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The Impact of Cost Sharing on Middle-Income Children AcademyHealth Annual Research Meeting June 2008 Amy M Lischko. Today’s agenda. Background and policy relevance Research questions Methodology Results Conclusions and policy implications Limitations and future research Questions.
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The Impact of Cost Sharing on Middle-Income ChildrenAcademyHealthAnnual Research MeetingJune 2008Amy M Lischko
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions
Background and policy relevance • Consumer-driven health plans require engagement of consumers in their health care decision-making. • Increased and differential cost sharing is being used by health plans to direct patients to more “efficient” use of health care services. • RAND HIE remains the gold standard, however results may be outdated. Medicine, the delivery of health care, insurance plans, and peoples’ beliefs about health care have changed dramatically since the late 1970’s. • Little published literature on whether and how privately insured employees change their utilization of health services when increases are made to cost sharing.
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions
Research questions • What is the impact of increased cost sharing on utilization of health care services? • Are there differences in response by age, income or health status? • Are there differences in the responses to increases in cost sharing by type of service? • Do any offsets occur due to responses to increases in cost sharing?
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions
Study design State employees <65 with 5+ continuous years in any GIC health plan (n = 73,476) Claims drawn for employees and dependents (n = 124,045) Claims for 3 yrs used (2002-04).Eliminated 13,950 members (employees and dependents) who changed plans (final n = 110,095). Difference-in-difference and trend models are used depending on service Claims were collapsed by plan for each month (8 * 36) = 288 observations.
Summary* of changes to cost sharing *Changes are more complex in some cases but difficult to display on single chart
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions
Characteristics of sample % Respondents * Education < College 14.0 College 48.8 >College 37.2 Age 18-24 0 25-34 6.0 35-44 24.4 45-54 41.1 55-64 28.5 Household Income < $45,000 12.8 45-$75,000 32.5 75 - $105,000 30.5 >$105,000 24.2 Married 63.8 Race White 84.0 Black 6.6 Other 9.4 Any Chronic Disease No 53.2 Yes 46.8 Children Any 51.3% Average number 1.9 Work status Full-time 94.3% Avg. years with state 18 Union position 71% * Respondents who changed plans are not included
Results (1 of 2) Research question • What is the impact of increased cost sharing on utilization of health care services? Type of Service Coef. se p-value Mental Health visits 02-03 -.0035 .0016 0.02* Mental Health visits 03-04 0.001 .0015 0.49 Outpatient Surgery -.0108 .0073 0.14 • Inpatient LOS .0009 .0013 0.46 • Coefficients are from difference-in-difference models • Type of Service Coef. se p-value • Office visits -.0018 .0009 0.047* • Emergency Dept. visits -.0000085 .0022 0.6 Coefficients are from linear trend models
Results (2 of 2) Research question • Are there differences in the responses to increases in cost sharing by type of service, age, income or health status? Age 0-18 19-34 35-64 Type of Service Mental Health visits 02-03 .0055*** .0017 -.007*** Mental Health visits 03-04 .0200*** -.007** .002 Outpatient Surgery -.005 -.0143 -.0129 • Inpatient LOS .0006 .0064 -.0013 • Coefficients are from difference-in-difference models • Type of Service • Office visits -.004* .0003 -.0027 • Emergency Dept. visits -.00005* .00006* .000014 Coefficients are from linear trend models
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions
Conclusions and policy implications • Increases made to cost sharing did not deter most utilization • Similar results across income and health status • Reduction in office visits for children • No significant offsets in utilization were found More work needs to be done to study whether observed decreased utilization among children affected health outcomes. More targeted cost-sharing arrangements may be advisable.
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions
Limitations Underlying trends in utilization may confound Adverse selection or retention in plans Omitted variables GIC population may have some problems with external validity Massachusetts’ unique health care environment Future research What services are being reduced for children? Is there an impact on outcomes? How do parents make decisions about children’s healthcare utilization? How do they balance physician orders with convenience and economic incentives? Limitations and future research
Today’s agenda • Background and policy relevance • Research questions • Methodology • Results • Conclusions and policy implications • Limitations and future research • Questions