Using Self‐Reported Health Measures to Predict High‐Need Cases among Medicaid‐Eligible Adults. (15th August 2014)

• Record Type: Journal Article
• Authors: Wherry, Laura R.; Burns, Marguerite E.; Leininger, Lindsey Jeanne
• Is Part Of: Health services research. Volume 49:Number 2(2014)
• Page Start: 2147
• Page End: 2172
• Publication Date: 2014-08-15
• Subjects: Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.12222
• Languages: English
• ISSNs: 0017-9124

Abstract

<abstract abstract-type="main" id="hesr12222-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="hesr12222-sec-0001" sec-type="section"> <title>Objective</title> <p>To assess the ability of different self‐reported health (SRH) measures to prospectively identify individuals with high future health care needs among adults eligible for Medicaid.</p> </sec> <sec id="hesr12222-sec-0002" sec-type="section"> <title>Data Sources</title> <p>The 1997–2008 rounds of the National Health Interview Survey linked to the 1998–2009 rounds of the Medical Expenditure Panel Survey (<italic>n</italic> = 6, 725).</p> </sec> <sec id="hesr12222-sec-0003" sec-type="section"> <title>Study Design</title> <p>Multivariate logistic regression models are fitted for the following outcomes: having an inpatient visit; membership in the top decile of emergency room utilization; and membership in the top cost decile. We examine the incremental predictive ability of six different SRH domains (health conditions, mental health, access to care, health behaviors, health‐related quality of life [HRQOL], and prior utilization) over a baseline model with sociodemographic characteristics. Models are evaluated using the <italic>c</italic>‐statistic, integrated discrimination improvement, sensitivity, specificity, and predictive values.</p> </sec> <sec id="hesr12222-sec-0004" sec-type="section"> <title>Principal Findings</title> <p>Self‐reports of prior utilization provide the greatest predictive improvement, followed by information on health conditions and HRQOL. Models including these three domains meet the standard threshold of acceptability (<italic>c‐</italic>statistics range from 0.703 to 0.751).</p> </sec> <sec id="hesr12222-sec-0005" sec-type="section"> <title>Conclusions</title> <p>SRH measures provide a promising way to prospectively profile Medicaid‐eligible adults by likely health care needs.</p> </sec> </abstract>