OBJECTIVES: The authors evaluated methods of reporting on rates of pressure ulcer development in long-term care to identify approaches that lead to more stable estimates of actual performance. METHODS: Performance measures for facilities that adequately adjust for both random variation and casemix should be relatively stable from one time period to the next. The authors calculated facility rates of pressure ulcer development over eight consecutive time periods and correlated measures over time using different reporting methods including z-scores, combining rates from several time periods, and limiting analyses to large facilities. Results were compared with a Monte Carlo simulation. RESULTS: Observed facility rates of pressure ulcer development varied considerably over time. The average correlation coefficient across seven time comparisons for observed rates was 0.17. Reporting performance as a z-score or limiting the analyses to large facilities increased the correlation. Combining two time periods was effective only when used with one of these other approaches. The correlation coefficient based on a simulation using only large facilities was 0.51. CONCLUSIONS: Random variation affects reported rates of pressure ulcer development. Using only large facilities and combining two time periods limits the effects of random variation and results in more stable estimates of performance. When describing performance, management must consider tradeoffs between having more accurate data, the frequency with which data are provided, and whether it is given to all providers.
OBJECTIVES: The authors evaluated methods of reporting on rates of pressure ulcer development in long-term care to identify approaches that lead to more stable estimates of actual performance. METHODS: Performance measures for facilities that adequately adjust for both random variation and casemix should be relatively stable from one time period to the next. The authors calculated facility rates of pressure ulcer development over eight consecutive time periods and correlated measures over time using different reporting methods including z-scores, combining rates from several time periods, and limiting analyses to large facilities. Results were compared with a Monte Carlo simulation. RESULTS: Observed facility rates of pressure ulcer development varied considerably over time. The average correlation coefficient across seven time comparisons for observed rates was 0.17. Reporting performance as a z-score or limiting the analyses to large facilities increased the correlation. Combining two time periods was effective only when used with one of these other approaches. The correlation coefficient based on a simulation using only large facilities was 0.51. CONCLUSIONS: Random variation affects reported rates of pressure ulcer development. Using only large facilities and combining two time periods limits the effects of random variation and results in more stable estimates of performance. When describing performance, management must consider tradeoffs between having more accurate data, the frequency with which data are provided, and whether it is given to all providers.