ArticleJournal of health economics2019
Data transformations to improve the performance of health plan payment methods.
Article in Journal of health economics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A Microsimulation-Based Approach for Mitigating Societal Bias in Chronic Kidney Disease Data.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- A Machine Learning Model to Improve Risk Adjustment Accuracy in Medicare.Health services research · 2026Article
- Does Health-Based Prospective Risk Adjustment Adequately Compensate for Individuals Diagnosed With a New Chronic Disease?Medical care research and review : MCRR · 2026Article
- Impact of risk adjustment for drug-resistant types on tuberculosis patients' outcomes under China's innovative payment methods: a quasi-experimental study design.Infectious diseases of poverty · 2026Article
- A microsimulation-based framework for mitigating societal bias in primary care data.medRxiv : the preprint server for health sciences · 2025Article
- Unfairness toward rural beneficiaries in Medicare's hierarchical conditions categories score.Health affairs scholar · 2025Article
- Algorithms to Improve Fairness in Medicare Risk Adjustment.JAMA health forum · 2025Article
- Incorporating area-level social drivers of health in predictive algorithms using electronic health record data.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Supporting Primary Care for Medically and Socially Complex Patients in Medicaid Managed Care.JAMA network open · 2025Article
- Prediction of non emergent acute care utilization and cost among patients receiving Medicaid.Scientific reports · 2024Article
- Sex differences in care complexity and cost of cardiac-related procedures as a basis for improving hospital payments systems.The European journal of health economics : HEPAC : health economics in prevention and care · 2023Article
- Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets.Health economics review · 2023Article
- Risk Adjustment And Promoting Health Equity In Population-Based Payment: Concepts And Evidence.Health affairs (Project Hope) · 2023Article
- Disparities in Health Care Spending and Utilization Among Black and White Medicaid Enrollees.JAMA health forum · 2022Article
- Intersections of machine learning and epidemiological methods for health services research.International journal of epidemiology · 2021Article
- Improving the Performance of Risk Adjustment Systems: Constrained Regressions, Reinsurance, and Variable Selection.American journal of health economics · 2021Article
- Fair regression for health care spending.Biometrics · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
The conventional method for developing health care plan payment systems uses observed data to study alternative algorithms and set incentives for the health care system. In this paper, we take a different approach and transform the input data rather than the algorithm, so that the data used reflect the desired spending levels rather than the observed spending levels. We present a general economic model that incorporates the previously overlooked two-way relationship between health plan payment and insurer actions. We then demonstrate our systematic approach for data transformations in two Medicare applications: underprovision of care for individuals with chronic illnesses and health care disparities by geographic income levels. Empirically comparing our method to two other common approaches shows that the "side effects" of these approaches vary by context, and that data transformation is an effective tool for addressing misallocations in individual health insurance markets.
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