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Category: Health Care Economics Health Insurance Expert Uses Data Desk to Create New Modeling Tool At the University of California, San Francisco, economist Hal Luft is researching how to design payment plans that will find a balance between fulfilling patients’ needs and maintaining the viability of health care insurers and providers. Data Desk has become an indispensable tool in this process. Hal is the Caldwell B. Esselstyn Professor at U.C. San Francisco’s Institute for Health Policy Studies and a specialist in health economics. The goal of his current work is to help policymakers configure a variety of payment lans that will enable payers, such as Medicare and employers, to offer insurers and providers more for enrolling high risk people and less for low risk people. He is using Data Desk to build risk-adjustment models that simulate the myriad tradeoffs among “healthiness,” health care costs, and payment arrangements. Hal points out that in the market for health care insurance, patients can sometimes accept or reject the terms of a health care plan by remaining in or exiting the plan and switching to another. This allows plans to devise subtle strategies to keep the people they think will be profitable, and encourage those they think will be costly to leave—unless payers can adjustment their payments appropriately. His models project health care costs for 320,000 patients. Rather than just selecting cases at random, his program allows the user to adjust the probability of selection for people in each percentile of the expenditure distribution for year 1. This allows the user to simulate discouraging high-cost participants, attracting low-cost patients or other strategies. One then examines the costs of the enrollees in year 2, and the ability of various risk adjustment approaches to predict these costs. Hal has typically been running sets of 1,000 simulations at a time with 250 or 5,000 enrollees in each. Although Hal points out that the core of his simulations consists of about 15 lines of code, these15 lines of code allow the non-random access to all 320,000 cases and many variables to generate large and sophisticated modeling and analysis environment. The size of the dataset presents no obstacle in Data Desk. The whole dataset resides comfortably on his Mac, and 1,000 simulations of 250 enrollees each takes under 2 minutes; 1,000 simulations of 5,000 enrollees each takes only 15 minutes. What Hal says he especially appreciates about the software are the tools for building specialized templates and specialized applications. “I like the ability to put the model all together and lock it. Then you can let the user just drop in the variables.” Hal’s research will be published for the benefit of health care policy experts and students of policy. In order to allow people in these audiences to try out their own simulations that can respond to their own particular situations, Hal is building a modeling tool that will incorporate a special version of Data Desk 6.1 and customized interface that lets the user do a complete set of simulations for examination and analysis, without the need for any special statistics or Data Desk expertise. |
Name: Hal Luft Affiliation: UC, San Francisco |
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