OBJECTIVES: New methods developed to improve the statistical basis of provider profiling may be particularly applicable to nursing homes. We examine the use of Bayesian hierarchical modeling in profiling nursing homes on their rate of pressure ulcer development. DESIGN: Observational study using Minimum Data Set data from 1997 and 1998. SETTING: A for-profit nursing home chain. PARTICIPANTS: Residents of 108 nursing homes who were without a pressure ulcer on an index assessment. MEASUREMENTS: Nursing homes were compared on their performance on risk-adjusted rates of pressure ulcer development calculated using standard statistical techniques and Bayesian hierarchical modeling. RESULTS: Bayesian estimates of nursing home performance differed considerably from rates calculated using standard statistical techniques. The range of risk-adjusted rates among nursing homes was 0% to 14.3% using standard methods and 1.0% to 4.8% using Bayesian analysis. Fifteen nursing homes were designated as outliers based on their z scores, and two were outliers using Bayesian modeling. Only one nursing home had greater than a 50% probability of having a true rate of ulcer development exceeding 4%. CONCLUSIONS: Bayesian hierarchical modeling can be successfully applied to the problem of profiling nursing homes. Results obtained from Bayesian modeling are different from those obtained using standard statistical techniques. The continued evaluation and application of this new methodology in nursing homes may ensure that consumers and providers have the most accurate information regarding performance.
OBJECTIVES: New methods developed to improve the statistical basis of provider profiling may be particularly applicable to nursing homes. We examine the use of Bayesian hierarchical modeling in profiling nursing homes on their rate of pressure ulcer development. DESIGN: Observational study using Minimum Data Set data from 1997 and 1998. SETTING: A for-profit nursing home chain. PARTICIPANTS: Residents of 108 nursing homes who were without a pressure ulcer on an index assessment. MEASUREMENTS: Nursing homes were compared on their performance on risk-adjusted rates of pressure ulcer development calculated using standard statistical techniques and Bayesian hierarchical modeling. RESULTS: Bayesian estimates of nursing home performance differed considerably from rates calculated using standard statistical techniques. The range of risk-adjusted rates among nursing homes was 0% to 14.3% using standard methods and 1.0% to 4.8% using Bayesian analysis. Fifteen nursing homes were designated as outliers based on their z scores, and two were outliers using Bayesian modeling. Only one nursing home had greater than a 50% probability of having a true rate of ulcer development exceeding 4%. CONCLUSIONS: Bayesian hierarchical modeling can be successfully applied to the problem of profiling nursing homes. Results obtained from Bayesian modeling are different from those obtained using standard statistical techniques. The continued evaluation and application of this new methodology in nursing homes may ensure that consumers and providers have the most accurate information regarding performance.
Authors: Michael Shwartz; Erol A Peköz; Cindy L Christiansen; James F Burgess; Dan Berlowitz Journal: Health Serv Res Date: 2012-06-20 Impact factor: 3.402
Authors: Joanna B Broad; Toni Ashton; Thomas Lumley; Michal Boyd; Ngaire Kerse; Martin J Connolly Journal: BMC Med Res Methodol Date: 2014-07-22 Impact factor: 4.615