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National Release of the Nursing Home Quality Report Cards: Implications of Statistical Methodology for Risk Adjustment
Author(s) -
Li Yue,
Cai Xueya,
Glance Laurent G.,
Spector William D.,
Mukamel Dana B.
Publication year - 2009
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/j.1475-6773.2008.00910.x
Subject(s) - minimum data set , estimator , statistics , confidence interval , logistic regression , medicine , activities of daily living , demography , econometrics , mathematics , nursing homes , physical therapy , nursing , sociology
Objective. To determine how alternative statistical risk‐adjustment methods may affect the quality measures (QMs) in nursing home (NH) report cards. Data Sources/Study Settings. Secondary data from the national Minimum Data Set files of 2004 and 2005 that include 605,433 long‐term residents in 9,336 facilities. Study Design. We estimated risk‐adjusted QMs of decline in activities of daily living (ADL) functioning using classical, fixed‐effects, and random‐effects logistic models. Risk‐adjusted QMs were compared with each other, and with the published QM (unadjusted) in identifying high‐ and low‐quality facilities by either the rankings or 95 percent confidence intervals of QMs. Principal Findings. Risk‐adjusted QMs showed better overall agreement (or convergent validity) with each other than did the unadjusted versus each adjusted QM; the disagreement rate between unadjusted and adjusted QM can be as high as 48 percent. The risk‐adjusted QM derived from the random‐effects shrinkage estimator deviated nonrandomly from other risk‐adjusted estimates in identifying the best 10 percent facilities using rankings. Conclusions. The extensively risk‐adjusted QMs of ADL decline, even when estimated by alternative statistical methods, show higher convergent validity and provide more robust NH comparisons than the unadjusted QM. Outcome rankings based on ADL decline tend to show lower convergent validity when estimated by the shrinkage estimator rather than other statistical methods.