Value-based insurance design and medication adherence: opportunities and challenges.

Area of Science:

• Health economics
• Pharmaceutical policy
• Medication adherence research

Background:

• Value-based insurance design (V-BID) programs aim to improve healthcare access and outcomes by aligning patient costs with healthcare value.
• Medication adherence is a critical factor in managing chronic diseases and achieving desired therapeutic results.
• Evaluating the effectiveness of V-BID programs on medication adherence is essential for informing healthcare policy and program design.

Purpose of the Study:

• To critically assess the quality of existing evaluations of V-BID programs concerning medication adherence.
• To identify methodological weaknesses in current V-BID program evaluations.
• To delineate areas for future research to enhance V-BID policy development.

Main Methods:

• A comprehensive literature review was conducted using major healthcare and economic databases.
• Studies evaluating the impact of V-BID programs on medication adherence were systematically searched and analyzed.
• Methodological characteristics of V-BID programs that could introduce bias in effectiveness estimates were examined.

Main Results:

• Twenty studies involving 17 V-BID programs were reviewed, indicating a general improvement in medication adherence (average effect size of 3.4% after one year).
• Significant methodological limitations were identified, including insufficient reporting of baseline/final adherence rates and absolute adherence changes.
• Factors influencing effect sizes included program specifics, baseline adherence, disease category, and co-occurring disease management programs. Higher effect sizes were noted in industry-sponsored studies.

Conclusions:

• Many V-BID program evaluations exhibit a lack of methodological clarity and result transparency, with potential conflicts of interest influencing findings.
• Recommendations for future research include mandatory reporting of baseline/final adherence values alongside effect sizes.
• Ensuring consistent terminology, assessing bias from confounders, and rigorously eliminating alternative explanations are crucial for credible V-BID research.