12 DEVELOPMENT AND EVALUATION OF AN ANALYTICAL POLICY TOOL

Thursday, October 18, 2012
The Atrium (Hyatt Regency)
Poster Board # 12
INFORMS (INF), Applied Health Economics (AHE)

Zhuo Yang, Masters, Joy Melnikow, MD, MPH, Dominique Ritley, MPH and Meghan Soulsby, MPH, Center for Healthcare Policy and Research, Sacramento, CA

Purpose:    Application of cost-effectiveness modeling to formulation of healthcare policy is limited by lack of accessibility, transparency, timeliness and relevance. This project aimed to engage stakeholders and researchers in a collaborative effort to create a usable, program-specific cost-effectiveness model to inform policymaking for a state safety-net breast cancer screening program.

Method:    Based on a micro-simulation cost effectiveness model, a prototype user-friendly version with interactive features, realized via Visual Basic programming, was developed. Priority policy questions addressed by the model were defined based on structured meetings with stakeholders in administrative, legislative, and advocacy positions. Evaluation of model usability, accessibility and relevance is being collected through individual interviews with 25-30 stakeholders. The final product will be available to decision makers and advocates to assess the potential impact of program policies.

Result:    The model synthesized clinical evidence (from review of published clinical trials), program-specific data (from analysis of program claims data) and allowed structured user-selected inputs.. The current version allows the user to customize the cost-effectiveness analysis by selecting program length, screening frequency and age eligibility. The interface also incorporated stakeholder suggestions (e.g., new screening technologies, budget issues, impact of ACA) when feasible. The model includes an option for budget-constrained cost-effectiveness analysis which identifies the most efficient budget allocation strategy under a fixed annual budget. Feedback on the clarity and usability of the model from individual interviews will lead to further modifications. In the next phase, we will collect data on use of the model for policy formulation.

Conclusion:    This innovative approach aims to bridge the gap between evidence-based research and healthcare policy making. We anticipate this user-friendly model will facilitate the process of delivering timely, accessible and relevant evidence to policy stakeholders.  Our methods can be generalized to other public health policy areas.