64) with 

Pre-Existing Conditions in States, Low, 

Midpoint, and High Estimate, 2009

Page 35 GAO-12-439 Pre-Existing Conditions

Low: estimate 1 Midpoint: estimate 3 High: estimate 5

State Number Standard error Number Standard error Number Standard error

All adults 36,116,647 1,056,380 59,978,301 1,734,242 121,560,174 2,950,667

Alabama — — — — 1,936,170a 692,379

Alaska — — — — — — 

Arizona — — 1,136,752 304,102 2,216,186 501,837

Arkansas — — — — 1,480,153a 755,180

California 4,004,774 511,259 6,606,715 857,916 13,651,336 1,435,726

Colorado — — — — 1,893,776a 590,540

Connecticut — — — — 1,211,605a 618,166

Delaware — — — — — — 

District of Columbia — — — — — — 

Florida 1,670,935 255,058 2,612,694 384,664 5,689,120 906,300

Georgia 1,215,469 136,640 1,898,146 211,029 3,461,859 301,183

Hawaii — — — — 683,798a 348,877

Idaho — — — — — — 

Illinois 1,179,171 159,490 2,181,909 343,397 4,488,169 575,415

Indiana — — 1,358,572 233,200 2,623,593 408,833

Iowa — — — — 1,597,729 349,209

Kansas — — — — 1,047,433a 534,405

Kentucky — — 2,186,644a 1,058,849 3,527,324a 1,699,657

Louisiana — — — — 1,436,715a 590,999

Maine — — — — — — 

Maryland — — — — 2,161,840 370,581

Massachusetts — — 1,097,055 271,483 2,311,677 550,103

Michigan 1,226,779 221,142 2,453,149 495,322 4,390,757 888,570

Minnesota — — — — 2,333,096 347,476

Mississippi — — — — 1,432,693a 730,966

Missouri — — 1,407,053 210,782 2,736,950 444,142

Montana — — — — — — 

Nebraska — — — — — — 

Nevada — — — — — — 

New Hampshire — — — — — — 

New Jersey 1,055,825 142,155 1,914,939 293,777 4,474,967 690,321

New Mexico — — — — — — 

New York 1,952,701 524,780 3,580,631 876,213 7,308,236 1,725,171

Appendix II: Number of Adults (Age 19-64) 

with Pre-Existing Conditions in States, Low, 

Midpoint, and High Estimate, 2009
Appendix II: Number of Adults (Age 19-64) with 

Pre-Existing Conditions in States, Low, 

Midpoint, and High Estimate, 2009

Page 36 GAO-12-439 Pre-Existing Conditions

Low: estimate 1 Midpoint: estimate 3 High: estimate 5

State Number Standard error Number Standard error Number Standard error

North Carolina 1,131,189a 553,188 1,746,407a 891,024 3,426,132a 1,748,027

North Dakota — — — — — — 

Ohio 1,758,412 358,372 2,523,454 540,527 4,945,135 837,152

Oklahoma — — — — 1,230,321a 627,715

Oregon — — — — 2,008,453a 867,185

Pennsylvania 1,628,060 139,301 2,777,003 271,756 5,546,111 583,727

Rhode Island — — — — — — 

South Carolina — — — — 1,324,442a 675,736

South Dakota — — — — — — 

Tennessee — — 772,781a 394,276 1,625,348a 829,259

Texas 2,673,379 378,510 4,366,855 619,441 9,045,432 1,483,132

Utah — — — — 1,736,201a 885,817

Vermont — — — — — — 

Virginia 1,160,804a 380,094 1,895,256 541,223 3,968,986 1,137,964

Washington — — 1,509,783 328,015 3,542,050 736,548

West Virginia — — — — — — 

Wisconsin — — — — 2,319,211a 834,253

Wyoming — — — — — — 

Source: GAO analysis of Medical Expenditure Panel Survey (MEPS).

Notes: Information on the conditions included in each estimate is detailed in appendix I. Estimate 1 is 

based on the methodology in Harold Pollack’s article “High-Risk Pools for the Sick and Uninsured 

Under Health Reform: Too Little and Thus Too Late,” in the Journal of General Internal Medicine

(published online on September 2, 2010). Estimate 3 is based on the methodology in the Families 

USA report “Health Reform: Help for Americans with Pre-Existing Conditions,” published in May 2010. 

Estimate 5 is based on the methodology used in the GAO report Health Insurance: Enrollment, 

Benefits, Funding, and Other Characteristics of State High-Risk Health Insurance Pools, 

GAO-09-730R (Washington, D.C.: July 22, 2009). The standard error is a measure of variation 

around the estimate, in this case, the estimated number of individuals in the state with pre-existing 

conditions. The 95 percent confidence intervals for estimates in this table are within +/- 3 percent of 

the estimates themselves. Due to insufficient sample sizes, MEPS data could not be used to provide 

any estimates for 15 states and Washington, D.C. Dashes in the table indicate that the sample size 

was not sufficient to produce an estimate.

a

The relative standard error is greater than or equal to 30 percent. Relative standard error is the 

proportion of the standard error divided by the estimate itself.
Appendix III: State Protections for Individuals 

with Pre-Existing Conditions, as of September 

2011

Page 37 GAO-12-439 Pre-Existing Conditions

State 

Guaranteed 

issuea 

Insurer of last 

resortb Pure community ratingc Adjusted community ratingd Rate bandse

Alabama No No No No No

Alaska No No No No No

Arizona Yes - Some No No No No

Arkansas No No No No No

California No No No No No

Colorado No No No No No

Connecticut No No No No No

Delaware No No No No No

District of Columbia No No No No No

Florida No No No No No

Georgia No No No No No

Hawaii No No No No No

Idaho Yes - Some No No No Yes

Illinois No No No No No

Indiana No No No No No

Iowa No No No No Yes

Kansas No No No No No

Kentucky No No No No Yes

Louisiana No No No Nof Yes

Maine Yes - All No No Yes No

Maryland No No No No Yes

Massachusetts Yes – All No No Yes No

Michigan Yes – Some No No No No

Minnesota No No No No Yes

Mississippi No No No No No

Missouri No No No No No

Montana No No No No No

Nebraska No No No No No

Nevada No No No No Yes

New Hampshire No No No No Yes

New Jersey Yes – All Nog No Yes No

New Mexico No No No No Yes

New York Yes – All No Yes No No

North Carolina No No No No No

North Dakota No No No No No

Appendix III: State Protections for 

Individuals with Pre-Existing Conditions, as 

of September 2011
Appendix III: State Protections for Individuals 

with Pre-Existing Conditions, as of September 

2011

Page 38 GAO-12-439 Pre-Existing Conditions

State 

Guaranteed 

issuea

 

Insurer of last 

resortb Pure community ratingc Adjusted community ratingd Rate bandse

Ohio Yes – Some No No No Noh

Oklahoma No No No No No

Oregon No No No Yes No

Pennsylvania No Yes No Yes No

Rhode Island Yes – Some Yes No No No

South Carolina No No No No No

South Dakota No No No No Yes

Tennessee No No No No Yes

Texas No No No No No

Utah Yes – Some No No No Yes

Vermont Yes – All No No Yes No

Virginia No Yes No No No

Washington No No No Yes No

West Virginia Yes – Some No No No No

Wisconsin No No No No No

Wyoming No No No No No

Source: GAO survey of state officials pertaining to categories of protection previously reported on by the Kaiser Family Foundation.

Note: We did not attempt to independently identify categories of protection or to validate the accuracy 

of the state responses.

a

Guaranteed issue requirements prohibit the denial of coverage to individuals based on pre-existing 

conditions. In some states, all products must be guaranteed issue, while in other states guaranteed 

issue requirements are only applicable to some individuals, for instance those with 12 months of 

creditable coverage, or some standard product, such as a basic health plan.

b

An insurer of last resort law requires one insurer in the state to issue products to individuals 

regardless of pre-existing conditions.

c

Under pure community rating, insurers may not adjust premiums due to health status, age, or 

gender.

d

Under adjusted community rating, insurers may not adjust premiums due to health status, but may 

adjust premiums according to characteristics such as gender or age, depending on the state.

e

Rate bands limit the extent to which premium can vary based on an individual’s health status, for 

example, to a certain percentage of the average premium.

f

Louisiana reported that its community modified rating law allows for limited rate variation 

between member participants for health status, tier rating, and durational rating. It also allows rating 

for age, gender, industry, geographic area, family composition, group size, tobacco usage, plan of 

benefits, or other factors approved by the Louisiana Department of Insurance.

g

While New Jersey reported that it has an insurer of last resort by law, it does not function as such in 

practice because of the guaranteed issue requirement.

h

Rating bands only apply in parts of the individual market where a small group plan is being converted 

to an individual plan.
Appendix IV: Comments from the Department 

of Health and Human Services

Page 39 GAO-12-439 Pre-Existing Conditions

Appendix IV: Comments from the 

Department of Health and Human Services
Appendix V: GAO Contact and Staff 

Acknowledgments

Page 40 GAO-12-439 Pre-Existing Conditions

John E. Dicken, (202) 512-7114 or DickenJ@gao.gov

In addition to the contact named above, Walter Ochinko, Assistant 

Director; Lori Achman; George Bogart; Sean DeBlieck; Giselle Hicks; and 

Laurie Pachter made key contributions to this report.

Appendix V: GAO Contact and Staff 

Acknowledgments 

GAO Contact

Staff 

Acknowledgments: 

(290958)
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