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DataWatch

Out-Of-Pocket Medical Spending For Care Of Chronic Conditions

Abstract

 
We examined out-of-pocket medical spending by persons with and without chronic conditions using data from the 1996 Medical Expenditure Panel Survey (MEPS). Our results show that mean out-of-pocket spending increased with the number of chronic conditions. The level of this spending also varied by age and insurance coverage, among other characteristics. Out-of-pocket spending for prescription drugs was substantial for both elderly and nonelderly persons with chronic conditions. As policymakers continue to use cost sharing and design of benefit packages to contain health spending, it is important to consider the impact of these policies on persons with chronic conditions and their families.

The few studies that are available have not identified the characteristics of persons with high out-of-pocket spending and have not examined the wide range of services used by persons with chronic conditions. For example, Catherine Hoffman and colleagues, using data from 1987, estimated that out-of-pocket spending made up about 22 percent of total direct medical spending for all persons with a chronic condition². However, they did not explore variations in out-of-pocket spending by individual or family characteristics. Most studies limit their analysis of out-of-pocket spending to specific chronic conditions or to specific services.³ The disease- and service-specific nature of these studies, combined with methodological and data limitations (for example, no comparison group, reliance on convenience samples), makes it difficult to generalize the results to a larger population, thus diminishing their policy relevance. In addition, approximately half of those with a chronic condition have multiple such conditions, making disease-specific studies more difficult to interpret.⁴

In this study we examine data from the 1996 Medical Expenditure Panel Survey (MEPS) to assess the impact of chronic conditions on out-of-pocket spending for individuals and families. At the individual level, we used descriptive and multiple regression analyses to examine the variation in out-of-pocket spending by number of chronic conditions and by socioeconomic factors. We also determine how out-of-pocket expenditures were distributed across different spending categories (for example, hospital, office-based visits, prescription medications). At the family level, we explore the variation in mean out-of-pocket spending and the characteristics of families with high levels of such spending.

Study Methods

Top Study Methods Study Results Summary And Policy Implications NOTES

 
Data source. Data for this study were drawn from the 1996 MEPS, a nationally representative survey sponsored by the Agency for Healthcare Research and Quality (AHRQ). The MEPS household component collected detailed information on health status, health care use and expenses, and health insurance coverage; it represents the most comprehensive, nationally representative utilization and expenditure data available.⁵ Responses from 22,326 individuals and 8,605 families were used in this analysis.

Definition of chronic condition. We defined a person as having a chronic condition if that person’s condition had lasted or was expected to last twelve or more months and resulted in functional limitations and/or the need for ongoing medical care.⁶ We selected a broad definition of chronic condition for several reasons. First, we know that almost half of persons with chronic conditions have more than one.⁷ For example, our own analysis of the MEPS data found that 77 percent of adults with diabetes, 70 percent of adults with hypertension, and 68 percent of adults with asthma had another chronic condition. Second, the consequences of health problems (such as functional limitations) are often independent of specific diseases. Although specific diagnoses are important for medical interventions, condition labels alone often provide incomplete information on morbidity, because of the wide variation in severity that exist within specific chronic conditions.⁸

To operationalize our definition of chronic condition in the context of the MEPS data set, we convened two physician panels to review all medical conditions reported by the survey sample.⁹ The panelists included five general pediatricians to review conditions of persons age nineteen and younger and five internists to review those of adults. Each physician was asked to judge whether each International Classification of Diseases, Ninth Revision (ICD-9) code as listed in the data set met the definition presented above.¹⁰ A total of 578 codes were classified; 111 were classified as chronic conditions in children and 177 as chronic conditions in adults.¹¹

To determine the number of distinct chronic conditions per person, we used a clinical classification system (CCS) already developed by AHRQ. The CCS aggregates all diagnosis codes into 259 mutually exclusive, clinically homogeneous categories.¹² These groups have been used to construct comorbidity measures to predict the use and costs of hospital services and mortality.¹³ In our analysis persons were considered to have more than one chronic condition if (1) they had more than one condition classified as chronic by our physician panels; and (2) these conditions were in separate CCS categories.¹⁴ For example, diabetes and asthma were classified as two separate chronic conditions, while spina bifida (ICD-9 code 741) and "other congenital anomalies of the nervous system" (ICD-9 code 742) were aggregated into one chronic condition (nervous system congenital anomalies). Using this approach, persons were assigned to one of four categories based on their total number of chronic conditions (0, 1, 2, 3 or more).

Out-of-pocket spending. Out-of-pocket expenditures reported in MEPS represent self-reported payments for coinsurance and deductibles, as well as cash outlays for services, supplies, and other items not covered by health insurance. Health insurance premiums, whether directly paid or withheld by employers, were not included in our analysis.¹⁵ When examined by type of service, mean out-of-pocket expenditures were calculated across persons using medical services during the year (that is, persons without any medical services use were not included in denominators).

Other variables. Persons under age sixty-five were classified into one of four mutually exclusive health insurance categories: private, Medicaid, other public insurance, and uninsured. Three insurance categories were used to classify the status of persons age sixty-five and older: Medicare only, Medicare plus private insurance, and Medicare plus Medicaid.¹⁶ Income information was translated into percentage above or below the federal poverty level.¹⁷

Study Results

Top Study Methods Study Results Summary And Policy Implications NOTES

 
Populations with chronic conditions. Based on our definition of a chronic condition, an estimated 41 percent of the noninstitutionalized U.S. population, or 108 million persons, had one or more chronic conditions in 1996. Among them, 58 percent had only one chronic condition, approximately 24 percent had two, and 18 percent had three or more. The most prevalent conditions for adults were upper respiratory infections, hypertension, nontraumatic joint disorders, diabetes, disorders of lipid metabolism, and asthma. For children, upper respiratory disease, asthma, blindness/vision defects, lower respiratory disease, and mental conditions were most frequently reported.

As expected, the prevalence of chronic conditions increased with age (Exhibit 1). Among subgroups, women were slightly more likely than men to have had a chronic condition. The gender difference persisted when the results were adjusted for age (data not shown). Among the population under age sixty-five, prevalence was lowest for those with no insurance (27.1 percent) and highest for those whose coverage was classified as "other public" (41.5 percent). Prevalence was similar for the privately insured (36.8 percent) and those covered by Medicaid (36.9 percent). Among the population age sixty-five and older, the prevalence of chronic conditions was slightly lower among persons insured by Medicare only (74.8 percent) compared with those with Medicare and private insurance (81.4 percent) or Medicare and Medicaid (79.3 percent).

The level of out-of-pocket spending also varied by type of health insurance. Among the population under age sixty-five, out-of-pocket spending was lowest for those covered by Medicaid. This is not surprising given the comprehensive nature of the Medicaid benefit package and the limits on cost sharing. Nevertheless, there was a positive association between out-of-pocket spending and chronic conditions for Medicaid beneficiaries.

Mean out-of-pocket spending was higher for the uninsured than for persons with health insurance. Further analysis revealed that despite higher out-of-pocket spending, uninsured persons were less likely to see a health care provider than were persons with insurance. Approximately 45 percent of uninsured persons without a chronic condition used no medical services during the year, compared with 16 percent of persons with private insurance. Fifteen percent of uninsured persons with at least one chronic condition and 6 percent of uninsured persons with multiple chronic conditions did not see a medical care provider, compared with fewer than 3 percent and 1 percent, respectively, of privately insured persons.

Among persons age sixty-five and older, mean out-of-pocket spending was lowest for those insured by both Medicare and Medicaid (dual eligibles). Dual eligibles spent about half as much out of pocket as other Medicare beneficiaries did. This was true for persons with or without chronic conditions. Surprisingly, mean out-of-pocket spending was only slightly lower for seniors with Medicare and private coverage than for those with Medicare only. The results were consistent regardless of number of chronic conditions.

Two separate multiple linear regression models (one for those under age sixty-five and the other for those age sixty-five and older) were constructed to confirm the relationship between out-of-pocket spending and the presence of chronic conditions while controlling for demographic characteristics and insurance status. Multivariate results confirmed the directions of the bivariate analyses and suggest that the number of chronic conditions is an important predictor of out-of-pocket spending.¹⁹

Out-of-pocket spending by type of service. For persons age sixty-five and older, mean out-of-pocket spending was highest for prescription drugs ($397), followed by dental services ($145) (Exhibit 3). For persons under age sixty-five, mean out-of-pocket spending was highest for physician office visits ($104). With the exceptions of dental services and vision aids, spending generally increased with the number of chronic conditions. Increases in mean out-of-pocket spending for prescription drugs were particularly noticeable for persons both under and over age sixty-five. Home health care was the second-highest out-of-pocket spending category when seniors had three or more chronic conditions.

Study limitations. Several possible study limitations should be mentioned. First, response and recall errors are a potential concern with survey data. Inability to recall a condition, unwillingness to reveal a condition, or errors in coding conditions also could introduce errors.²¹ Second, while MEPS separately collected information on nursing home residents, these data were not publicly available at the time of our analysis. Future research should consider out-of-pocket spending by persons residing in nursing homes and other residential facilities, since these persons are likely to be disproportionately affected by chronic conditions. Third, information was not available on direct "nonmedical" out-of-pocket costs that individuals and families with chronic conditions often encounter, such as travel expenses, clothing, home modifications, and phone bills.

Finally, in this study it is not possible to make any statements about the appropriateness of the level of out-of-pocket spending. For example, some persons may make a rational decision to pay for medical care out of pocket rather than to purchase health insurance. Therefore, they may have higher out-of-pocket spending than persons with health insurance have but lower overall spending because they have no outlays for health insurance.

Summary And Policy Implications

Top Study Methods Study Results Summary And Policy Implications NOTES

 
Findings from this study show that, on average, out-of-pocket spending on personal medical care increases as the number of chronic conditions rises. This nearly linear relationship persists even after insurance status and other demographic factors are controlled for. This suggests that the number of chronic conditions is an important predictor of out-of-pocket medical spending.

Families with chronically ill members are 2.6 times more likely than other families are to spend $1,000 out of pocket annually for medical care. Higher out-of-pocket expenditures for these persons and families are likely to persist over multiple years, given that most chronic conditions, by definition, persist over time. As a result, these individuals and families are particularly likely to be affected by changes in benefit design and coverage.

The high out-of-pocket expenses among uninsured chronically ill persons poses another potential challenge to policymakers in their efforts to improve access to health care. This study shows that among chronically ill persons the uninsured had the highest out-of-pocket spending and were five times less likely to see a medical care provider in a given year. Further research is necessary to clarify the relationship between insurance status, out-of-pocket spending, and access to care among persons with chronic conditions.

As public and private insurers continue to use cost sharing and benefit packages to reduce health care spending, it is important to consider the impact of these policies on vulnerable populations. Persons with multiple chronic conditions are particularly vulnerable to cost sharing and coverage restrictions because of their higher overall utilization and their use of specific services for which benefits are limited.

Editor's Notes

 
Wenke Hwang and Wendy Weller are assistant scientists, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health. Henry Ireys is a senior researcher at Mathematica Policy Research. Gerard Anderson is national program director of Partnership for Solutions: Better Lives for People with Chronic Conditions; professor of health policy and management and international health at the Bloomberg School of Public Health; and professor of medicine, Johns Hopkins School of Medicine.

The authors thank the following physicians, who carefully reviewed and classified diagnosis codes: Neil Powe, Tom O’Toole, Albert Wu, Claudia Steiner, Gail Daumit, Cynthia Minkovitz, Eric Levey, Renee Wachtel, Jonathan Ellen, and Larry Pakula. This work was funded by the Robert Wood Johnson Foundation.

NOTES

Top Study Methods Study Results Summary And Policy Implications NOTES

 

1. B. Altman, P.F. Cooper, and P.J. Cunningham, "The Case of Disability in the Family: Impact on Health Care Utilization and Expenditures for Nondisabled Members," Milbank Quarterly 77, no. 1 (1999): 39–75[Medline]; and E. Rasell, J. Bernstein, and K. Tang, "The Impact of Health Care Financing on Family Budgets," International Journal of Health Services 24, no. 4 (1994): 691–714.[Medline]
2. C. Hoffman, D. Rice, and H-Y. Sung, "Persons with Chronic Conditions: Their Prevalence and Costs," Journal of the American Medical Association 276, no. 18 (1996): 1473–1479.[Abstract/Free Full Text]
3. See, for example, A.M. Epstein et al., "Costs of Medical Care and Out-of-Pocket Expenditures for Persons with AIDS in the Boston Health Study," Inquiry (Summer 1995): 211–221; K. Whetten-Goldstein et al., "The Burden of Parkinson’s Disease on Society, Family, and the Individual," Journal of the American Geriatrics Society 45, no. 7 (1997): 844–849[Medline]; M. Stommel, C.W. Given, and B.A. Given, "The Cost of Cancer Home Care to Families," Cancer 71, no. 5 (1993): 1867–1874[Medline]; E.P. Steinberg et al., "Beyond Survey Data: A Claims-Based Analysis of Drug Use and Spending by the Elderly," Health Affairs (Mar/Apr 2000): 198–211; C. Mueller, C. Schur, and J. O’Connell, "Prescription Drug Spending: The Impact of Age and Chronic Disease Status," American Journal of Public Health 87, no. 10 (1997): 1626–1629[Abstract/Free Full Text]; and J. Rogowski, L. Lillard, and R. Kington, "The Financial Burden of Prescription Drug Use among Elderly Persons," Gerontologist 37, no. 4 (1997): 475–482.[Abstract]
4. Hoffman et al., "Persons with Chronic Conditions."
5. See S.B. Cohen, Sample Design of the 1996 Medical Expenditure Panel Survey Household Component, Methodology Report no. 2, Pub. no. 97-0027 (Rockville, Md.: Agency for Healthcare Research and Quality, July 1997). Although the 1996 MEPS provides the most recent, comprehensive national spending data available, it is now nearly five years old. However, we do not believe that the level or distribution of out-of-pocket spending changed dramatically between 1996 and 2001. According to the National Health Accounts, out-of-pocket spending increased 4.4 percent in 1996, 6.2 percent in 1997, and 5.5 percent in 1998, while personal health care spending increased 5.2 percent, 4.8 percent, and 5.2 percent, respectively, during the same time period. K. Levit et al., "Health Spending in 1998: Signals of Change," Health Affairs (Jan/Feb 2000): 124–132.Because managed care plans generally have lower out-of-pocket spending than fee-for-service plans have, an increase in the number of managed care enrollees could change the distribution of out-of-pocket spending. Studies suggest that persons with more health concerns are less likely to enroll in managed care than healthier persons are. The amount of out-of-pocket spending for persons with chronic conditions should remain relatively stable. Finally, more recent data sets, such as the Current Population Survey, do not contain the detailed information on out-of-pocket spending needed to conduct this type of analysis.
6. E.C. Perrin et al., "Issues Involved in the Definition and Classification of Chronic Health Conditions," Pediatrics 91, no. 4 (1993): 787–793[Abstract/Free Full Text]; R.E.K. Stein et al., "Framework for Identifying Children Who Have Chronic Conditions: The Case for a New Definition," Journal of Pediatrics 122, no. 3 (1993): 342–347[Medline]; and R.E.K. Stein, L.E. Westbrook, and L.J. Bauman, "The Questionnaire for Identifying Children with Chronic Conditions: A Measure Based on a Noncategorical Approach," Pediatrics 99, no. 4 (1997): 513–521. A more detailed description of our conceptual framework is available from Wenke Hwang, <whwang{at}hsph.edu>.[Abstract/Free Full Text]
7. Hoffman et al., "Persons with Chronic Conditions."
8. Stein et al., "The Questionnaire for Identifying Children."
9. In MEPS, medical conditions and procedures were described by respondents, recorded as verbatim text by interviewers, and then assigned a diagnosis code by professional coders. See S.R. Machlin and A.K. Taylor, Design, Methods, and Field Results of the 1996 Medical Expenditure Panel Survey Medical Provider Component, MEPS Methodology Report no. 9, Pub. no. 00-0028 (Rockville, Md.: AHRQ, May 2000).
10. Because MEPS data on an individual’s medical condition were self-reported, three-digit ICD-9 codes were used instead of the more specific five-digit codes. As a result, some diagnosis codes were broad enough to include both chronic and acute forms of a condition. In these cases, the physicians made a decision based on their clinical experience and available published literature regarding whether the majority of the cases associated with the code were chronic or acute.
11. The list of chronic conditions is available from the authors upon request.
12. See MEPS Data Documentation HC-006: 1996 Medical Conditions, Pub. no. 99-DP06 (Rockville, Md.: AHRQ, 1999).
13. A. Elixhauser et al., "Comorbidity Measures for Use with Administrative Data," Medical Care 36, no. 1 (1998): 8–27.[Medline]
14. After we classified conditions as acute or chronic, eighty-two CCS categories were identified as chronic for adults and seventy-seven for children.
15. This approach produces a measure of the financial burden on individuals and families that is directly related to their own medical care use. See G. Shearer, Hidden from View—The Growing Burden of Health Care Cost (Washington: Consumers Union, January 1998). For a detailed description of MEPS expenditure data, see MEPS HC-011: 1996 Full Year Use and Expenditure Data (Rockville, Md.: AHRQ, December 1999).
16. Persons could have been covered by more than one type of insurance in separate periods during the year or by more than one type of insurance during the same time period. Therefore, several steps were taken and decision rules were applied to assign persons to mutually exclusive insurance categories. First, we divided the population into those under age sixty-five and those age sixty-five or older. Second, we required persons to have more than six months of one type of insurance to be assigned to that insurance group. Third, when persons age sixty-five and older were covered by multiple types of insurance for more than six months during the year, they were categorized as having both types of coverage. Finally, persons under age sixty-five were classified as uninsured only if they reported having no insurance during the entire year, the approach used by the U.S. Census Bureau for identifying uninsured persons. We were unable to determine the type of insurance for approximately 2.8 percent of the population under age sixty-five (most often because they were covered by multiple types of insurance for short periods during the year); these persons were excluded from the analysis.
17. In MEPS, income of each family member was aggregated to estimate family income. Family income then was used to determine the family’s poverty status (based on family size and age of the head of family). All families were classified into one of the following five groups: poor, near-poor, low income, middle income, and high income. See MEPS HC-08: 1996 Full Year Population Characteristics (Rockville, Md.: AHRQ, December 1999).
18. Out-of pocket expenditures presented throughout this study reflect mean expenditures among persons who used medical services in 1996.
19. Because the distribution of the dependent variable was skewed, we modeled the natural logarithm of out-of-pocket expenditures. The following independent variables were included in the models: number of chronic conditions, age, sex, race, Hispanic ethnicity, insurance, and poverty status. For persons under age sixty-five, presence of chronic conditions, age, sex, race, and insurance type were all statistically significant at p <.01. The overall adjusted R-square was 0.22. For persons age sixty-five and older, sex and age were not significant, but the presence of chronic conditions and insurance type were statistically significant at p <.01, with an adjusted R-square of 0.14. Various stratified regression analyses were conducted to test possible interactions between variables. Specific results from the regression analyses (for example, parameter estimates and p-values) are available from the authors.
20. Families who have health insurance but spend more than 10 percent of their family income on out-of-pocket medical spending are considered to be underinsured. See P.F. Short and J.S. Banthin, "New Estimates of the Underinsured Younger than 65 Years," Journal of the American Medical Association 274, no. 16 (1995): 1302–1306.[Abstract/Free Full Text]
21. Hoffman et al., "Persons with Chronic Conditions."

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