Access to Care, Expenditures, and Productivity in Survivors of Adolescent and Young Adult Cancers
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1 Access to Care, Expenditures, and Productivity in Survivors of Adolescent and Young Adult s July 15, 2013 Robin Yabroff, Ph.D. Health Services and Economics Branch Division of Control and Population Sciences National Institute yabroffr@mail.nih.gov
2 Survivorship and Access to Care, Healthcare Expenditures, and Productivity s can experience lasting effects of treatment and increased risk for additional cancers and chronic conditions Compared to individuals without a cancer, cancer s may experience greater: Disparities in access to care and use of preventive services by insurance type Healthcare expenditures Health limitations Limitations in amount or kind of work and days lost from work
3 Survivors of Adolescent and Young Adult s Less research has focused on socioeconomic outcomes of s of adolescent and young adult (AYA) cancers Goal of talk: Adapt several recent studies using national data to focus on s of AYA cancers compared to individuals without a cancer Access to care Healthcare expenditures Productivity losses (e.g., health related unemployment, missed work)
4 Medical Expenditure Panel Survey (MEPS) Annual survey with overlapping panel design, sample selected from National Health Interview Survey Conducted by Agency for Healthcare Research & Quality Nationally representative Approximately 13,000 households and 32,000 individuals Average annual response rate approximately 60% Topics include Health status Access to care Health insurance Healthcare utilization and expenditures
5 Survivors of Adolescent and Young Adult s in the MEPS 3 years of MEPS Household Component ( ) Did a doctor or other health professional ever tell cancer or malignancy of any kind Prevalent sample Sample ages at time of the survey s: diagnosed at ages Comparison group: never diagnosed with cancer
6 Survivors of Adolescent and Young Adult s in the MEPS Evaluated the association between cancer ship and Access to care Expenditures Productivity (e.g., health related unemployment, missed work) Multivariate regression analyses controlled for age, gender, marital status, and number of comorbid conditions Reported predicted margins (adjusted percentages)
7 Characteristics of Survivors of AYA s and Individuals without a History Survivor No History (N = 882) (N=55,972) Wtd % Wtd % p-value Age group Sex Male <.0001 Female Race / ethnicity Non-Hispanic white <.0001 Non-Hispanic black Hispanic Non-Hispanic other Data source: Medical Expenditure Panel Survey (MEPS); Limited to individuals ages either diagnosed with cancer at ages or never diagnosed with cancer
8 Characteristics of Survivors of AYA s and Individuals without a History Wtd % Wtd % p-value Health insurance Any private <.0001 Public only Uninsured Number of known MEPS priority conditions, excluding cancer < Data source: Medical Expenditure Panel Survey (MEPS); Limited to individuals ages either diagnosed with cancer at ages or never diagnosed with cancer
9 Adjusted percentage Usual Source of Care, by Type of Health Insurance Any private insurance Public insurance only Uninsured p<0.0001; Multivariate logistic regression analyses with estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity, marital status. Data source: Medical Expenditure Panel Survey Source: Adapted from Yabroff KR, Short PF, Machlin S, Dowling E, Rozjabek H, Li C, McNeel T, Ekwueme DU, Virgo KS Access to preventive healthcare for cancer s. Am J Prev Med, in press.
10 Adjusted percentage Recent Dental Visit, by Type of Health Insurance Any private insurance Public insurance only Uninsured p<0.0001; Multivariate logistic regression analyses with estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity, marital status. Data source: Medical Expenditure Panel Survey Source: Adapted from Yabroff KR, Short PF, Machlin S, Dowling E, Rozjabek H, Li C, McNeel, Ekwueme DU, Virgo KS Access to preventive healthcare for cancer s. Am J Prev Med, in press.
11 Adjusted percentage Unable to Get or Delayed Necessary Medical Care, Dental Care, or Prescription Medication P<0.001; Multivariate logistic regression analyses with estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity, marital status. Data source: Medical Expenditure Panel Survey Source: Adapted from Yabroff KR, Short PF, Machlin S, Dowling E, Rozjabek H, Li C, McNeel T, Ekwueme DU, Virgo KS Access to preventive healthcare for cancer s. Am J Prev Med, in press.
12 Adjusted percentage Unable to Get or Delayed Necessary Medical Care, Dental Care, or Prescription Medication, by Type of Health Insurance Any private insurance Public insurance only Uninsured p<0.0001; Multivariate logistic regression analyses with estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity, marital status. Data source: Medical Expenditure Panel Survey Source: Adapted from Yabroff KR, Short PF, Machlin S, Dowling E, Rozjabek H, Li C, McNeel T, Ekwueme DU, Virgo KS Access to preventive healthcare for cancer s. Am J Prev Med, in press.
13 Adjusted percentage Impact of Delayed or Lack of Access to Medical Care, by Type of Health Insurance 100% 80% 60% Not a problem / missing 40% 20% A small problem A big problem 0% Any private insurance Public insurance only Uninsured p<0.0001; Multivariate logistic regression analyses with estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity, marital status. Data source: Medical Expenditure Panel Survey Source: Adapted from Yabroff KR, Short PF, Machlin S, Dowling E, Rozjabek H, Li C, McNeel T, Ekwueme DU, Virgo KS. Access to preventive healthcare for cancer s. Am J Prev Med, in press.
14 Mean Annual Expenditures (in 2010 US dollars) Survivors $8,348 (95% CI: $6,078-10,618) Individuals without a History $4,295 (95% CI: $4,172-$4,417) Ambulatory Care Inpatient Care Prescription Medications Other Services p<0.0001; Generalized linear regression analyses with a gamma distribution and a log link. Estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity. Data source: Medical Expenditure Panel Survey Source: Guy GF, Yabroff KR, et al. The health and economic burden of adolescent and young adult cancer ship in the United States.
15 Adjusted percentage Limited in Kind of Work or Activities Because of Physical Health in Past 4 Weeks 100% % % All or most of the time 40% Some of the time Little or none of the time 20% 0% p< Multivariate logistic regression analyses with estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity, marital status. Data source: Medical Expenditure Panel Survey Source: Adapted from Dowling EC, Chawla N, Forsythe LP, de Moor J, McNeel T, Rozjabek HM, Ekwueme DU, Yabroff KR. Lost productivity and burden of illness in cancer s and individuals with and without other chronic conditions., in press.
16 Percent unable to work due to illness/injury Lost Productivity Survivors Adjusted estimate (95% CI) Individuals Without a History Adjusted estimate (95% CI) P-value 11.5 ( ) 5.4 ( ) <0.001 Missed work days among employed 4.4 ( ) 3.3 ( ) 0.02 Lost household productivity days 11.4 ( ) 3.8 ( ) <0.001 Regression analyses varied by outcome type. Estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity. Data source: Medical Expenditure Panel Survey Source: Guy GP Jr, Yabroff KR, et al. The health and economic burden of adolescent and young adult cancer ship in the United States.
17 Mean Annual Lost Productivity (in 2010 US dollars) Survivors $4,769 (95% CI: $3,825-$5,683) Individuals without a History $2,296 (95% CI: $2,164-$2,458) Health related unemployment Missed work days among employed Lost household productivity p<0.001; Generalized linear regression analyses with a gamma distribution and a log link. Estimates reported as predicted margins and controlling for the effects of age, number of comorbid conditions, gender, race/ethnicity. Data source: Medical Expenditure Panel Survey Source: Guy GP Jr, Yabroff KR, et al. The health and economic burden of adolescent and young adult cancer ship in the United States.
18 Summary of Findings Compared to individuals without a cancer, s of AYA cancers are more likely to: be unable to get or delayed necessary medical care have higher medical expenditures experience greater physical limitations, healthrelated unemployment and productivity losses Disparities in access to care for publicly insured or uninsured s of AYA cancers Prevalent sample of cancer s, many 5 or more years after diagnosis. Individuals with short survival cancers under-represented
19 Considerations when Using the MEPS to Evaluate Outcomes in Survivors Strengths Nationally representative Adults of all ages Comparison group of individuals without cancer Expenditures from all payers, including out-of-pocket Limitations Small number with specific cancer or newly diagnosed in any year Information on cancer diagnosis is self-reported, no details about stage, cancer treatment Measures are for relatively short periods, no information on long-term trajectories
20 Future Directions Evaluation of socioeconomic outcomes in s with specific cancers specific treatments Ongoing evaluation of access to care and aspects of health insurance (e.g., coverage caps, co-pays) with implementation of the Affordable Care Act (ACA) Investigation of related topics Financial burden (e.g., medical debt) Impact on caregiver and family -related morbidity in relation to access, employment and economic outcomes Care coordination
21 Future Directions Greater utilization of existing data, research resources, novel data linkages, and enhancements Research Network (CRN) Hospital and ambulatory care discharge data linked to registry data Novel linkages (multiple payer and registry, bankruptcy claims and registry) Enhancement of existing surveys with access, productivity, utilization, and expenditure items Supplemental surveys
22 MEPS Experiences with Survivorship Supplement Collaborative effort with NCI, AHRQ, CDC, ACS, OBSSR, LIVESTRONG Foundation Oversampled households with cancer s from the 2010 NHIS ( Control Supplement) Added special survey for cancer s Items related to: Changes in work because of cancer Changes in caregiver work because of cancer Financial burden Limitations in activities because of cancer
23 MEPS Experiences with Survivorship Supplement Survey completed by about 1500 cancer s (92% response rate) Survey also fielded by LIVESTRONG Foundation with more than 6,000 respondents MEPS data publicly available September 2013 LIVESTRONG Foundation data available by application in
24 Acknowledgements National Institute (Emily Dowling, Neetu Chawla, Laura Forsythe, Janet de Moor, Heather Rozjabek, Ashley Wilder Smith) Centers for Disease Control and Prevention (Gery Guy, Donatus Ekwueme, Juan Rodriguez, Lisa Richardson) American Society (Katherine Virgo) Massachusetts General Hospital (Emily Dowling) LIVESTRONG (Ruth Rechis, Stephanie Nutt) Agency for Healthcare Research & Quality (Steven Machlin, Anita Soni, Amy Davidoff) Information Management Services, Inc (Timothy McNeel)
25 Thank You!
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