Background
Methods
Search strategy
Inclusion and exclusion criteria
Analysis of data
Study
|
Sample
|
Study Design
|
Outcomes
|
---|---|---|---|
Adams, Soumerai, & Ross-Degnan, 2001a | 4439 Medicare beneficiaries with hypertension | national longitudinal survey (MCBS 1995); inferential statistic | Association between types of drug coverage, consumption & costs per tablet; Findings: income |
Blustein, 1995a | 4110 female Medicare beneficiaries | probability survey based on multistage, stratified cluster sample of Medicare (MCBS 1991-1992); multiple inferential statistic | Use of mammography during first 2 years of Medicare offered benefit; Findings: income, education |
Blustein, 2000b | 4334 Medicare beneficiaries with hypertension | nationally-representative face-to-face survey of Medicare; multiple inferential statistic | Sexual differences in burden for prescription drugs; Findings: sex |
Chandra et al., 2007 | 70912 CalPers plan members | Panel of Medicare supplemental plan Members (CalPers 2000-2003); multiple inferential statistic | Influence & consequences of price elasticity in patient cost-sharing; Findings: income |
Crystal, Johnson, Harman, Sambamoorthi, & Kumar, 2000b | 7886 Medicare beneficiaries | nationally representative survey of Medicare, stratified, multistage, area probability sample (MCBS 1995); multiple inferential statistic | Overview on size, distribution & burden of OOPP; Findings: income, education |
Davis, Poisal, Chulis, Zarabozo, & Cooper, 1999a | 12.000 Medicare beneficiaries | Panel Survey (MCBS 1995); descriptive | Overview on sources & extent of drug coverage among Medicare beneficiaries; Findings: income |
Dowd et al., 1994a | 2891 Medicare HMO & fee-for-service members | Survey; multiple inferential statistic | Characteristics of Medicare beneficiaries & influence on choice of health plan; Findings: income |
Fahlman, Lynn, Doberman, Gabel, & Finch, 2006d | 4602 Medicare beneficiaries | Cross-sectional, retrospective review & 1990 Census data; multiple inferential statistic | Drug spending by disease & demographics in last year of life; Findings: income |
Gellad, Huskamp, Phillips, & Haas, 2006a | 5596 Medicare beneficiaries | Panel Survey, nationally representative sample (MEPS-HC 1996-2000); multiple inferential statistic | Estimation of change of OOPP for drugs after Part D implementation; Findings: income |
Goldman & Zissimopoulos, 2003b | 7836 Medicare beneficiaries | Cross sectional survey of 4th wave of Panel survey (HRS 1998); inferential statistic | Examination of OOPP health-care spending; Findings: income |
Guidry, Aday, Zhang, & Winn, 1998b | 593 Texan cancer patients | analytical cross-sectional survey; inferential statistic | Prevalence of barriers to cancer treatment; Findings: income |
Hwang, Weller, Ireys, & Anderson, 2001a | 22.326 patients with chronic condition | cross-sectional survey (MEPS 1996); descriptive | Impact of chronic condition & demographics on OOPP spending; Findings: sex |
Klein, Turvey, & Wallace, 2004i | 6535 participants of AHEAD-study | cross-sectional study of 2nd wave of AHEAD study 1997; inferential statistic | Reasons for delay in medication use because of cost; Findings: income, sex |
Lapsley, March, Tribe, Cross, & Brooks, 2001a | 113 patients with osteo-arthritis in Australia | prospective-cohort study; inferential statistic | OOPP expenditures related to osteo-arthritis; Findings: sex |
McGarry & Schoeni, 2005b | 3821 >70 years old Americans (271 widowers, 3550 married) | national panel survey (2 Waves) (HRS); descriptive | Financial gap between widowed and married Elders; Findings: sex |
Miller & Champion, 1993a | 161 women | convenience sample, mailed survey; inferential statistic | Relationship of patient's characteristics and mammography utilization; Findings: income, education |
Mitchell, Mathews, Hunt, Cobb, & Watson, 2001a | 499 patients with at least one regular prescription medication | cross-sectional survey; mutliple inferential statistic | extent of mismanaging of prescription drugs among rural Elders; Findings: income |
Mojtabai & Olfson, 2003c | 10.413 Medicare beneficiaries | cross-sectional (HRS 2000); multiple inferential statistic | Association between drug coverage & adherence; cost-related poor adherence & health outcomes; Findings: income |
Ness, Cirillo, Weir, Nisly, & Wallace, 2005b | 1099 participants of HRS study | cross-sectional (HRS 2000); inferential statistic | Correlates of complementary & alternative medicine (CAM) utilization among Elders; Findings: sex |
Pourat, Rice, Kominski, & Snyder, 2000d | 15.103 Medicare beneficiaries | cross-sectional (MCBS 1996); inferential statistic | Comparison of supplemental insurances to examine impact of socioeconomics; Findings: income, education |
Rector & Venus, 2004a | 1500 Medicare+Choice plan beneficiaries | cross-sectional, random sample in eight Medicare+Choice Plans; inferential statistic | Influence of drug benefits on affordability for beneficiaries; Findings: income |
Rice & Desmond, 2006e | 9278 Medicare beneficiaries | cross-sectional (SIPP 2001); descriptive | Number and characteristics of Medicare beneficiaries excluded from low-income subsidies because of failed asset test; Findings: education, sex |
Riley, 2008b | 4000 Medicare beneficiaries at a time | panel 4 waves (MCBS 1992, 96, 2000, 04); inferential statistic | Trends in OOPP health-care costs for MediCare beneficiaries; Findings: income |
Rogowski, Lillard, & Kington, 1997b | 996 Elders | cross-sectional (PSID 1990); multiple inferential statistic | Amount & influence of supplemental insurance on burden of prescription drug OOPP costs; Findings: income, education, sex |
Sambamoorthi, Shea, & Crystal, 2003b | 8814 Medicare beneficiaries | cross-sectional (MCBS 1997); multiple inferential statistic | Total and OOPP burden for prescription drugs in relation to characteristics of elderly population; Findings: income, education |
Saver, Doescher, Jackson, & Fishman, 2004d | 4492 Medicare+Choice enrollees | cross-sectional survey and administrative data from Medicare, 2000; multiple inferential statistic | Relationship between drug benefit status & access to medications + influence of income; Findings: income, education |
Selden & Banthin, 2003b | 5733 (1987), 2549 (1996) >65 years old beneficiaries | stratified random samples (NMES 1987 and MPES 1996), longitudinal; descriptive | Amount health-care burden for Elders; Findings: income, sex |
Soumerai et al., 2006a | 13.835 Medicare beneficiaries | stratified, multistage sample (MCBS 2004), cross-sectional; multiple inferential statistic | Prevalence of cost-related medication non-adherence prior to Medicare Part D; Findings: income |
Wei, Akincigil, Crystal, & Sambamoorthi, 2006a | 76.440 person-years (30.375 beneficiaries) of Medicare beneficiaries | longitudinal (MCBS 1992-2000); multiple inferential statistic | Gender differences in OOPP expenditures & burden for medication; Findings: sex |
Presentation of findings
Results
Reviewed Articles
Study
|
Key findings
|
Confounders controlled for
|
---|---|---|
Adams, Soumerai, & Ross-Degnan, 2001a | high income > good insurance > lower OOPP > higher drug consumption | none |
Blustein, 1995a | low income > less probability of mammography | age, race, education, self-rated health status, total Medicare Part B reimbursement in 1991, smoking status, living arrangement |
Chandra et al., 2007 | low income > high price elasticity > increased hospital visits due to less prevention | type of insurance plan, age, spending tercile, Charlson Index, health status |
Crystal, Johnson, Harman, Sambamoorthi, & Kumar, 2000b | average OOPP burden: 19% (lowest quintile: 31.5%, top quintile: 8.5%) | sex, race, age, education, marital status, self-reported health status, number of medical conditions, number of ADL & IADL impairments, insurance coverage |
Davis, Poisal, Chulis, Zarabozo, & Cooper, 1999a | high income > best insurance > lowest OOPP | none |
Dowd et al., 1994a | high income > best insurance > lowest OOPP | age, sex, marital status, education, living arrangements, number & proximity of living children, health insurance, self-reported health condition |
Fahlman, Lynn, Doberman, Gabel, & Finch, 2006d | high income > high utilization & OOPP | race, sex, Charlson Index, age, insurance type |
Gellad, Huskamp, Phillips, & Haas, 2006a | Medicare Part D > general cost decline, but: high incomes advantaged through lower burden in Donut Hole | race, chronic conditions, insurance coverage |
Goldman & Zissimopoulos, 2003b | high income > high absolute OOPP, but lower burden (highest quartile: 1% OOPP of income, lowest: 17% (up to 43%); hardest hit: those shortly above limit of Medicaid support) | none |
Guidry, Aday, Zhang, & Winn, 1998b | disadvantages for minorities (lower income, bad insurance, higher costs, less treatments) | none |
Klein, Turvey, & Wallace, 2004i | low income > bad insurance > high OOPP > less prevention > more illnesses > more OOPP > more cost-reducing strategies > high follow-up costs (each +100$/month OOPP > +10% of unregular use) | none |
Miller & Champion, 1993a | high income > high utilization & drug adherence | none |
Mitchell, Mathews, Hunt, Cobb, & Watson, 2001a | less income > less medication adherence due to OOPP > worse health status & less health consciousness > higher OOPP > less adherence | age, race, education, residential status, health status, medication profile |
Mojtabai & Olfson, 2003c | lower income > less adherence | age, sex, race, education, marital status, employment, insurance coverage |
Pourat, Rice, Kominski, & Snyder, 2000d | low income > less supplemental prescription drug coverage > high OOPP | none |
Rector & Venus, 2004a | low income > more cost induced delay or stop of medication utilization (<$1000 monthly household income: 38%, >$4000: 17%) | none |
Riley, 2008b | 1992-2004: absolute OOPP up by 22.5%; highest burden: second lowest quartile > no Medicaid | none |
Rogowski, Lillard, & Kington, 1997b | low income > higher expenditures & higher burden: 5,4-5,9%, middle income: 1.6%, highest income: 0,6%; insurance coverage reduces amount spent by 50%; cost distribution highly skewed: 55% spend 1% or less, 1% spend 25% of yearly income | age, sex, race, education, residential status, marital status, insurance coverage, health status |
Sambamoorthi, Shea, & Crystal, 2003b | Absolute OOPP nearly equal, but: low income > higher burden (+10% burden: <200% of poverty level: 13.4%, >200%: 2.4%) | sex, race, age, education, marital status, insurance coverage, self-rated health status, place of residence |
Saver, Doescher, Jackson, & Fishman, 2004d | high income > higher probability of drug benefit (25% vs. 17%) > more adherence | age, race, sex, education, household configuration, insurance coverage, self-rated health status |
Selden & Banthin, 2003b | lower income > higher burden: +40% burden 1987 (1996) (below poverty line: 20.9% (19.6%), >200% of p.l.: 3.8% (4.8%)) | none |
Soumerai et al., 2006a | low income > less drug adherence (<$10.000 yearly income: 14.5%, >$40.000: 8.7%) | sex, age, race, education, self-rated health status, insurance coverage |
Study
|
Key findings
|
Confounders controlled for
|
---|---|---|
Blustein, 1995a | low education > less probability of mammography | age, race, income, self-rated health status, total Medicare Part B reimbursement in 1991, smoking status, living arrangement |
Crystal, Johnson, Harman, Sambamoorthi, & Kumar, 2000b | OOPP burden with no high school: 21.4%, college degree: 12.8% | gender, race, age, income, marital status, self-reported health status, number of medical conditions, number of ADL & IADL impairments, insurance coverage |
Miller & Champion, 1993a | college degree significant for mammography & physician visits > less OOPP burden in the long-term | none |
Pourat, Rice, Kominski, & Snyder, 2000d | better education > better insurance > less OOPP | none |
Rice & Desmond, 2006e | higher education than lowest income group > income above Medicaid limit > same OOPP as high income group, but less education & income; higher OOPP than subsidy group for having higher education & income | none |
Rogowski, Lillard, & Kington, 1997b | better education > less OOPP burden (higher income, better insurance): >12 years: 1.6%, <12 years: 4.5% | age, sex, race, income, residential status, marital status, insurance coverage, health status |
Sambamoorthi, Shea, & Crystal, 2003b | less education > higher OOPP (over 10% of burden without high school degree: 12.1%, college: 3.9%) | gender, race, age, income, marital status, insurance coverage, self-rated health status, place of residence |
Saver, Doescher, Jackson, & Fishman, 2004d) | better education > more prescription drug coverage > less OOPP | age, race, sex, income, household configuration, insurance coverage, self-rated health status |
Study
|
Key findings
|
Confounders controlled for
|
---|---|---|
Blustein, 2000b | women > rather poor (26% below poverty line, men: 11%); less employed > less insurance coverage > higher OOPP (18% higher than men for drugs) | age, race, education, self-rated health status, insurance coverage |
Fahlman, Lynn, Doberman, Gabel, & Finch, 2006d | women > higher OOPP in last year of life ($668 vs. $586) | race, income, Charlson Index, age, insurance type |
Hwang, Weller, Ireys, & Anderson, 2001a | women > longer lifespan > higher probability of comorbidities > higher OOPP | none |
Klein, Turvey, & Wallace, 2004i | women > higher OOPP > more cost-reducing strategies | none |
Lapsley, March, Tribe, Cross, & Brooks, 2001a | women > higher OOPP for drugs & devices | none |
McGarry & Schoeni, 2005b | women > longer lifespan > more widowhood; lowest income quartile (<$12.000): 70% of income spent in final two years for health-care (average: 30%); poverty rate: widows 17%, married Elders: 5% | none |
Ness, Cirillo, Weir, Nisly, & Wallace, 2005b | women > more CAM utilization > higher OOPP | none |
Rice & Desmond, 2006e | women > longer lifespan: partner dies > income plummets >heir above limit > no subsidies > old-age poverty; of 46% widowers failing asset test > 46% female | none |
Rogowski, Lillard, & Kington, 1997b | women > equal expenditures, but higher burden (3.3% vs. 2.8%) | age, income, race, education, residential status, marital status, insurance coverage, health status |
Sambamoorthi, Shea, & Crystal, 2003b | women > higher OOPP (over 10% of burden > women 9.4%, men 5.7%) | income, race, age, education, marital status, insurance coverage, self-rated health status, place of residence |
Selden & Banthin, 2003b | women > higher burden (over 20% of burden 1987 (1996): 19.6% (19.8%), men: 12.7% (15.9%) | none |
Wei, Akincigil, Crystal, & Sambamoorthi, 2006a | women > lower income, more utilization, higher absolute OOPP, higher burden; gender-specific illnesses > less generous benefits > higher OOPP | race, age, marital status, education, place of residence, poverty status, insurance coverage, health status |