JSM 2011 Online Program

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Abstract Details

Activity Number: 29
Type: Contributed
Date/Time: Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
Sponsor: Section on Health Policy Statistics
Abstract - #301424
Title: A Bayesian Analytical Study of the Impact of Information Therapy Events Using Patient-Level Claims Data
Author(s): Philip Twumasi-Ankrah*+ and Traci A. Hart and Douglas D. Bradham and Nikki Woods and Amy Chesser
Companies: University of Kansas SOM - Wichita and University of Kansas and University of Kansas SOM - Wichita and University of Kansas SOM - Wichita and University of Kansas SOM - Wichita
Address: Dept of Preventive Medicine and Public Health, Wichita, KS, 67214,
Keywords: Information Therapy ; Health-care ; generalized linear models ; bayesian analysis ; claims data ; insurance
Abstract:

Interest in accurately estimating the cost and utilization of healthcare and the impact of specific treatments continue to increase. Observational real-world data have limitations and often are not appropriate for determining costs, use and the optimal treatment of conditions, since they focus on: routine care, use of broader outcomes and heterogeneous populations with co-morbidities. Insurance claims data can be used to understand the characteristics of treatments and behaviors of patients using specific treatments. It is expected that patient behavior in treatment; costs and utilization which are great determinants of effective health care programs, are modifiable by the consumption of information therapy. As people become more knowledgeable about health and care implications, it is expected that only a few patients would incur extremely high costs, or have longer hospital stays. A critical analytical issue is accounting for a large set of patients not incurring costs or services. We use Bayesian analysis of generalized linear models to estimate costs and utilization characteristics for health-care services from 2004 to 2008 of a mid-western city employer, utilizing claims data.


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