OBJECTIVES: When comparing the scores from Consumer Assessment of Health Plans Study (CAHPS) surveys across health plans, it is important to adjust for patient characteristics (casemix) that are not under the control of the plan but that affect plan ratings. Our goal was to develop casemix models for pediatric CAHPS surveys. METHODS: We analyzed responses to the pediatric CAHPS 2.0 surveys from 50,583 Medicaid beneficiaries and 43,579 persons with private health insurance. We identified patient characteristics with the most substantial impact on scores and assessed casemix models that include different combinations of adjusters. In addition, we tested whether casemix coefficients differed between the Medicaid and commercial samples and across health plans. RESULTS: Parent age and education and child health status and race were important casemix adjustment variables for pediatric CAHPS surveys. Child age and gender had smaller effects. The relationship between patient characteristics and CAHPS scores was different in the Medicaid and commercial samples for some variables. The effects of a patient's characteristics on ratings and report scores were not consistent across Medicaid plans but more consistent for commercial plans. CONCLUSIONS: Our analyses indicate that plan scores on the pediatric CAHPS survey should be adjusted for plan differences in casemix. Users should consider estimating separate models for Medicaid and commercially insured respondents. Such models should adjust for child health status, parent age, and parent education.
OBJECTIVES: When comparing the scores from Consumer Assessment of Health Plans Study (CAHPS) surveys across health plans, it is important to adjust for patient characteristics (casemix) that are not under the control of the plan but that affect plan ratings. Our goal was to develop casemix models for pediatric CAHPS surveys. METHODS: We analyzed responses to the pediatric CAHPS 2.0 surveys from 50,583 Medicaid beneficiaries and 43,579 persons with private health insurance. We identified patient characteristics with the most substantial impact on scores and assessed casemix models that include different combinations of adjusters. In addition, we tested whether casemix coefficients differed between the Medicaid and commercial samples and across health plans. RESULTS: Parent age and education and child health status and race were important casemix adjustment variables for pediatric CAHPS surveys. Child age and gender had smaller effects. The relationship between patient characteristics and CAHPS scores was different in the Medicaid and commercial samples for some variables. The effects of a patient's characteristics on ratings and report scores were not consistent across Medicaid plans but more consistent for commercial plans. CONCLUSIONS: Our analyses indicate that plan scores on the pediatric CAHPS survey should be adjusted for plan differences in casemix. Users should consider estimating separate models for Medicaid and commercially insured respondents. Such models should adjust for child health status, parent age, and parent education.
Authors: Laura L Eselius; Paul D Cleary; Alan M Zaslavsky; Haiden A Huskamp; Susan H Busch Journal: Health Serv Res Date: 2008-09-08 Impact factor: 3.402
Authors: Patricia Gallagher; Lin Ding; Hazen P Ham; Edward L Schor; Ron D Hays; Paul D Cleary Journal: Pediatrics Date: 2009-10-12 Impact factor: 7.124
Authors: Marc N Elliott; Alan M Zaslavsky; Elizabeth Goldstein; William Lehrman; Katrin Hambarsoomians; Megan K Beckett; Laura Giordano Journal: Health Serv Res Date: 2009-04 Impact factor: 3.402
Authors: Chia-Ling Liu; Alan M Zaslavsky; Michael L Ganz; James Perrin; Steven Gortmaker; Marie C McCormick Journal: Matern Child Health J Date: 2007-06-08