The reliability and validity of Bayesian measures for hospital profiling: a Monte Carlo assessment |
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| Institution: | 1. Institute for Clinical Evaluative Sciences, G-160, 2075 Bayview Avenue, Toronto, Ont., Canada M4N 3M5;2. Department of Public Health Sciences, University of Toronto, Toronto, Ont., Canada;3. Department of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ont., Canada;1. College of Mathematics and Statistics, Shenzhen University, Shengzeng, Guangdong, China;2. School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, Hubei, China;3. Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;4. Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN, USA;5. Department of Epidemiology & Cancer Control, St. Jude Children’s Research Hospital, Memphis, TN, USA;6. Shenzhen Research Institute & Department of Statistics, Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China;1. Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Respiratory Unit and Cystic Fibrosis Adult Center, Milan, Italy;2. Università degli Studi di Milano, Department of Pathophysiology and Transplantation, Milan, Italy;3. Thoracic Surgery and Lung Transplant Unit, Fondazione Irccs Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy;1. University of Applied Sciences and Arts Hannover, Hannover, Germany;2. Chair of Health Management, Friedrich-Alexander-University Erlangen-Nuremberg, Nürnberg, Germany;1. LCP-A2MC, Université de Lorraine, 1 Boulevard Arago – CP 87811, F-57078 Metz Cedex 3, France;2. LCPME UMR 7564 CNRS-Université de Lorraine, 405 rue de Vandoeuvre, F-54602 Villers-lès-Nancy Cedex, France;3. SRSMC UMR 7565 CNRS-Université de Lorraine, Faculté des Sciences et Techniques, B.P. 70239, 54506 Vandoeuvre-les-Nancy Cedex, France;4. LTU, Department of Engineering Sciences and Mathematics, Luleå University of Technology, 971 87 Luleå, Sweden;5. Department of Physics, Harvard University, Cambridge, MA 02138, USA |
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| Abstract: | There is a growing trend towards the production of “hospital report-cards” in which hospitals with higher than acceptable mortality rates are identified. Several commentators have advocated for the use of Bayesian methods for health care report cards. Earlier research has demonstrated that there is poor concordance between different Bayesian methods. The current study used Monte Carlo simulation methods to examine the reliability and validity of four different Bayesian measures of hospital performance. Estimates of the reliability of the different measures ranged from a low of 0.89 to a high of 0.99. Estimates of the validity of the four measures ranged from a low of 0.58 to a high of 0.65. Thus, while the four measures of hospital performance demonstrated high reliability, the validity of each method was at most moderate. It is hypothesized that the low validity is due in part to the limited sample sizes that are typically available for hospital report cards. |
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