Speaker
Description
Background: There is an increasing interest in making use of patient reported outcome measures for provider comparisons, However, guidance on the choice of outcomes and selection of variables for case-mix adjustment for specific patient groups is lacking.
Material: In the ACRF-pred study 973 patients from 19 different clinics were followed after arthroscopic rotator cuff repair for 24 months with several patient reported outcomes and for 12 months with several clinician reported outcomes. Fifty-two potential indicators for provider comparisons could be defined. Five approaches to select variables (out of 55 available) for case-mix adjustment were predefined to study the robustness of the comparison of indicators.
Methods: The usefulness of an indicator was conceptually defined as the ability to discriminate between clinics. This ability was assessed by the variation explained by the clinics after case-mix adjustments. To judge the need for case mix adjustment, the reduction in the standard deviation of the case-mix adjusted clinic-specific mean values was considered. The direct impact of the approach to variable selection was measured by the change in position in funnel plots.
To shift the focus on average performance towards occasional low-level performance percentile-based transformations of indicators were considered giving higher weights to unfavourable outcome values. The same analytical steps were performed with focus on the shift of results with increasing weight given to unfavourable outcomes. The validity of analysing percentile-based transformed variables by mixed models was investigated in a simulation study.
Results: Both patient reported outcomes as well as clinician reported outcomes were able to discriminate between clinics to a substantial degree. The impact of case-mix adjustment was rather moderate, which could be explained by a lack of variables predictive for the outcomes of interest AND varying in distribution across clinics.
Moving the focus from average performance towards occasional low-level performance can be approached in a reliable manner using percentile-based transformation of indicators. It can have an impact on the choice of outcomes and the positioning of single clinics.
Choice of outcomes for quality assessment and monitoring can benefit from further analyses addressing the question whether different outcomes / transformations address the same or different underlying quality constructs.
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