TY - JOUR
T1 - Using self-reported health measures to predict high-need cases among medicaid-eligible adults
AU - Wherry, Laura R.
AU - Burns, Marguerite E.
AU - Leininger, Lindsey Jeanne
N1 - Publisher Copyright:
© Health Research and Educational Trust.
PY - 2014/12/1
Y1 - 2014/12/1
N2 - Objective 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.Data Sources The 1997-2008 rounds of the National Health Interview Survey linked to the 1998-2009 rounds of the Medical Expenditure Panel Survey (n = 6,725).Study Design 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 c-statistic, integrated discrimination improvement, sensitivity, specificity, and predictive values.Principal Findings 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 (c-statistics range from 0.703 to 0.751).Conclusions SRH measures provide a promising way to prospectively profile Medicaid-eligible adults by likely health care needs.
AB - Objective 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.Data Sources The 1997-2008 rounds of the National Health Interview Survey linked to the 1998-2009 rounds of the Medical Expenditure Panel Survey (n = 6,725).Study Design 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 c-statistic, integrated discrimination improvement, sensitivity, specificity, and predictive values.Principal Findings 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 (c-statistics range from 0.703 to 0.751).Conclusions SRH measures provide a promising way to prospectively profile Medicaid-eligible adults by likely health care needs.
KW - Medicaid
KW - prediction models
KW - risk assessment
KW - self-rated health measurement
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U2 - 10.1111/1475-6773.12222
DO - 10.1111/1475-6773.12222
M3 - Article
C2 - 25130916
AN - SCOPUS:84912530879
SN - 0017-9124
VL - 49
SP - 2147
EP - 2172
JO - Health Services Research
JF - Health Services Research
IS - S2
ER -