NEAIC Cost Evaluation (presented by Robin Clark)
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Presentation on the planned cost analysis of the NEAIC intervention by Robin Clark, PhD. (Presented at the annual meeting of the New England Asthma Innovations Collaborative, June 13, 2013, Shrewbury, MA)
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Quality and Performance.docx
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Permission required for use and distribution. Please contact Christine Gordon at cgordon@hria.org for more details.
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NEAIC Cost Evaluation (presented by Robin Clark)
- 1. Evaluating the Impact of NEAIC Interventions on Healthcare Costs Robin Clark, PhD Director of Research & Evaluation Center for Health Policy & Research
- 2. What are the ideal questions? Did NEAIC interventions improve children’s health? How did NEAIC interventions affect healthcare costs? How much did it cost to improve health outcomes?
- 3. Compared to what? • Doing nothing? • Another new treatment? • Treatment as usual?
- 4. Types of Economic Evaluations • • • • Cost-effectiveness Cost benefit Return on investment Cost
- 5. Types of Economic Evaluations Cost-effectiveness Cost benefit Compare change in costs and change in outcomes Return on investment Compares change in cost Cost Measures change in cost
- 6. Cost-effectiveness is preferred …. but it requires cost and outcome data for a comparison group cost comparisons can be derived from medical claims
- 7. Return on Investment Analysis: Healthcare Payer Perspective Intervention Group Comparison Group Healthcare Costs Healthcare Costs Difference Change Change Before After Before After
- 8. What costs are included? • The cost of the NEAIC intervention • The cost of other healthcare that study participants used • Measured from a public insurer perspective
- 9. Creating a comparison group 1. Use Medicaid claims to identify a group of children with asthma who are similar to the intervention group 2. Match the groups on demographics, diagnoses, clinical risk and service use history 3. Create a 1 to 1 or 1 to 2 match.
- 10. Why bother? • A comparison group helps answer the question “What would have happened if we had not intervened?” • Helps to rule out some alternative explanations for change (e.g. regression to the mean.)
- 11. Other possibilities: • Collect original outcome data for a comparison group (expensive) • Derive hypothetical change measures from another study with a similar population (some challenges)