- Email: [email protected]
Health care expenditures among working-age adults with physical disabilities: Variations by disability spans
Disability and Health Journal 6 (2013) 287e296 www.disabilityandhealthjnl.com
Research Paper
Health care expenditures among working-age adults with physical disabilities: Variations by disability spans Chaiporn Pumkam, Ph.D.a,*, Janice C. Probst, Ph.D.a, Kevin J. Bennett, Ph.D.b, James Hardin, Ph.D.c, and Sudha Xirasagar, Ph.D.a a
Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, 800 Sumter Street, SC 29208, USA b Department of Family and Preventive Medicine, University of South Carolina School of Medicine, Columbia, SC 29203, USA c Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
Abstract Background: Data on health care costs for working-age adults with physical disabilities are sparse and the dynamic nature of disability is not captured. Objectives: To assess the effect of 3 types of disability status (persistent disability, temporary disability, and no disability) on health care expenditures, out-of-pocket (OOP) spending, and financial burden. Methods: Data from Medical Expenditure Panel Survey panel 12 (2007e2008) were used. Respondents were classified into 3 groups. Medians of average annual expenditures, OOP expenditures, and financial ratios were weighted. The package R was used for quantile regression analyses. Results: Fifteen percent of the working-age population reported persistent disabilities and 7% had temporary disabilities. The persistent disability group had the greatest unadjusted annual medians for total expenditures ($4234), OOP expenses ($591), and financial burden ratios (1.59), followed by the temporary disability group ($1612, $388, 0.71 respectively). The persistent disability group paid approximately 15% of total health care expenditures out-of-pocket, while the temporary disability group and the no disability group each paid 22% out-of-pocket. After adjusting for other factors, quantile regression shows that the persistent disability group had significantly higher total expenditures, OOP expenses, and financial burden ratios (coefficients 1664, 156, 0.58 respectively) relative to the no disability group at the 50th percentile. Results for the temporary disability group show a similar trend except for OOP expenses. Conclusions: People who have disabling conditions for a longer period have better financial protection against OOP health care expenses but face greater financial burdens because of their higher out-of-pocket expenditures and their socioeconomic disadvantages. Ó 2013 Elsevier Inc. All rights reserved. Keywords: Disability; Expenditures; Working-age; Disparities
In 2010, about 36 million (12%) Americans of all ages living in the community reported a disability, including 10% of adults aged 18e64 and 37% of adults over 65 years of age.1 While disability rates increase with age, given the large number of working-age persons in the population, most persons with disability are working-age adults. Adults aged 18e64 constitute more than 52% of the total disabled population.1 No conflicts of interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The abstract was selected for oral presentation during the 140th APHA Annual Meeting (October 27e31, 2012) in San Francisco, CA, USA. * Corresponding author. Tel.: þ1 803 777 1627. E-mail address: [email protected] or [email protected] (C. Pumkam). 1936-6574/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.dhjo.2013.03.002
Costs of disabilities among working-age adults are substantial. In 2008, US government spending for assistance to working-age adults with disabilities was $357 billion, approximately 12% of all federal expenditures.2 Health care and income maintenance each accounted for more than 47%of the federal spending for workingage people with disabilities.2 These economic burdens continue to rise, putting both private and public sectors at financial risk.3 This can lead to the declines in spending on other governmental programs (e.g., employment, housing, and food assistance programs) for supporting disabled people as to compensate for the increase in health care costs. Disability can result from injury, aging, or chronic diseases such as arthritis, asthma, obesity, back and joint problems, and cardiovascular disease.4e6 In addition, the
288
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
presence of a disabling condition places people at increased risk for one or more secondary conditions such as diabetes and cardiovascular disease.7e9 Disabling and secondary conditions require people with disabilities to make greater use of health care than the general population,7,10e13 resulting in higher health care expenditures, out-of-pocket (OOP) spending, and financial burden compared with people without disabilities.14 In general, disabled people experience higher rates of poverty, unemployment, lower educational attainment, and inadequate health insurance coverage.15 Several policy initiatives at the federal and state levels seek to improve access to care and protect people with disabilities against considerable financial risk. Two principal income support benefits, the Supplemental Security Income (SSI) program and Social Security Disability Insurance (SSDI) program provide a safety net for disabled people. These two programs interact with other programs such as health insurance programs (i.e., Medicare and Medicaid), employmentrelated programs (i.e., Unemployment Insurance (UI) and Workers’ Compensation (WC)), Supplemental Nutrition Assistance Program (SNAP), and Temporary Assistance for Needy Families (TANF).16 Over time, laws have been enacted to expand health care coverage to persons with preexisting conditions. These include the Ticket to Work and Work Incentives Improvement Act (TWWIA) of 1999, which allows Medicaid buy-in for disabled persons whose income would otherwise disqualify them; the Health Insurance Portability and Accountability Act (HIPAA), which guarantees the portability of insurance regardless of preexisting conditions; the Consolidated Omnibus Budget Reconciliation Act (COBRA), which requires continued coverage for 29 months for disabled individuals; and the Patient Protection and Affordable Care Act (PPACA) of 2010. Improvements overtime in legislation and these public health programs are anticipated to reduce outof-pocket spending and financial burden among adults with disabilities. Several studies have examined health care costs for the elderly and children with disabilities, but data for working-age adults with disabilities are sparse. In 1996, the mean health care expenditure for people with disabilities was $2489, compared to $420 for those without disabilities.17 In 2004, the average total health care expenditure and the financial burden (the percentage of family income spent on total out-of-pocket (OOP) spending) among adults aged 21e61 years with disabilities was about 5 times those of adults without disabilities, while the OOP spending for the disabled adults was 3 times that for their nondisabled counterparts.14 These prior studies, however, did not examine health care expenditures, OOP spending, and financial burden across service categories (inpatient, outpatient, emergency department, or prescription medications). Further, previous studies on expenditures among people
with disabilities have not distinguished between shortterm and long-term disability. Differences in duration of disability may differently affect health care needs, expenditures, and governmental income benefits. For example, individuals who are permanently disabled may qualify for SSDI and, after receiving SSDI for 2 years, become eligible for Medicare. Temporarily disabled individuals, however, may pay a higher share of their health care expenditures out-of-pocket and face a higher financial burden due to inadequate financial protection. Thus, the present research aims to investigate the effect of the 3 types of physical disability status (persistent disability, temporary disability, and no disability) on health care expenditures, OOP spending, and financial burden community-dwelling working-age adults. Methods Data source and sample Data were drawn from Medical Expenditure Panel Survey (MEPS) panel 12 (2007e2008), a nationally representative survey of health care use, expenditures, sources of payment, and health insurance coverage for the US civilian, noninstitutionalized population, cosponsored by Agency for Healthcare Research and Quality (AHRQ) and the National Center for Health Statistics. The MEPS is a panel survey, with 5 rounds of interviews covering 2 full years. Study data primarily came from the Household Component, which collects person-level information about demographic characteristics, health conditions, health status, use of medical services, charges and sources of payments, access to care, satisfaction, health insurance coverage, income, and employment. MEPS uses a multistage sampling design that accounts for clustering, stratification, oversampling, and nonresponse. This enables generation of unbiased national estimates.18 The sample was limited to adults between 18 and 64 years of age with data for both years of the survey, all 5 rounds (N 5 6764). Variables Independent variable: definition of disability We conceptualized disability according to the International Classification of Functioning, Disability and Health (ICF) framework endorsed by the World Health Organization.19 The ICF framework classifies disability into 3 levels: physical and mental impairment, activity limitations, and participation restrictions. Disability is considered the outcome of a dynamic interaction between health conditions and contextual factors including external environmental factors (e.g., social attitudes and social structures) and internal personal factors (e.g., gender, age, education, and behavior patterns). Paralleling previous work,20 we used the MEPS ANYLIM variable to identify disability status. The MEPS
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
defines any limitation (ANYLIM) as reporting any functional, activity, and/or sensory limitation in any survey round within 1 year. Disability is deemed present if a respondent meets any one of the following criteria: (1) requiring help or supervision with at least one ADL (activity of daily living) or IADL (instrumental activity of daily living); (2) having difficulty in performing certain specific physical actions (e.g., bending, lifting, or stooping); (3) having any limitation in work, housework, or school; and (4) having difficulty seeing (with glasses or contacts, if used) or hearing (with a hearing aid, if used).21 We limited our study population to those with physical impairments; persons with mental disorders were excluded. To capture change in disability status, we classified respondents into 1 of 3 groups: persistent disability, temporary disability, and without disability. Disability was considered persistent if the respondent reported any limitation in both years. Disability was considered temporary if individuals reported any limitation in the first year (2007) of the survey and not the other, while individuals who reported no limitation in both years were categorized as nondisabled.
Dependent variables Expenditures. Total health care expenditures and expenditures for outpatient visits, inpatient stays, emergency room visits, and medication prescriptions were calculated by summing payments for care provided in 2007e2008. The sum of expenditures over both years for each respondent was then divided by 2 to generate average annual expenditures per person. MEPS expenditures include out-of-pocket payments and payments paid by third party payers including private insurance, Medicaid, Medicare, and other sources. Expenditures for over-the-counter medications, alternative care services, and phone contracts with medical providers are not included.22 For this study, hospital outpatient and officebased visit expenditures associated with physician and nonphysician visits as well as expenditures for 0-night stays were combined into a single outpatient service category. Inpatient expenditures included the total expenses for hospital stays minus expenses associated with 0-night stays. Expenditures for dental, home health, vision aids, and other medical service categories were not examined because these service expenditures accounted for less than 20% of the total expenditures. The total expenditures values reported do include these categories. Out-of-pocket spending on health care. Out-of-pocket expenditures, paid by an individual or family, were summed over the 2 years and averaged to generate average annual service OOP spending and total OOP spending. In MEPS, OOP expenditures are self-reported payments for coinsurance, copayments, deductibles, and medically related items and services not covered by insurance.22 Paralleling
289
23,24
previous studies, this measure does not include health insurance premiums, because premiums are a constant value that does not change with health services use. Financial burden (out-of-pocket spending burden). Health care financial burden was defined as the ratio of OOP spending over total family income, expressed as a percentage. Family income was derived by summing incomes across family members. Person-level income included annual earnings, business and farm gains and losses, unemployment and workers’ compensation, interest and dividends, child support, private pensions, IRA withdrawals, social security, veterans payments, supplemental security income and cash welfare payments from public assistance, related programs and other income.25 Financial burden ratios were calculated for the 4 service categories and total health care services and averaged over the 2 years. One dollar was added to respondents’ family incomes when 0 family income was reported. To reduce the impact of extreme cases, these ratios were top-coded at 100%.23 Additional independent variables were selected according to Anderson’s model of health services use.26 Predisposing characteristics included: sex, age group (18e44 vs. 45e64 years), race (white, nonwhite), marital status (married, windowed/divorced/separated, and never married), geographic region (Northeast, Midwest, South, and West), place of residence (urban vs. rural), education (no degree, a high school diploma or general education diploma (GED), a bachelor’s degree or more than a high school degree or a graduate degree such as M.A. or Ph.D.), and family size (living alone, 2, >3). The enabling characteristics included: employment status (employed vs. unemployed), insurance status and type (private insurance, public insurance, uninsured), having a usual source of care (yes vs. no), and poverty status/household income (poor/ near poor, low income, middle income, or high income). Lastly, health needs included self-reported health status (very good/excellent, good, and fair/poor) and comorbidities (expressed as having 0, 1, 2, >3 conditions). The comorbidity conditions included cancer, hypertension, diabetes, acute myocardial infarction (AMI), coronary heart disease, angina, stroke, rheumatoid arthritis, asthma, and emphysema.27 Statistical approach Descriptive analyses were performed using SASCallable SUDAAN 9.2 statistical software to account for the complex sampling design of MEPS.21 Differences in characteristics across the 3 disability types were tested using Wald Chi-square tests. Medians of average annual expenditures, OOP expenditures, and ratios for each service category and the total services, subdivided by disability status were generated. All median estimates for expenditures, OOP expenses, and ratios were weighted to provide national estimates. Median estimates then were compared
290
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Table 1 Demographic characteristics of working-age adults, by disability status Characteristics Total Persistent disability Observations Weighted observations Predisposing characteristics Race/ethnicity White Nonwhite Gendera Male Female Age groupa 18e44 45e64 Marital statusa Married Widow/divorced/separated Never married Educationa No degree High school Bachelor/post high school/graduate school Enabling characteristics Employment statusa Employed Unemployed Household incomea Poor/near poor Low income Middle income High income Insurance statusa Any private Public only Uninsured Usual source of carea Yes No Geographic locationa Northeast Midwest South West Residencea Urban Rural Perceived health needs Self-reported health statusa Excellent/very good Good Fair/poor Chronic conditionsa No comorbidity 1 comorbidity 2 comorbidity >3 comorbidity a b c
6764 (100%) 176 060 374
1016 (14.8%) 26 067 388
Temporary disability
No disability
454 (6.9%) 12 114 217
5294 (78.3%) 137 878 769
p valuea
0.3079 80.5 19.5
81.9 18.1
82.2 17.8
80.1 19.9
49.5 50.5
44.8b,c 55.2b,c
56.2b 43.8b
49.7 50.3
58.7 41.3
30.2b,c 69.8b,c
43.6b 56.4b
65.4 34.6
55.6 15.3 29.1
45.9b,c 31.3b,c 22.8b
56.0 23.0b 21.0b
57.4 11.6 31.0
15.4 49.1 35.5
20.6b, 53.0c 26.4b,c
14.9 43.9 41.2
14.5 48.8 36.8
77.2 22.8
49.4b,c 50.6b,c
75.6b 24.4b
82.5 17.5
14.4 13.2 33.0 39.5
26.7b,c 15.3 31.7 26.3b,c
17.5b 13.4 33.7 35.4
11.8 12.8 33.1 42.3
71.6 9.8 18.5
56.4b,c 28.7b,c 14.9b
72.6 9.8 17.5
74.4 6.2 19.3
72.0 28.0
82.3b,c 17.7b,c
73.6 26.4
69.9 30.1
18.6 21.9 36.1 23.5
14.9 25.8 37.9 21.3
16.8 19.6 41.0 22.6
19.4 21.3 35.3 24.0
84.6 15.4
81.0 19.0
80.1 19.9
85.7 14.3
62.8 25.7 11.5
24.0b,c 32.7b 43.3b,c
54.8b 30.3b 14.9b
70.9 23.9 5.2
58.6 23.7 10.2 7.4
24.2b,c 24.7 21.1b 30.0b,c
44.0b 29.7b 16.1b 10.2b
66.4 23.0 7.7 2.9
0.0008
!0.0001 !0.0001
!0.0001
!0.0001 !0.0001
!0.0001
!0.0001
0.0339
0.0197
!0.0001
!0.0001
Significant differences in proportions for each characteristic across the 3 disability types, p ! 0.05. Significantly different from the no disability group, p ! 0.05. Significantly different from the temporary disability group, p ! 0.05.
across the 3 disability types using quantile regression analysis and considered significantly different if their 95% confidence intervals did not overlap.
The distribution of health care expenditures typically is skewed to the right, because a small proportion of people experience extreme costs, leading to inappropriate means
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
and large standard errors. Previous analyses of health care expenditures used ordinary least squares (OLS) regression analyses of the mean expenditure and the logarithmic transformation to normalize skewed data and stabilize variances.28e30 However, linear regression of log transformed expenditures models the expected mean of the log expenditures, rather than the log of the expected mean. Back transformation without the application of bias correction factors results in biased estimates of expenditures and inaccurate effect size of selected variables on expenditures.30 Furthermore, OLS is unable to capture how variable the effect of each selected factor can be across the distribution. Thus, quantile regression is considered appropriate for data with heavily skewed distributions. Quantile regression allows the intercept and slope coefficients to vary across quantiles rather than constant slopes assumed by OLS.31 A more comprehensive picture of the effect of selected variables on the outcome variable at specific or all percentiles can then be detected. We applied quantile regression analyses to examine the effect of the 3 disability types on the outcomes of interest: average annual total health care expenditures, total out-ofpocket spending, and financial burden. We estimated the 10th, 50th, and 90th percentile of the dependent variables, conditional on the independent variables. The main independent variable of interest was disability status (persistent disability, temporary disability, and no disability). Adjusted coefficient estimates at 10th, 50th and 90th percentiles were presented. The statistical software package ‘‘R’’ version 2.12.2 was used to perform quantile regression analyses for the survey data.32 Statistical significance for all analyses in this study was defined as p ! 0.05 unless explicitly noted. Results Prevalence of disability Among working-age adults surveyed in 2007e2008, 15% reported a disability in both years of the survey period (persistent disability) and approximately 7% reported a disability in the first year of the 2 years (temporary disability). The distribution of the population by disability status across socio-demographic and health categories is provided in Table 1. Across disability types, temporarily disabled adults were more similar to the nondisabled population than to permanently disabled adults, in ways that might affect the financial burden of care. For example, similar proportions of the temporarily disabled and the nondisabled respondents reported private insurance coverage (73% and 74%, respectively), vs. 56.4% among the persistently disabled. Similarly, the proportion of the temporarily disabled and nondisabled adults who were poor or near poor were slightly different (17.5% and 11.8%, respectively), while disabled adults were markedly more likely than either of the other groups to experience poverty (26.7%).
291
Health care expenditures Table 2 shows unadjusted overall medians and user medians for average annual expenditures, OOP expenditures and financial burden, by disability status. Overall medians were generated across the total study population while user medians came from the values among respondents who used one or more specified services. Among the total study population, 81% had at least 1 outpatient visit, 72% filled at least 1 prescription, 11% had at least 1 inpatient visit, and 21% had at least 1 emergency room visit. Median total expenditures among persistently disabled adults were almost 6 times higher than among the nondisabled, $4234 compared to $748. Across all adults, not restricted to those who used specific services, median costs were highest for outpatient services, followed by prescription drugs; overall medians for inpatient and ED expenditures were 0. A similar difference was present for the overall median outpatient expenditures between these 2 groups ($1119 vs. $188). The overall median prescription expenditure for the persistent disability group was markedly high than among nondisabled adults. Temporarily disabled adults had lower expenditures than those who were persistently disabled, but still have higher median total, outpatient, and prescription expenditures than nondisabled adults. Among service users (Table 2), the highest median expenditures were associated with inpatient care, followed by outpatient services. For outpatient care and prescription drugs, persistently disabled adults experienced median expenditures that were significantly higher than both nondisabled and temporarily disabled adults. Among persons with at least 1 inpatient stay, disability was not associated with expenditures. Averaging expenditures across a 2-year period might understate expenditures for temporarily disabled persons, who were not disabled in the second year of study. To address this issue, we compared median estimates for 2007 and 2008 (data not in table). While median estimated overall expenditures for the temporary disability group were higher in 2007 than in 2008 ($1462 6 $172 vs. $1124 6 $143, respectively), in both years median expenditures by temporarily disabled adults were statistically higher than those of nondisabled persons, ($607 6 $28 and $464 6 $23, respectively). OOP expenses Among all adults, the 3 disability groups did not differ in OOP expenses for inpatient services and emergency department services (Table 2). Persistently disabled adults spent more than nondisabled adults for total services, outpatient services and prescription drugs. Of note, median OOP spending for drug prescriptions among persistently disabled adults was approximately 14 times higher than among nondisabled persons ($186 vs. $13), although differences declined to about 4 times higher when only persons who used prescription drugs were compared ($226 vs. $56).
292
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Table 2 Average annual health care expenditures, out-of-pocket expenditures, and ratios of out-of-pocket spending to family income by disability status: 2007 and 2008 Medical Expenditure Panel Survey Inpatient service ED service Drug prescriptions Total services Outpatient servicea
Disability status
Overall median (SE)
Healthcare expenditures, $ Total 282 (13) Persistent disability 1119b,c (78) Temporary disability 536b (59) No disability 188 (9) OOP expenditures, $ Total 37 (2) Persistent disability 99b (8) Temporary disability 73b (8) No disability 29 (2) Financial burden, % Total 0.06 (0.00) Persistent disability 0.22b,c (0.02) Temporary disability 0.12b (0.02) No disability 0.04 (0.00)
User median (SE)d
Overall median (SE)
User median (SE)e
Overall median (SE)
(207) (588) (833) (208)
0 0 0 0
323 311 258 327
(12) (0) (0) (17)
0 0 0 0
10 0b 8 22
(0.02) (0.00) (0.00) (0.03)
0 0 0 0
0.02 0.00b 0.03 0.03
474 1195b,c 698b 350
(16) (64) (63) (15)
0 0 0 0
4011 4984 3569 3582
64 107b 92b 54
(3) (9) (10) (2)
0 0 0 0
16 0 0 42
0.11 0.26b 0.18b 0.08
(0.01) (0.02) (0.03) (0.00)
0 0 0 0
0.03 0.00 0.00 0.05
User median (SE)f
Overall median (SE)
User median (SE)g
Overall median (SE)
(17) (27) (30) (21)
67 (5) 984b,c (101) 170b (29) 31(3)
233 1209b,c 291b 148
(13) (110) (43) (9)
1067 4234b,c 1612b 748
(38) (284) (121) (33)
(4) (0) (0) (3)
26 186b,c 64b 13
(2) (17) (11) (1)
79 226b,c 107b 56
(4) (20) (17) (3)
245 591b,c 388b 186
(9) (48) (37) (8)
(0.00) (0.00) (0.00) (0.00)
0.05 0.54b,c 0.11b 0.02
(0.00) (0.04) (0.02) (0.00)
0.15 0.64b,c 0.19b 0.09
(0.01) (0.04) (0.04) (0.01)
0.40 1.59b,c 0.71b 0.28
(0.02) (0.08) (0.08) (0.01)
ED indicates emergency department. a Includes office-based and hospital outpatient visits to physicians and nonphysical visits and 0-night stay visits. b Significantly different from the no disability group, p ! 0.05. c Significantly different from the temporary disability group, p ! 0.05. d 80.9% of the study sample, 94.9% of those with persistent disabilities, 88.6%of those with temporary disabilities, and 77.6% of persons with no disability had one or more outpatient visits during the 2-year period. e 11.1% of the study sample, 24.1% of those with persistent disabilities, 11.1% of those with temporary disabilities, and 8.6% of persons with no disability had 1 or more inpatient visits during the 2-year period. f 20.5% of the study sample, 37.3% of those with persistent disabilities, 26.3% of those with temporary disabilities, and 16.9% of persons with no disability had 1 or more ED visits during the 2-year period. g 72.2% of the study sample, 92.8% of those with persistent disabilities, 84.5% of those with temporary disabilities, and 67.2% of persons with no disability had 1 or more drug prescription fill or refills during the 2-year period.Source: 2007 and 2008 MEPS.
Temporarily disabled adults had higher OOP expenditures than nondisabled adults for total services, outpatient services, and prescription drugs (Table 2). The expenses associated with outpatient services were similar among persistently and temporarily disabled adults, but the temporarily disabled had lower expenditures for prescription drugs and lower total OOP expenditures. We also examined OOP health care expenditures as a proportion of total expenditures for each service category and total services (data not in table). At the 50th percentile, persistently disabled adults paid 24% of drug prescription expenditures and 8% of outpatient expenditures out-ofpocket, compared to 31% and 11%, respectively, paid by the temporary disability group and 24% and 9% by the no disability group. The median percentages of expenditures paid out-of-pocket for total services for the 3 disability groups also show a similar trend. The persistent disability group paid the lowest percentages of total expenditures out-of-pocket (15%) and the temporary disability group and the no disability group paid similar shares (22%, data not in table). Financial burden At the median, persistently disabled adults spent a higher proportion of total family income for total health services
than did either temporarily or nondisabled adults (Table 2). Within service categories, OOP expenses for persistently disabled adults were higher than those experienced by temporarily disabled and nondisabled persons for outpatient services and for prescription drugs, with no significant different for inpatient services and a minor difference for emergency department expenditures. Quantile analyses Table 3 shows estimated total expenditures, OOP expenditures and the proportion of family income used for OOP health care expenses the 10th, 50th, and 90th percentiles, adjusted for predisposing, enabling and health care need factors. A full set of coefficients for the model at the 50th percentile is shown in Table 4. At each expense percentile, the persistent disability group was estimated to have higher adjusted annual average total health care expenditures, OOP-spending, and ratios of OOP spending to family income than nondisabled adults. At the 50th percentile, the persistently disabled also exceeded the temporarily disabled for both total expenditures and the proportion of family income spent for OOP expenses. Temporarily disabled adults, while spending less than the permanently disabled in the 2 categories noted, generally experienced higher total expenses and proportion of
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296 Table 3 Estimated total and out-of-pocket expenditures and ratios of OOP to income at 10th, 50th, and 90th percentiles, adjusted for personal characteristics,c 2007e2008 MEPS 10th 50th 90th Disability status Total health care expenditures Intercept Disability status Temporary disability Persistent disability No disability (Ref. group) Out-of-pocket expenditures Intercept Disability status Temporary disability Persistent disability No disability (Ref. group) Ratios of OOP spending to family Intercept Disability status Temporary disability Persistent disability No disability (Ref. group)
Estimate
Estimate
Estimate
8.60
859.56
8088.57
112.57a 217.92a e
254.15a 1663.76a,b e
1.00 18.84a 23.48a e income 0.03
156.61
1115.09
62.93 155.56a e
188.43 456.42a e
1.26
0.03a 0.06a e
1603.08 7263.45a,b e
12.19
0.15a 0.58a,b e
0.04 1.85a e
Significantly different from the reference group, p ! 0.05. The persistent disability group significantly different from the temporary group, p ! 0.05. c Personal characteristics include gender, age, race, marital status, education, employment status, household income, insurance status, usual source of care, geographic location, place of residence, self-reported health status, chronic condition, and family size. a
b
family income consumed by OOP spending than did nondisabled adults. Differences among disability groups are visualized in Fig. 1, which shows excess adjusted total and OOP expenditures associated with disability, either persistent or temporary, compared to nondisabled adults. The graphic presentation clearly shows the varying effect of disability at different percentiles of overall health services use. At the lowest levels of overall use, differences are relatively small, but among high expenditure adults, disability effects are sizeable. Discussion Our findings both support earlier studies14,33 and add to the body knowledge about the effect of duration of physical disability on expenditures. We found that about 15% of working-age adults reported persistent disabilities and 7% had temporary disabilities. Adults with persistent disabilities, paralleling previous studies,34 were more economically vulnerable than nondisabled adults. In contrast, adults with temporary disabilities were similar to nondisabled adults in key socioeconomic characteristics, including education, income, and health insurance coverage. Adults with persistent disabilities had the greatest unadjusted annual medians for total expenditures, out-of-pocket
293
expenses, and financial burden ratios during 2007 and 2008. After adjusting for personal characteristics, estimated total expenditures, OOP expenses, and the proportion of family income spent as OOP expenses for persistently disabled persons were still far higher than those among nondisabled adults. Temporarily disabled adults also had higher estimated expenses than nondisabled persons, but at the middle of the distribution (50th percentile), persistently disabled persons had both higher total expenditures and financial burden ratios than the temporarily disabled. Individuals with persistent disabilities paid a lower percentage of their total expenditures OOP than did others, a finding consistent with previous research.28,35 This may be related to differences in health insurance status. Adults with persistent disabilities were more likely to be insured by public health insurance, which often provides coverage with low copayments.36 Conversely, the value of employer-based coverage has begun to erode over the last decade, leading to rapid premium growth and more costsharing.37 Despite better protection in terms of percent of expenditures met OOP, the adjusted median financial burden ratio among persistently disabled adults was higher than among their counterparts without disabilities. Adults with persistent disabilities seemed to be least protected from prescription drug costs, with persons who used medications spending 0.6% of total family income (median) for these products. Our findings suggest that caps on out-of-pocket spending could benefit permanently disabled individuals. Expenditure caps could be targeted to those with persistent disabilities who are most economically disadvantaged and have multiple chronic health conditions. Temporarily disabled working age adults constitute a demographically and clinically different population from those with permanent disability. They are more likely to be male, younger than 45 years, married rather than widowed/ divorced, with better education. With these resources, they are more likely to be employed, less likely to be poor, and more likely to be privately insured. They are a healthier population than the permanently disabled adults, as indicated by self-reported health status and number of chronic conditions. Nonetheless, their financial burden, as estimated at the median and adjusted for these demographic considerations, is higher than those of nondisabled individuals. Since most of the temporarily disabled have private health insurance, further research is needed to ascertain whether insurance characteristics, such as high deductibles or spending caps, are positively or negatively linked to financial burden. Several study limitations should be noted. First, MEPS does not include individuals who live in institutional settings, and thus our study does not address costs of these extremely disabled persons. Second, our definition of disability is relatively insensitive. We were able to measure functional, activity, and/or sensory limitations at only 2
294
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Table 4 Coefficients for all factors included in multivariable estimates for expenditures, OOP expenditures, and ratios of OOP spending to family income at 50th percentile, 2007e2008 MEPS Total health Out-of-pocket Ratios of OOP spending care expenditures expenditures to family income Characteristics Intercept Disability status (no disability) Temporary disability Persistent disability Gender (female) Male Age (age 18e44) Age 45e64 Race (White) Nonwhite Marital status (never married) Married Widowed/divorced/ separated Education (no degree) HS/ged BS/Post Hs/Grad Family size (1 person) 2 persons >3 persons Employment (unemployed) Employed Household income (poor/near poor) Low income Middle income High income Insurance status (uninsured) Any private Public insurance Usual source of care (no) Yes Geographic location (northeast) Midwest South West Residence (urban) Rural Self-reported health status (fair/poor) Good Excellent Chronic condition (no comorbidity) 1 comorbidity 2 comorbidities >3 comorbidities
Coefficient
95% CI
Coefficient
95% CI
Coefficient
95% CI
859.56
490.73e1228.38
156.61
73.13e240.09
1.26
0.98e1.54
254.15a 1663.76a,b
60.56e447.73 1254.01e2073.50
62.93 155.56a
7.84e133.70 87.61e223.51
0.15a 0.58a,b
0.02e0.27 0.39e0.78
465.50a
558.85e(372.15)
188.58a
122.11a
146.12e(98.10)
0.20a
59.40e317.77
113.10a
72.11e154.09
384.05e(192.38)
89.97a
117.28e(62.66)
0.10a
0.15e(0.06)
182.27a 95.74
84.28e280.26 261.71e70.22
19.43 41.98
8.72e47.58 96.29e12.33
0.01 0.08
0.05e0.03 0.06e0.23
93.17 250.63a
4.43e190.77 103.07e398.19
9.49 106.54a
17.81e36.78 69.40e143.69
86.40 391.98a
242.09e69.29 538.95e(245.01)
30.30 75.13a
75.16e14.57 112.52e(37.74)
0.39a 0.51a
0.52e(0.26) 0.64e(0.39)
249.40a
387.66e(111.14)
5.77
34.10e22.56
0.10a
0.15e(0.04)
103.30 80.43 337.76a
10.42e217.03 45.60e206.47 194.73e480.78
33.52a 41.53a 97.50a
1.12e65.92 10.12e72.93 55.76e139.24
0.10 0.18a 0.28a
0.22e0.02 0.31e(0.06) 0.41e(0.15)
369.11a 438.46a
272.46e465.76 188.10e688.83
18.38 112.95a
11.78e48.55 157.84e(68.06)
0.03 0.19a
0.02e0.07 0.29e(0.09)
339.82a
252.98e426.67
75.05a
46.72e103.38
0.12a
0.08e0.15
165.55a 162.33a 86.59
9.63e321.47 31.21e293.45 50.84e224.01
37.83 40.60a 25.56
6.25e81.91 1.58e79.61 16.48e67.59
0.07a 0.06a 0.03
0.02e0.12 0.01e0.12 0.02e0.08
62.74
177.24e51.76
16.81
47.53e13.90
0.01
0.03e0.05
397.13a 483.81a
678.84e(115.43) 772.87e(194.75)
40.11 59.97a
94.24e14.02 114.58e(5.36)
487.84a 1350.54a 3361.27a
363.50e612.18 902.45e1798.62 2616.92e4105.62
134.83a 278.56a 484.71a
103.21e166.46 196.36e360.76 328.23e641.19
288.22a
0.10a
0.23e(0.16)
0.07a 0.13a
0.37a 0.42a
0.19a 0.46a 1.21a
0.06e0.14
0.02e0.12 0.07e0.20
0.56e(0.19) 0.60e(0.23)
0.13e0.24 0.33e0.60 0.88e1.53
Reference categories in brackets. Significantly different from the reference group, p ! 0.05. b The persistent disability group significantly different from the temporary group, p ! 0.05. a
points over a 2-year period. This may not be an adequate representation of a respondent’s disability trajectory. Third, all definitions of disability are based on self-report, and
thus subject to problems in recall and reporting. Fourth, our analysis is restricted to persons with physical limitations; mental limitations may have similar or different
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Fig. 1. Differences in annual total health care expenditures and out-ofpocket expenditures at 10th, 50th, and 90th percentiles after controlling for other factors, comparing persistently disabled adults and temporarily disabled adults with nondisabled adults, based on data from 2007 to 2008 Medical Expenditure Panel Survey.
implications. Next, our analysis averaged estimates over 2 years. Averaging could have underestimated the median expenditures for temporarily disabled adults during their year of disability. Finally, MEPS data on health conditions, health status, health insurance coverage, income, and employment are self-reported and, like disability status, may be subject to recall bias. In summary, our study is the first study using longitudinal data and quantile regression analyses to explore the impact of variations durations of disability over a 2-year interval on health care expenditures and financial burden. Our findings suggest that people who have disabling conditions for a long period have better financial protection against out of pocket health care expenses but still face high financial burdens because of their higher level of need for health care services and their socioeconomic disadvantage. The experience of temporarily disabled adults deserves further study to clarify needed policy interventions.
Acknowledgments The authors wish to express their appreciation to Andrew Ortaglia for his assistance in quantile regression analyses. The statements contained in this article are solely those of the authors and do not necessarily reflect the views or policies of their agencies.
References 1. Houtenville AJ, Ruiz T. Annual Disability Statistics Compendium: 2011. Durham, NH: University of New Hampshire, Institute on Disability; 2011. 2. Livermore G, Stapleton DC, O’Toole M. Health care costs are a key driver of growth in federal and state assistance to working-age people with disabilities. Health Aff (Millwood). 2011;30(9):1664e1672.
295
3. Institute of Medicine Committe on Disability in America. The Future of Disability in America. Washington, DC: National Academies Press; 2007. 4. Pobutsky AM, Hirokawa R, Reyes-Salvail F. Estimates of disability among ethnic groups in Hawaii. Californian J Health Promot. 2003;1(Special Issue):65e82. 5. Centers for Disease Control and Prevention (CDC). Prevalence and most common causes of disability among adultseUnited States, 2005. Morb Mortal Wkly Rep. 2009;58(16):421e426. 6. Foote SM, Hogan C. Disability profile and health care costs of Medicare beneficiaries under age sixty-five. Health Aff (Millwood). 2001;20:242e253. 7. Kinne S, Patrick DL, Doyle DL. Prevalence of secondary conditions among people with disabilities. Am J Public Health. 2004;94(3): 443e445. 8. Chevarley FM, Thierry JM, Gill CJ, Ryerson AB, Nosek MA. Health, preventive health care, and health care access among women with disabilities in the 1994e1995 National Health Interview Survey, Supplement on Disability. Womens Health Issues. 2006;16(6): 297e312. 9. Rasch EK, Magder L, Hochberg MC, Magaziner J, Altman BM. Health of community-dwelling adults with mobility limitations in the United States: incidence of secondary health conditions. Part II. Arch Phys Med Rehabil. 2008;89(2):219e230. 10. Wilber N, Mitra M, Walker DK, Allen D, Meyers AR, Tupper P. Disability as a public health issue: findings and reflections from the Massachusetts survey of secondary conditions. Milbank Q. 2002;80(2):393e421. 11. Lollar DJ. Public health and disability: emerging opportunities. Public Health Rep. 2002;117(2):131e136. 12. Simeonsson RJ, McDevitt LN. Issues in Disability & Health the Role of Secondary Conditions & Quality of Life. Chapel Hill, NC: Office on Disability and Health; 1999. 13. Sutton JP, DeJong G. Managed care and people with disabilities: framing the issues. Arch Phys Med Rehabil. 1998;79(10): 1312e1316. 14. Mitra S, Findley PA, Sambamoorthi U. Health care expenditures of living with a disability: total expenditures, out-of-pocket expenses, and burden, 1996 to 2004. Arch Phys Med Rehabil. 2009;90(9): 1532e1540. 15. Centers for Disease Control and Prevention (CDC). Racial/ethnic disparities in self-rated health status among adults with and without disabilitieseUnited States, 2004-2006. Morb Mortal Wkly Rep. 2008;57(39):1069e1073. 16. Rupp K, Davies PS, Strand A. Disability benefit coverage and program interactions in the working-age population. Soc Secur Bull Social Security Bull. 2008;68(1):1e30. 17. Dejong G, Palsbo SE, Beatty PW, Jones GC, Knoll T, Neri MT. The organization and financing of health services for persons with disabilities. Milbank Q. 2002;80(2):261e301. 18. Martin BI, Lee MJ, Turner JA, Mirza SK, Comstock BA, Deyo RA. Trends in health care expenditures, utilization, and health status among US adults with spine problems, 1997-2006. Spine (Phila Pa 1976). 2009;34(19):2077e2084. 19. WHO. International Classification of Functioning, Disability and Health (ICF). Available from: http://www.who.int/classifications/icf/ en/index.html; April 2011. 20. Wei W, Findley PA, Sambamoorthi U. Disability and receipt of clinical preventive services among women. Womens Health Issues. 2006;16(6):286e296. 21. Agency for Healthcare Research and Quality. MEPS HC-121: 2008 Full Year Consolidated Data File. Available from: http://www.meps. ahrq.gov/mepsweb/data_stats/download_data/pufs/h121/h121doc.shtml; July 2011. 22. Agency for Healthcare Research and Quality. MEPS-HC Summary Data Tables Technical Notes. Available from: http://www.meps.ahrq. gov/mepsweb/survey_comp/hc_technical_notes.shtml; July 2011.
296
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
23. Bennett KJ, Dismuke CE. Families at financial risk due to high ratio of out-of-pocket health care expenditures to total income. J Health Care Poor Underserved. 2010;21(2):691e703. 24. Paez KA, Zhao L, Hwang W. Rising out-of-pocket spending for chronic conditions: a ten-year trend. Health Aff. 2009;28(1): 15e25. 25. Agency for Healthcare Research and Quality. MEPS HC-113: 2007 Full Year Consolidated Data File. Available from: http://meps. ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPuf Number5HC-113; July 2011. 26. Andersen RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav. 1995;36(1):1e10. 27. Chan L, Ciol MA, Shumway-Cook A, et al. A longitudinal evaluation of persons with disabilities: does a longitudinal definition help define who receives necessary care? Arch Phys Med Rehabil. 2008;89(6): 1023e1030. 28. Newacheck PW, Inkelas M, Kim SE. Health services use and health care expenditures for children with disabilities. Pediatrics. 2004;114(1):79e85. 29. Egede LE, Zheng D, Simpson K. Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care. 2002;25(3):464e470.
30. Dodd S, Bassi A, Bodger K, Williamson P. A comparison of multivariable regression models to analyse cost data. J Eval Clin Pract. 2006;12(1):76e86. 31. Cook BL, Manning WG. Measuring racial/ethnic disparities across the distribution of health care expenditures. Health Serv Res. 2009;44(5 Pt 1):1603e1621. 32. Koenker R, Hallock KF. Quantile regression. J Econ Perspect. 2001;15(4):143e156. 33. Martin BI, Deyo RA, Mirza SK, et al. Expenditures and health status among adults with back and neck problems. JAMA. 2008;299(6): 656e664. 34. Iezzoni LI. Eliminating health and health care disparities among the growing population of people with disabilities. Health Aff (Millwood). 2011;30(10):1947e1954. 35. Riley GF, Lubitz JD, Zhang N. Patterns of health care and disability for Medicare beneficiaries under 65. Inquiry. 2003;40(1):71e83. 36. Shen Y-C, McFeeters J. Out-of-pocket health spending between lowand higher-income populations: who is at risk of having high financial burdens? Med Care. 2005;44(3):200e209. 37. Rowland D, Hoffman C, McGinn-Shapiro M. Health Care and the Middle Class: More Costs and Less Coverage. Menlo Park, CA: Henry J. Kaiser Family Foundation; 2009.
Research Paper
Health care expenditures among working-age adults with physical disabilities: Variations by disability spans Chaiporn Pumkam, Ph.D.a,*, Janice C. Probst, Ph.D.a, Kevin J. Bennett, Ph.D.b, James Hardin, Ph.D.c, and Sudha Xirasagar, Ph.D.a a
Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, 800 Sumter Street, SC 29208, USA b Department of Family and Preventive Medicine, University of South Carolina School of Medicine, Columbia, SC 29203, USA c Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
Abstract Background: Data on health care costs for working-age adults with physical disabilities are sparse and the dynamic nature of disability is not captured. Objectives: To assess the effect of 3 types of disability status (persistent disability, temporary disability, and no disability) on health care expenditures, out-of-pocket (OOP) spending, and financial burden. Methods: Data from Medical Expenditure Panel Survey panel 12 (2007e2008) were used. Respondents were classified into 3 groups. Medians of average annual expenditures, OOP expenditures, and financial ratios were weighted. The package R was used for quantile regression analyses. Results: Fifteen percent of the working-age population reported persistent disabilities and 7% had temporary disabilities. The persistent disability group had the greatest unadjusted annual medians for total expenditures ($4234), OOP expenses ($591), and financial burden ratios (1.59), followed by the temporary disability group ($1612, $388, 0.71 respectively). The persistent disability group paid approximately 15% of total health care expenditures out-of-pocket, while the temporary disability group and the no disability group each paid 22% out-of-pocket. After adjusting for other factors, quantile regression shows that the persistent disability group had significantly higher total expenditures, OOP expenses, and financial burden ratios (coefficients 1664, 156, 0.58 respectively) relative to the no disability group at the 50th percentile. Results for the temporary disability group show a similar trend except for OOP expenses. Conclusions: People who have disabling conditions for a longer period have better financial protection against OOP health care expenses but face greater financial burdens because of their higher out-of-pocket expenditures and their socioeconomic disadvantages. Ó 2013 Elsevier Inc. All rights reserved. Keywords: Disability; Expenditures; Working-age; Disparities
In 2010, about 36 million (12%) Americans of all ages living in the community reported a disability, including 10% of adults aged 18e64 and 37% of adults over 65 years of age.1 While disability rates increase with age, given the large number of working-age persons in the population, most persons with disability are working-age adults. Adults aged 18e64 constitute more than 52% of the total disabled population.1 No conflicts of interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The abstract was selected for oral presentation during the 140th APHA Annual Meeting (October 27e31, 2012) in San Francisco, CA, USA. * Corresponding author. Tel.: þ1 803 777 1627. E-mail address: [email protected] or [email protected] (C. Pumkam). 1936-6574/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.dhjo.2013.03.002
Costs of disabilities among working-age adults are substantial. In 2008, US government spending for assistance to working-age adults with disabilities was $357 billion, approximately 12% of all federal expenditures.2 Health care and income maintenance each accounted for more than 47%of the federal spending for workingage people with disabilities.2 These economic burdens continue to rise, putting both private and public sectors at financial risk.3 This can lead to the declines in spending on other governmental programs (e.g., employment, housing, and food assistance programs) for supporting disabled people as to compensate for the increase in health care costs. Disability can result from injury, aging, or chronic diseases such as arthritis, asthma, obesity, back and joint problems, and cardiovascular disease.4e6 In addition, the
288
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
presence of a disabling condition places people at increased risk for one or more secondary conditions such as diabetes and cardiovascular disease.7e9 Disabling and secondary conditions require people with disabilities to make greater use of health care than the general population,7,10e13 resulting in higher health care expenditures, out-of-pocket (OOP) spending, and financial burden compared with people without disabilities.14 In general, disabled people experience higher rates of poverty, unemployment, lower educational attainment, and inadequate health insurance coverage.15 Several policy initiatives at the federal and state levels seek to improve access to care and protect people with disabilities against considerable financial risk. Two principal income support benefits, the Supplemental Security Income (SSI) program and Social Security Disability Insurance (SSDI) program provide a safety net for disabled people. These two programs interact with other programs such as health insurance programs (i.e., Medicare and Medicaid), employmentrelated programs (i.e., Unemployment Insurance (UI) and Workers’ Compensation (WC)), Supplemental Nutrition Assistance Program (SNAP), and Temporary Assistance for Needy Families (TANF).16 Over time, laws have been enacted to expand health care coverage to persons with preexisting conditions. These include the Ticket to Work and Work Incentives Improvement Act (TWWIA) of 1999, which allows Medicaid buy-in for disabled persons whose income would otherwise disqualify them; the Health Insurance Portability and Accountability Act (HIPAA), which guarantees the portability of insurance regardless of preexisting conditions; the Consolidated Omnibus Budget Reconciliation Act (COBRA), which requires continued coverage for 29 months for disabled individuals; and the Patient Protection and Affordable Care Act (PPACA) of 2010. Improvements overtime in legislation and these public health programs are anticipated to reduce outof-pocket spending and financial burden among adults with disabilities. Several studies have examined health care costs for the elderly and children with disabilities, but data for working-age adults with disabilities are sparse. In 1996, the mean health care expenditure for people with disabilities was $2489, compared to $420 for those without disabilities.17 In 2004, the average total health care expenditure and the financial burden (the percentage of family income spent on total out-of-pocket (OOP) spending) among adults aged 21e61 years with disabilities was about 5 times those of adults without disabilities, while the OOP spending for the disabled adults was 3 times that for their nondisabled counterparts.14 These prior studies, however, did not examine health care expenditures, OOP spending, and financial burden across service categories (inpatient, outpatient, emergency department, or prescription medications). Further, previous studies on expenditures among people
with disabilities have not distinguished between shortterm and long-term disability. Differences in duration of disability may differently affect health care needs, expenditures, and governmental income benefits. For example, individuals who are permanently disabled may qualify for SSDI and, after receiving SSDI for 2 years, become eligible for Medicare. Temporarily disabled individuals, however, may pay a higher share of their health care expenditures out-of-pocket and face a higher financial burden due to inadequate financial protection. Thus, the present research aims to investigate the effect of the 3 types of physical disability status (persistent disability, temporary disability, and no disability) on health care expenditures, OOP spending, and financial burden community-dwelling working-age adults. Methods Data source and sample Data were drawn from Medical Expenditure Panel Survey (MEPS) panel 12 (2007e2008), a nationally representative survey of health care use, expenditures, sources of payment, and health insurance coverage for the US civilian, noninstitutionalized population, cosponsored by Agency for Healthcare Research and Quality (AHRQ) and the National Center for Health Statistics. The MEPS is a panel survey, with 5 rounds of interviews covering 2 full years. Study data primarily came from the Household Component, which collects person-level information about demographic characteristics, health conditions, health status, use of medical services, charges and sources of payments, access to care, satisfaction, health insurance coverage, income, and employment. MEPS uses a multistage sampling design that accounts for clustering, stratification, oversampling, and nonresponse. This enables generation of unbiased national estimates.18 The sample was limited to adults between 18 and 64 years of age with data for both years of the survey, all 5 rounds (N 5 6764). Variables Independent variable: definition of disability We conceptualized disability according to the International Classification of Functioning, Disability and Health (ICF) framework endorsed by the World Health Organization.19 The ICF framework classifies disability into 3 levels: physical and mental impairment, activity limitations, and participation restrictions. Disability is considered the outcome of a dynamic interaction between health conditions and contextual factors including external environmental factors (e.g., social attitudes and social structures) and internal personal factors (e.g., gender, age, education, and behavior patterns). Paralleling previous work,20 we used the MEPS ANYLIM variable to identify disability status. The MEPS
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
defines any limitation (ANYLIM) as reporting any functional, activity, and/or sensory limitation in any survey round within 1 year. Disability is deemed present if a respondent meets any one of the following criteria: (1) requiring help or supervision with at least one ADL (activity of daily living) or IADL (instrumental activity of daily living); (2) having difficulty in performing certain specific physical actions (e.g., bending, lifting, or stooping); (3) having any limitation in work, housework, or school; and (4) having difficulty seeing (with glasses or contacts, if used) or hearing (with a hearing aid, if used).21 We limited our study population to those with physical impairments; persons with mental disorders were excluded. To capture change in disability status, we classified respondents into 1 of 3 groups: persistent disability, temporary disability, and without disability. Disability was considered persistent if the respondent reported any limitation in both years. Disability was considered temporary if individuals reported any limitation in the first year (2007) of the survey and not the other, while individuals who reported no limitation in both years were categorized as nondisabled.
Dependent variables Expenditures. Total health care expenditures and expenditures for outpatient visits, inpatient stays, emergency room visits, and medication prescriptions were calculated by summing payments for care provided in 2007e2008. The sum of expenditures over both years for each respondent was then divided by 2 to generate average annual expenditures per person. MEPS expenditures include out-of-pocket payments and payments paid by third party payers including private insurance, Medicaid, Medicare, and other sources. Expenditures for over-the-counter medications, alternative care services, and phone contracts with medical providers are not included.22 For this study, hospital outpatient and officebased visit expenditures associated with physician and nonphysician visits as well as expenditures for 0-night stays were combined into a single outpatient service category. Inpatient expenditures included the total expenses for hospital stays minus expenses associated with 0-night stays. Expenditures for dental, home health, vision aids, and other medical service categories were not examined because these service expenditures accounted for less than 20% of the total expenditures. The total expenditures values reported do include these categories. Out-of-pocket spending on health care. Out-of-pocket expenditures, paid by an individual or family, were summed over the 2 years and averaged to generate average annual service OOP spending and total OOP spending. In MEPS, OOP expenditures are self-reported payments for coinsurance, copayments, deductibles, and medically related items and services not covered by insurance.22 Paralleling
289
23,24
previous studies, this measure does not include health insurance premiums, because premiums are a constant value that does not change with health services use. Financial burden (out-of-pocket spending burden). Health care financial burden was defined as the ratio of OOP spending over total family income, expressed as a percentage. Family income was derived by summing incomes across family members. Person-level income included annual earnings, business and farm gains and losses, unemployment and workers’ compensation, interest and dividends, child support, private pensions, IRA withdrawals, social security, veterans payments, supplemental security income and cash welfare payments from public assistance, related programs and other income.25 Financial burden ratios were calculated for the 4 service categories and total health care services and averaged over the 2 years. One dollar was added to respondents’ family incomes when 0 family income was reported. To reduce the impact of extreme cases, these ratios were top-coded at 100%.23 Additional independent variables were selected according to Anderson’s model of health services use.26 Predisposing characteristics included: sex, age group (18e44 vs. 45e64 years), race (white, nonwhite), marital status (married, windowed/divorced/separated, and never married), geographic region (Northeast, Midwest, South, and West), place of residence (urban vs. rural), education (no degree, a high school diploma or general education diploma (GED), a bachelor’s degree or more than a high school degree or a graduate degree such as M.A. or Ph.D.), and family size (living alone, 2, >3). The enabling characteristics included: employment status (employed vs. unemployed), insurance status and type (private insurance, public insurance, uninsured), having a usual source of care (yes vs. no), and poverty status/household income (poor/ near poor, low income, middle income, or high income). Lastly, health needs included self-reported health status (very good/excellent, good, and fair/poor) and comorbidities (expressed as having 0, 1, 2, >3 conditions). The comorbidity conditions included cancer, hypertension, diabetes, acute myocardial infarction (AMI), coronary heart disease, angina, stroke, rheumatoid arthritis, asthma, and emphysema.27 Statistical approach Descriptive analyses were performed using SASCallable SUDAAN 9.2 statistical software to account for the complex sampling design of MEPS.21 Differences in characteristics across the 3 disability types were tested using Wald Chi-square tests. Medians of average annual expenditures, OOP expenditures, and ratios for each service category and the total services, subdivided by disability status were generated. All median estimates for expenditures, OOP expenses, and ratios were weighted to provide national estimates. Median estimates then were compared
290
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Table 1 Demographic characteristics of working-age adults, by disability status Characteristics Total Persistent disability Observations Weighted observations Predisposing characteristics Race/ethnicity White Nonwhite Gendera Male Female Age groupa 18e44 45e64 Marital statusa Married Widow/divorced/separated Never married Educationa No degree High school Bachelor/post high school/graduate school Enabling characteristics Employment statusa Employed Unemployed Household incomea Poor/near poor Low income Middle income High income Insurance statusa Any private Public only Uninsured Usual source of carea Yes No Geographic locationa Northeast Midwest South West Residencea Urban Rural Perceived health needs Self-reported health statusa Excellent/very good Good Fair/poor Chronic conditionsa No comorbidity 1 comorbidity 2 comorbidity >3 comorbidity a b c
6764 (100%) 176 060 374
1016 (14.8%) 26 067 388
Temporary disability
No disability
454 (6.9%) 12 114 217
5294 (78.3%) 137 878 769
p valuea
0.3079 80.5 19.5
81.9 18.1
82.2 17.8
80.1 19.9
49.5 50.5
44.8b,c 55.2b,c
56.2b 43.8b
49.7 50.3
58.7 41.3
30.2b,c 69.8b,c
43.6b 56.4b
65.4 34.6
55.6 15.3 29.1
45.9b,c 31.3b,c 22.8b
56.0 23.0b 21.0b
57.4 11.6 31.0
15.4 49.1 35.5
20.6b, 53.0c 26.4b,c
14.9 43.9 41.2
14.5 48.8 36.8
77.2 22.8
49.4b,c 50.6b,c
75.6b 24.4b
82.5 17.5
14.4 13.2 33.0 39.5
26.7b,c 15.3 31.7 26.3b,c
17.5b 13.4 33.7 35.4
11.8 12.8 33.1 42.3
71.6 9.8 18.5
56.4b,c 28.7b,c 14.9b
72.6 9.8 17.5
74.4 6.2 19.3
72.0 28.0
82.3b,c 17.7b,c
73.6 26.4
69.9 30.1
18.6 21.9 36.1 23.5
14.9 25.8 37.9 21.3
16.8 19.6 41.0 22.6
19.4 21.3 35.3 24.0
84.6 15.4
81.0 19.0
80.1 19.9
85.7 14.3
62.8 25.7 11.5
24.0b,c 32.7b 43.3b,c
54.8b 30.3b 14.9b
70.9 23.9 5.2
58.6 23.7 10.2 7.4
24.2b,c 24.7 21.1b 30.0b,c
44.0b 29.7b 16.1b 10.2b
66.4 23.0 7.7 2.9
0.0008
!0.0001 !0.0001
!0.0001
!0.0001 !0.0001
!0.0001
!0.0001
0.0339
0.0197
!0.0001
!0.0001
Significant differences in proportions for each characteristic across the 3 disability types, p ! 0.05. Significantly different from the no disability group, p ! 0.05. Significantly different from the temporary disability group, p ! 0.05.
across the 3 disability types using quantile regression analysis and considered significantly different if their 95% confidence intervals did not overlap.
The distribution of health care expenditures typically is skewed to the right, because a small proportion of people experience extreme costs, leading to inappropriate means
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
and large standard errors. Previous analyses of health care expenditures used ordinary least squares (OLS) regression analyses of the mean expenditure and the logarithmic transformation to normalize skewed data and stabilize variances.28e30 However, linear regression of log transformed expenditures models the expected mean of the log expenditures, rather than the log of the expected mean. Back transformation without the application of bias correction factors results in biased estimates of expenditures and inaccurate effect size of selected variables on expenditures.30 Furthermore, OLS is unable to capture how variable the effect of each selected factor can be across the distribution. Thus, quantile regression is considered appropriate for data with heavily skewed distributions. Quantile regression allows the intercept and slope coefficients to vary across quantiles rather than constant slopes assumed by OLS.31 A more comprehensive picture of the effect of selected variables on the outcome variable at specific or all percentiles can then be detected. We applied quantile regression analyses to examine the effect of the 3 disability types on the outcomes of interest: average annual total health care expenditures, total out-ofpocket spending, and financial burden. We estimated the 10th, 50th, and 90th percentile of the dependent variables, conditional on the independent variables. The main independent variable of interest was disability status (persistent disability, temporary disability, and no disability). Adjusted coefficient estimates at 10th, 50th and 90th percentiles were presented. The statistical software package ‘‘R’’ version 2.12.2 was used to perform quantile regression analyses for the survey data.32 Statistical significance for all analyses in this study was defined as p ! 0.05 unless explicitly noted. Results Prevalence of disability Among working-age adults surveyed in 2007e2008, 15% reported a disability in both years of the survey period (persistent disability) and approximately 7% reported a disability in the first year of the 2 years (temporary disability). The distribution of the population by disability status across socio-demographic and health categories is provided in Table 1. Across disability types, temporarily disabled adults were more similar to the nondisabled population than to permanently disabled adults, in ways that might affect the financial burden of care. For example, similar proportions of the temporarily disabled and the nondisabled respondents reported private insurance coverage (73% and 74%, respectively), vs. 56.4% among the persistently disabled. Similarly, the proportion of the temporarily disabled and nondisabled adults who were poor or near poor were slightly different (17.5% and 11.8%, respectively), while disabled adults were markedly more likely than either of the other groups to experience poverty (26.7%).
291
Health care expenditures Table 2 shows unadjusted overall medians and user medians for average annual expenditures, OOP expenditures and financial burden, by disability status. Overall medians were generated across the total study population while user medians came from the values among respondents who used one or more specified services. Among the total study population, 81% had at least 1 outpatient visit, 72% filled at least 1 prescription, 11% had at least 1 inpatient visit, and 21% had at least 1 emergency room visit. Median total expenditures among persistently disabled adults were almost 6 times higher than among the nondisabled, $4234 compared to $748. Across all adults, not restricted to those who used specific services, median costs were highest for outpatient services, followed by prescription drugs; overall medians for inpatient and ED expenditures were 0. A similar difference was present for the overall median outpatient expenditures between these 2 groups ($1119 vs. $188). The overall median prescription expenditure for the persistent disability group was markedly high than among nondisabled adults. Temporarily disabled adults had lower expenditures than those who were persistently disabled, but still have higher median total, outpatient, and prescription expenditures than nondisabled adults. Among service users (Table 2), the highest median expenditures were associated with inpatient care, followed by outpatient services. For outpatient care and prescription drugs, persistently disabled adults experienced median expenditures that were significantly higher than both nondisabled and temporarily disabled adults. Among persons with at least 1 inpatient stay, disability was not associated with expenditures. Averaging expenditures across a 2-year period might understate expenditures for temporarily disabled persons, who were not disabled in the second year of study. To address this issue, we compared median estimates for 2007 and 2008 (data not in table). While median estimated overall expenditures for the temporary disability group were higher in 2007 than in 2008 ($1462 6 $172 vs. $1124 6 $143, respectively), in both years median expenditures by temporarily disabled adults were statistically higher than those of nondisabled persons, ($607 6 $28 and $464 6 $23, respectively). OOP expenses Among all adults, the 3 disability groups did not differ in OOP expenses for inpatient services and emergency department services (Table 2). Persistently disabled adults spent more than nondisabled adults for total services, outpatient services and prescription drugs. Of note, median OOP spending for drug prescriptions among persistently disabled adults was approximately 14 times higher than among nondisabled persons ($186 vs. $13), although differences declined to about 4 times higher when only persons who used prescription drugs were compared ($226 vs. $56).
292
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Table 2 Average annual health care expenditures, out-of-pocket expenditures, and ratios of out-of-pocket spending to family income by disability status: 2007 and 2008 Medical Expenditure Panel Survey Inpatient service ED service Drug prescriptions Total services Outpatient servicea
Disability status
Overall median (SE)
Healthcare expenditures, $ Total 282 (13) Persistent disability 1119b,c (78) Temporary disability 536b (59) No disability 188 (9) OOP expenditures, $ Total 37 (2) Persistent disability 99b (8) Temporary disability 73b (8) No disability 29 (2) Financial burden, % Total 0.06 (0.00) Persistent disability 0.22b,c (0.02) Temporary disability 0.12b (0.02) No disability 0.04 (0.00)
User median (SE)d
Overall median (SE)
User median (SE)e
Overall median (SE)
(207) (588) (833) (208)
0 0 0 0
323 311 258 327
(12) (0) (0) (17)
0 0 0 0
10 0b 8 22
(0.02) (0.00) (0.00) (0.03)
0 0 0 0
0.02 0.00b 0.03 0.03
474 1195b,c 698b 350
(16) (64) (63) (15)
0 0 0 0
4011 4984 3569 3582
64 107b 92b 54
(3) (9) (10) (2)
0 0 0 0
16 0 0 42
0.11 0.26b 0.18b 0.08
(0.01) (0.02) (0.03) (0.00)
0 0 0 0
0.03 0.00 0.00 0.05
User median (SE)f
Overall median (SE)
User median (SE)g
Overall median (SE)
(17) (27) (30) (21)
67 (5) 984b,c (101) 170b (29) 31(3)
233 1209b,c 291b 148
(13) (110) (43) (9)
1067 4234b,c 1612b 748
(38) (284) (121) (33)
(4) (0) (0) (3)
26 186b,c 64b 13
(2) (17) (11) (1)
79 226b,c 107b 56
(4) (20) (17) (3)
245 591b,c 388b 186
(9) (48) (37) (8)
(0.00) (0.00) (0.00) (0.00)
0.05 0.54b,c 0.11b 0.02
(0.00) (0.04) (0.02) (0.00)
0.15 0.64b,c 0.19b 0.09
(0.01) (0.04) (0.04) (0.01)
0.40 1.59b,c 0.71b 0.28
(0.02) (0.08) (0.08) (0.01)
ED indicates emergency department. a Includes office-based and hospital outpatient visits to physicians and nonphysical visits and 0-night stay visits. b Significantly different from the no disability group, p ! 0.05. c Significantly different from the temporary disability group, p ! 0.05. d 80.9% of the study sample, 94.9% of those with persistent disabilities, 88.6%of those with temporary disabilities, and 77.6% of persons with no disability had one or more outpatient visits during the 2-year period. e 11.1% of the study sample, 24.1% of those with persistent disabilities, 11.1% of those with temporary disabilities, and 8.6% of persons with no disability had 1 or more inpatient visits during the 2-year period. f 20.5% of the study sample, 37.3% of those with persistent disabilities, 26.3% of those with temporary disabilities, and 16.9% of persons with no disability had 1 or more ED visits during the 2-year period. g 72.2% of the study sample, 92.8% of those with persistent disabilities, 84.5% of those with temporary disabilities, and 67.2% of persons with no disability had 1 or more drug prescription fill or refills during the 2-year period.Source: 2007 and 2008 MEPS.
Temporarily disabled adults had higher OOP expenditures than nondisabled adults for total services, outpatient services, and prescription drugs (Table 2). The expenses associated with outpatient services were similar among persistently and temporarily disabled adults, but the temporarily disabled had lower expenditures for prescription drugs and lower total OOP expenditures. We also examined OOP health care expenditures as a proportion of total expenditures for each service category and total services (data not in table). At the 50th percentile, persistently disabled adults paid 24% of drug prescription expenditures and 8% of outpatient expenditures out-ofpocket, compared to 31% and 11%, respectively, paid by the temporary disability group and 24% and 9% by the no disability group. The median percentages of expenditures paid out-of-pocket for total services for the 3 disability groups also show a similar trend. The persistent disability group paid the lowest percentages of total expenditures out-of-pocket (15%) and the temporary disability group and the no disability group paid similar shares (22%, data not in table). Financial burden At the median, persistently disabled adults spent a higher proportion of total family income for total health services
than did either temporarily or nondisabled adults (Table 2). Within service categories, OOP expenses for persistently disabled adults were higher than those experienced by temporarily disabled and nondisabled persons for outpatient services and for prescription drugs, with no significant different for inpatient services and a minor difference for emergency department expenditures. Quantile analyses Table 3 shows estimated total expenditures, OOP expenditures and the proportion of family income used for OOP health care expenses the 10th, 50th, and 90th percentiles, adjusted for predisposing, enabling and health care need factors. A full set of coefficients for the model at the 50th percentile is shown in Table 4. At each expense percentile, the persistent disability group was estimated to have higher adjusted annual average total health care expenditures, OOP-spending, and ratios of OOP spending to family income than nondisabled adults. At the 50th percentile, the persistently disabled also exceeded the temporarily disabled for both total expenditures and the proportion of family income spent for OOP expenses. Temporarily disabled adults, while spending less than the permanently disabled in the 2 categories noted, generally experienced higher total expenses and proportion of
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296 Table 3 Estimated total and out-of-pocket expenditures and ratios of OOP to income at 10th, 50th, and 90th percentiles, adjusted for personal characteristics,c 2007e2008 MEPS 10th 50th 90th Disability status Total health care expenditures Intercept Disability status Temporary disability Persistent disability No disability (Ref. group) Out-of-pocket expenditures Intercept Disability status Temporary disability Persistent disability No disability (Ref. group) Ratios of OOP spending to family Intercept Disability status Temporary disability Persistent disability No disability (Ref. group)
Estimate
Estimate
Estimate
8.60
859.56
8088.57
112.57a 217.92a e
254.15a 1663.76a,b e
1.00 18.84a 23.48a e income 0.03
156.61
1115.09
62.93 155.56a e
188.43 456.42a e
1.26
0.03a 0.06a e
1603.08 7263.45a,b e
12.19
0.15a 0.58a,b e
0.04 1.85a e
Significantly different from the reference group, p ! 0.05. The persistent disability group significantly different from the temporary group, p ! 0.05. c Personal characteristics include gender, age, race, marital status, education, employment status, household income, insurance status, usual source of care, geographic location, place of residence, self-reported health status, chronic condition, and family size. a
b
family income consumed by OOP spending than did nondisabled adults. Differences among disability groups are visualized in Fig. 1, which shows excess adjusted total and OOP expenditures associated with disability, either persistent or temporary, compared to nondisabled adults. The graphic presentation clearly shows the varying effect of disability at different percentiles of overall health services use. At the lowest levels of overall use, differences are relatively small, but among high expenditure adults, disability effects are sizeable. Discussion Our findings both support earlier studies14,33 and add to the body knowledge about the effect of duration of physical disability on expenditures. We found that about 15% of working-age adults reported persistent disabilities and 7% had temporary disabilities. Adults with persistent disabilities, paralleling previous studies,34 were more economically vulnerable than nondisabled adults. In contrast, adults with temporary disabilities were similar to nondisabled adults in key socioeconomic characteristics, including education, income, and health insurance coverage. Adults with persistent disabilities had the greatest unadjusted annual medians for total expenditures, out-of-pocket
293
expenses, and financial burden ratios during 2007 and 2008. After adjusting for personal characteristics, estimated total expenditures, OOP expenses, and the proportion of family income spent as OOP expenses for persistently disabled persons were still far higher than those among nondisabled adults. Temporarily disabled adults also had higher estimated expenses than nondisabled persons, but at the middle of the distribution (50th percentile), persistently disabled persons had both higher total expenditures and financial burden ratios than the temporarily disabled. Individuals with persistent disabilities paid a lower percentage of their total expenditures OOP than did others, a finding consistent with previous research.28,35 This may be related to differences in health insurance status. Adults with persistent disabilities were more likely to be insured by public health insurance, which often provides coverage with low copayments.36 Conversely, the value of employer-based coverage has begun to erode over the last decade, leading to rapid premium growth and more costsharing.37 Despite better protection in terms of percent of expenditures met OOP, the adjusted median financial burden ratio among persistently disabled adults was higher than among their counterparts without disabilities. Adults with persistent disabilities seemed to be least protected from prescription drug costs, with persons who used medications spending 0.6% of total family income (median) for these products. Our findings suggest that caps on out-of-pocket spending could benefit permanently disabled individuals. Expenditure caps could be targeted to those with persistent disabilities who are most economically disadvantaged and have multiple chronic health conditions. Temporarily disabled working age adults constitute a demographically and clinically different population from those with permanent disability. They are more likely to be male, younger than 45 years, married rather than widowed/ divorced, with better education. With these resources, they are more likely to be employed, less likely to be poor, and more likely to be privately insured. They are a healthier population than the permanently disabled adults, as indicated by self-reported health status and number of chronic conditions. Nonetheless, their financial burden, as estimated at the median and adjusted for these demographic considerations, is higher than those of nondisabled individuals. Since most of the temporarily disabled have private health insurance, further research is needed to ascertain whether insurance characteristics, such as high deductibles or spending caps, are positively or negatively linked to financial burden. Several study limitations should be noted. First, MEPS does not include individuals who live in institutional settings, and thus our study does not address costs of these extremely disabled persons. Second, our definition of disability is relatively insensitive. We were able to measure functional, activity, and/or sensory limitations at only 2
294
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Table 4 Coefficients for all factors included in multivariable estimates for expenditures, OOP expenditures, and ratios of OOP spending to family income at 50th percentile, 2007e2008 MEPS Total health Out-of-pocket Ratios of OOP spending care expenditures expenditures to family income Characteristics Intercept Disability status (no disability) Temporary disability Persistent disability Gender (female) Male Age (age 18e44) Age 45e64 Race (White) Nonwhite Marital status (never married) Married Widowed/divorced/ separated Education (no degree) HS/ged BS/Post Hs/Grad Family size (1 person) 2 persons >3 persons Employment (unemployed) Employed Household income (poor/near poor) Low income Middle income High income Insurance status (uninsured) Any private Public insurance Usual source of care (no) Yes Geographic location (northeast) Midwest South West Residence (urban) Rural Self-reported health status (fair/poor) Good Excellent Chronic condition (no comorbidity) 1 comorbidity 2 comorbidities >3 comorbidities
Coefficient
95% CI
Coefficient
95% CI
Coefficient
95% CI
859.56
490.73e1228.38
156.61
73.13e240.09
1.26
0.98e1.54
254.15a 1663.76a,b
60.56e447.73 1254.01e2073.50
62.93 155.56a
7.84e133.70 87.61e223.51
0.15a 0.58a,b
0.02e0.27 0.39e0.78
465.50a
558.85e(372.15)
188.58a
122.11a
146.12e(98.10)
0.20a
59.40e317.77
113.10a
72.11e154.09
384.05e(192.38)
89.97a
117.28e(62.66)
0.10a
0.15e(0.06)
182.27a 95.74
84.28e280.26 261.71e70.22
19.43 41.98
8.72e47.58 96.29e12.33
0.01 0.08
0.05e0.03 0.06e0.23
93.17 250.63a
4.43e190.77 103.07e398.19
9.49 106.54a
17.81e36.78 69.40e143.69
86.40 391.98a
242.09e69.29 538.95e(245.01)
30.30 75.13a
75.16e14.57 112.52e(37.74)
0.39a 0.51a
0.52e(0.26) 0.64e(0.39)
249.40a
387.66e(111.14)
5.77
34.10e22.56
0.10a
0.15e(0.04)
103.30 80.43 337.76a
10.42e217.03 45.60e206.47 194.73e480.78
33.52a 41.53a 97.50a
1.12e65.92 10.12e72.93 55.76e139.24
0.10 0.18a 0.28a
0.22e0.02 0.31e(0.06) 0.41e(0.15)
369.11a 438.46a
272.46e465.76 188.10e688.83
18.38 112.95a
11.78e48.55 157.84e(68.06)
0.03 0.19a
0.02e0.07 0.29e(0.09)
339.82a
252.98e426.67
75.05a
46.72e103.38
0.12a
0.08e0.15
165.55a 162.33a 86.59
9.63e321.47 31.21e293.45 50.84e224.01
37.83 40.60a 25.56
6.25e81.91 1.58e79.61 16.48e67.59
0.07a 0.06a 0.03
0.02e0.12 0.01e0.12 0.02e0.08
62.74
177.24e51.76
16.81
47.53e13.90
0.01
0.03e0.05
397.13a 483.81a
678.84e(115.43) 772.87e(194.75)
40.11 59.97a
94.24e14.02 114.58e(5.36)
487.84a 1350.54a 3361.27a
363.50e612.18 902.45e1798.62 2616.92e4105.62
134.83a 278.56a 484.71a
103.21e166.46 196.36e360.76 328.23e641.19
288.22a
0.10a
0.23e(0.16)
0.07a 0.13a
0.37a 0.42a
0.19a 0.46a 1.21a
0.06e0.14
0.02e0.12 0.07e0.20
0.56e(0.19) 0.60e(0.23)
0.13e0.24 0.33e0.60 0.88e1.53
Reference categories in brackets. Significantly different from the reference group, p ! 0.05. b The persistent disability group significantly different from the temporary group, p ! 0.05. a
points over a 2-year period. This may not be an adequate representation of a respondent’s disability trajectory. Third, all definitions of disability are based on self-report, and
thus subject to problems in recall and reporting. Fourth, our analysis is restricted to persons with physical limitations; mental limitations may have similar or different
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
Fig. 1. Differences in annual total health care expenditures and out-ofpocket expenditures at 10th, 50th, and 90th percentiles after controlling for other factors, comparing persistently disabled adults and temporarily disabled adults with nondisabled adults, based on data from 2007 to 2008 Medical Expenditure Panel Survey.
implications. Next, our analysis averaged estimates over 2 years. Averaging could have underestimated the median expenditures for temporarily disabled adults during their year of disability. Finally, MEPS data on health conditions, health status, health insurance coverage, income, and employment are self-reported and, like disability status, may be subject to recall bias. In summary, our study is the first study using longitudinal data and quantile regression analyses to explore the impact of variations durations of disability over a 2-year interval on health care expenditures and financial burden. Our findings suggest that people who have disabling conditions for a long period have better financial protection against out of pocket health care expenses but still face high financial burdens because of their higher level of need for health care services and their socioeconomic disadvantage. The experience of temporarily disabled adults deserves further study to clarify needed policy interventions.
Acknowledgments The authors wish to express their appreciation to Andrew Ortaglia for his assistance in quantile regression analyses. The statements contained in this article are solely those of the authors and do not necessarily reflect the views or policies of their agencies.
References 1. Houtenville AJ, Ruiz T. Annual Disability Statistics Compendium: 2011. Durham, NH: University of New Hampshire, Institute on Disability; 2011. 2. Livermore G, Stapleton DC, O’Toole M. Health care costs are a key driver of growth in federal and state assistance to working-age people with disabilities. Health Aff (Millwood). 2011;30(9):1664e1672.
295
3. Institute of Medicine Committe on Disability in America. The Future of Disability in America. Washington, DC: National Academies Press; 2007. 4. Pobutsky AM, Hirokawa R, Reyes-Salvail F. Estimates of disability among ethnic groups in Hawaii. Californian J Health Promot. 2003;1(Special Issue):65e82. 5. Centers for Disease Control and Prevention (CDC). Prevalence and most common causes of disability among adultseUnited States, 2005. Morb Mortal Wkly Rep. 2009;58(16):421e426. 6. Foote SM, Hogan C. Disability profile and health care costs of Medicare beneficiaries under age sixty-five. Health Aff (Millwood). 2001;20:242e253. 7. Kinne S, Patrick DL, Doyle DL. Prevalence of secondary conditions among people with disabilities. Am J Public Health. 2004;94(3): 443e445. 8. Chevarley FM, Thierry JM, Gill CJ, Ryerson AB, Nosek MA. Health, preventive health care, and health care access among women with disabilities in the 1994e1995 National Health Interview Survey, Supplement on Disability. Womens Health Issues. 2006;16(6): 297e312. 9. Rasch EK, Magder L, Hochberg MC, Magaziner J, Altman BM. Health of community-dwelling adults with mobility limitations in the United States: incidence of secondary health conditions. Part II. Arch Phys Med Rehabil. 2008;89(2):219e230. 10. Wilber N, Mitra M, Walker DK, Allen D, Meyers AR, Tupper P. Disability as a public health issue: findings and reflections from the Massachusetts survey of secondary conditions. Milbank Q. 2002;80(2):393e421. 11. Lollar DJ. Public health and disability: emerging opportunities. Public Health Rep. 2002;117(2):131e136. 12. Simeonsson RJ, McDevitt LN. Issues in Disability & Health the Role of Secondary Conditions & Quality of Life. Chapel Hill, NC: Office on Disability and Health; 1999. 13. Sutton JP, DeJong G. Managed care and people with disabilities: framing the issues. Arch Phys Med Rehabil. 1998;79(10): 1312e1316. 14. Mitra S, Findley PA, Sambamoorthi U. Health care expenditures of living with a disability: total expenditures, out-of-pocket expenses, and burden, 1996 to 2004. Arch Phys Med Rehabil. 2009;90(9): 1532e1540. 15. Centers for Disease Control and Prevention (CDC). Racial/ethnic disparities in self-rated health status among adults with and without disabilitieseUnited States, 2004-2006. Morb Mortal Wkly Rep. 2008;57(39):1069e1073. 16. Rupp K, Davies PS, Strand A. Disability benefit coverage and program interactions in the working-age population. Soc Secur Bull Social Security Bull. 2008;68(1):1e30. 17. Dejong G, Palsbo SE, Beatty PW, Jones GC, Knoll T, Neri MT. The organization and financing of health services for persons with disabilities. Milbank Q. 2002;80(2):261e301. 18. Martin BI, Lee MJ, Turner JA, Mirza SK, Comstock BA, Deyo RA. Trends in health care expenditures, utilization, and health status among US adults with spine problems, 1997-2006. Spine (Phila Pa 1976). 2009;34(19):2077e2084. 19. WHO. International Classification of Functioning, Disability and Health (ICF). Available from: http://www.who.int/classifications/icf/ en/index.html; April 2011. 20. Wei W, Findley PA, Sambamoorthi U. Disability and receipt of clinical preventive services among women. Womens Health Issues. 2006;16(6):286e296. 21. Agency for Healthcare Research and Quality. MEPS HC-121: 2008 Full Year Consolidated Data File. Available from: http://www.meps. ahrq.gov/mepsweb/data_stats/download_data/pufs/h121/h121doc.shtml; July 2011. 22. Agency for Healthcare Research and Quality. MEPS-HC Summary Data Tables Technical Notes. Available from: http://www.meps.ahrq. gov/mepsweb/survey_comp/hc_technical_notes.shtml; July 2011.
296
C. Pumkam et al. / Disability and Health Journal 6 (2013) 287e296
23. Bennett KJ, Dismuke CE. Families at financial risk due to high ratio of out-of-pocket health care expenditures to total income. J Health Care Poor Underserved. 2010;21(2):691e703. 24. Paez KA, Zhao L, Hwang W. Rising out-of-pocket spending for chronic conditions: a ten-year trend. Health Aff. 2009;28(1): 15e25. 25. Agency for Healthcare Research and Quality. MEPS HC-113: 2007 Full Year Consolidated Data File. Available from: http://meps. ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPuf Number5HC-113; July 2011. 26. Andersen RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav. 1995;36(1):1e10. 27. Chan L, Ciol MA, Shumway-Cook A, et al. A longitudinal evaluation of persons with disabilities: does a longitudinal definition help define who receives necessary care? Arch Phys Med Rehabil. 2008;89(6): 1023e1030. 28. Newacheck PW, Inkelas M, Kim SE. Health services use and health care expenditures for children with disabilities. Pediatrics. 2004;114(1):79e85. 29. Egede LE, Zheng D, Simpson K. Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care. 2002;25(3):464e470.
30. Dodd S, Bassi A, Bodger K, Williamson P. A comparison of multivariable regression models to analyse cost data. J Eval Clin Pract. 2006;12(1):76e86. 31. Cook BL, Manning WG. Measuring racial/ethnic disparities across the distribution of health care expenditures. Health Serv Res. 2009;44(5 Pt 1):1603e1621. 32. Koenker R, Hallock KF. Quantile regression. J Econ Perspect. 2001;15(4):143e156. 33. Martin BI, Deyo RA, Mirza SK, et al. Expenditures and health status among adults with back and neck problems. JAMA. 2008;299(6): 656e664. 34. Iezzoni LI. Eliminating health and health care disparities among the growing population of people with disabilities. Health Aff (Millwood). 2011;30(10):1947e1954. 35. Riley GF, Lubitz JD, Zhang N. Patterns of health care and disability for Medicare beneficiaries under 65. Inquiry. 2003;40(1):71e83. 36. Shen Y-C, McFeeters J. Out-of-pocket health spending between lowand higher-income populations: who is at risk of having high financial burdens? Med Care. 2005;44(3):200e209. 37. Rowland D, Hoffman C, McGinn-Shapiro M. Health Care and the Middle Class: More Costs and Less Coverage. Menlo Park, CA: Henry J. Kaiser Family Foundation; 2009.