Health Management Seminar: Risk and Cost in Healthcare Delivery Networks

Health Management Seminar

Risk and Cost in Healthcare Delivery Networks:Data-driven and Analytical Models

Fernanda Bravo, Massachusetts Institute of Technology, MIT Sloan School of Management

Abstract

In this talk we will discuss several analytical models that address some of the current challenges faced by large healthcare delivery networks in the US. The recent healthcare reform act has accelerated even further the trend of consolidation in the healthcare industry in the US and the creation of large healthcare delivery networks.  However, unlike the prior decade in which consolidation efforts were primarily a way to gain market power, the current efforts require true integration of care across different parts of the network. Moreover, many of the large networks are facing a challenging environment in which they shift their engagement with payers from fee-for-service payment schemes to capitation risk contracts that require them to manage risk and health of patient populations, and at the same time they develop B2B relationships with smaller systems (acting themselves under capitation) to which they provide tertiary services.

Motivated by these challenges, we will discuss several analytical and data-driven models that capture major related tradeoffs. We will model the B2B interactions through a 2-echelon service supply chain between a service provider and a capitated service recipient.  Unlike the traditional product based supply chain, the service supply chain is characterized by risk asymmetry. We propose innovative contracting schemes that induce appropriate risk sharing, and demonstrate analytically that the new contracting scheme reduces the risks for the two parties compared to the standard commonly used single price contract. In addition, we describe a collaborative work with a major academic medical center in the Boston area, in which we employ ideas from revenue management to build data-driven decision support models to inform surgical resource allocation within their evolving network of hospitals. The models reveal the ‘correct’ costs within the network, guide resource allocation and highlight existing bottlenecks. Moreover, we demonstrate a dramatic improvement in terms of profitability as compared to the traditional approaches commonly used within healthcare systems to capture cost and allocate resources.

A light lunch will be served