• Patrick Taffé, Patricia Halfon, William A Ghali, Bernard Burnand, and International Methodology Consortium for Coded Health Information (IMECCHI).
• Institute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois, and University of Lausanne, Lausanne, Switzerland (PT, PH, BB)
• Med Decis Making. 2012 Jan 1; 32 (1): E1-12.

ObjectiveAccuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified.MethodsWe considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened.ResultsOver sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000.ConclusionsVerification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

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