Agent-Based Modeling for Competition in Health Markets with a focus on Accountable Care Organizations in the United States

Elucidating the intricate dynamics of health care markets, offering groundbreaking insights into insurer-provider bargaining, competitive regulations, and the potential implications of health reforms on market competition in the context of accountable care models

An Agent-based Simulation Model of Patient Choice of Health Care Providers in Accountable Care Organizations

With Shinyi Wu

Published in Health Care Management Science and presented at Academy Health’s Annual Research Meeting 2015

  • The rise of Accountable Care Organizations (ACO) in the U.S. seeks to balance health care costs with patient provider choice, but the implications of choosing distant, higher-quality care remain unclear.

  • An innovative agent-based simulation model was developed, focusing on Medicare beneficiaries and their congestive heart failure (CHF) outcomes within an ACO system.

  • Providers in this model weigh their ACO participation and the rollout of CHF management interventions.

  • Results find that patient choice can save $320 annually per CHF patient, reduce mortality rates by 0.12%, and decrease hospitalizations by 0.44%.

  • The model also indicates a slight uptick in provider ACO participation.

  • This tool offers policymakers insights into the effects of patient choice in ACOs and potential policy tweaks

Modelling Competition in Health Care Markets as a Complex Adaptive System: an Agent-Based Framework

With Shinyi Wu

Published in Health Systems and presented at INFORMS 2015

  • Health market reforms require ongoing reassessment of initiatives, regulations, and policies, but many nuances of market competition are often missed due to methodological constraints.

  • The study draws connections between the defining characteristics of health care markets (HCM) and complex adaptive systems (CAS) to address these limitations.

  • CAS science offers models that capture dynamic interactions, providing insights into diverse agents and emerging behaviors.

  • The introduced agent-based framework, a tool of CAS science, is tailored for exploring competition in HCM, detailing agents, environments, interactions, and other specifics to mimic HCM dynamics.

  • Advances in data, computational capabilities, and decision theory make the CAS approach a valuable addition to research on critical HCM challenges.

Developing an Agent-Based Simulation Model to Evaluate Competition in Private Health Care Markets

With Shinyi Wu

Submitted as a PhD Dissertation at the University of Southern California - Epstein Department of Industrial & Systems Engineering and presented at Academy Health Annual Research Meeting 2018

  • Healthcare market dynamics are intricate, with initiatives like state-level health insurance exchanges and Accountable Care Organizations (ACOs) potentially upsetting competitive balances.

  • An agent-based model (ABM) was developed to simulate private healthcare markets, focusing on the interplay between competition and collaboration under varying market conditions. This model represents health care plans, providers, and patients as agents interacting within a defined insurance rating area (IRA).

  • The model's simulations, validated against econometric literature, examined the effects of market conditions on outcomes such as insurer premiums, provider quality, health outcomes, and expenditures.

  • A case study within the model assessed the impact of ACO formations on market outcomes. Results indicated that in highly competitive markets, ACOs can shift power in favor of providers, while in less competitive markets, the price increase due to ACOs is marginal.

  • This research offers a novel approach to understanding healthcare competition, highlighting the potential of CAS simulation to uncover system leverage points and test policy interventions, challenging existing views on ACOs in competitive markets.

Applying Insurer-Provider Bargaining to Multi-Agent Models of Health Care Markets

With Humoud Alsabah, Shinyi Wu

In preparation and presented at INFORMS

  • Multi-agent models are suitable for studying the relationship between value and the competitive effects of healthcare regulations and initiatives.

  • This study introduces an insurer-provider bargaining framework based on a Nash bargaining model, considering each agent's market leverage and prevailing market conditions.

  • The Nash product solution represents the equilibrium price where agents optimize their disagreement tradeoffs.

  • Preliminary results demonstrate how alterations in provider and insurer market shares under different market setups influence service prices in simulated healthcare market models.

  • The results pave the way for dynamic and representative interactions between insurer and provider agents in virtual representations of markets

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