2025/11/03 by Xiyue Liao, Ian Duncan, Liao, Xiyue +3
Economics, Econometrics and Finance · Mathematics · Medicine · #Advanced Causal Inference Techniques #Chronic Disease Management Strategies #FOS: Economics and business #General Economics (econ.GN) #Healthcare Policy and Management
paper · pdf · doi:10.48550/arxiv.2511.08603
openalex publication_date 2025/11/03 · openalex created_date 2025/11/14 · openalex updated_date 2026/07/28
We seek to identify the most relevant benefits offered by Medicare Advantage Health Plans that drive membership and market share. As an example, we explore plans operating in a single county in New Jersey between 2018 and 2023. A dataset of benefits from publicly available data sources was created and the variance inflation factor was applied to identify the correlation between the extracted features, to avoid multicollinearity and overparameterization problems. We categorized the variable Market Share and used it as a multinomial response variable with three categories: less than 0.3%, 0.3% to 1.5%, and over 1.5%. Categories were chosen to achieve approximately uniform distribution of plans (47, 60, and 65 respectively). We built a multinomial Lasso model using 5-fold cross-validation to tune the penalty parameter. Lasso forced some features to be dropped from the model, which reduces the risk of overfitting and increases the interpretability of the results. For each category, important variables are different. Certain brands drive market share, as do PPO plans and prescription drug coverage. Benefits, particularly ancillary benefits that are not part of CMS's required benefits, appear to have little influence, while financial terms such as deductibles, copays, and out-of-pocket limits are associated with higher market share. Finally, we evaluated the predictive accuracy of the Lasso model with the test set. The accuracy is 0.76.