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Biography

LeRoy E Jones is Chief Executive Officer and founder of GSI Health, LLC, a healthcare technology solution provider and national leader in care coordination and population health management. He is a recognized expert in healthcare information technology, particularly interoperability and collaborative care. He is a frequent public speaker and is regularly called upon to lead and contribute toward significant industry initiatives. He holds an MS in Engineering in the Management of Technology jointly from The Wharton School and the Engineering School at the University of Pennsylvania, and a BS in Computer Science from Carnegie Mellon University.

Abstract

The march toward value-based care has been continuous for some years, but has been catalyzed recently by the passage of the Affordable Care Act, and regulations by the Centers for Medicare and Medicaid Services (CMS) which impose penalties for avoidable hospital readmissions for certain disease conditions. Many healthcare communities who have entered into collaborative care agreements are now looking to manage their shared populations of patients, and need analytics to help measure critical outcomes and key performance indicators of their care coordination efforts. There is, however, no coherent and well established approach to population analytics. There are differences in data types (e.g:claims versus clinical data), data quality standards, population stratification, and even in the measures themselves. In order to have replicable success, we need to build replicable models for analyzing population management and collaborative care. We need to construct a framework for consistently building the systems of measurement that can create a uniform benchmark for achieving the Triple Aim which has become the true-north for national healthcare reform that is undergirded by information technology. Technology, therefore, must not just offer a plethora of reports and calculations, but must offer a comprehensive system of evaluation and analysis that applies a consistent model of analytics to a variable set of data inputs, care models, and payment models (e.g., program incentives and drivers). The problem is not intractable, but requires recognition of the importance of consistent analysis in population health, and publication of reference systems of measurement that may be adopted broadly.

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