Focusing on Provider Quality Measurement: Continued Consensus and Feasibility Testing of Practice-Based Quality Measures for Primary Care Providers in Long-Term Care

Medical providers in long-term care (LTC) use a unique skillset in delivering comprehensive resident care. Publicly reported quality measures (QMs) do not directly emphasize medical provider competency and their role in care. The impact of providers is understudied and to a large extent, unknown. Our objective was to define, test, and validate QMs to pragmatically measure the practice-based quality of medical providers in a pilot study. We included 7 North American LTC homes with data from practicing medical providers for LTC residents. We engaged in a 4-phased approach. In phase 1, experts rated 95 candidate QMs using 5 pragmatic-focused criteria in a RAND-modified Delphi process. Phase 2 involved specifying 37 QMs for collection (4 QMs were dropped during pilot testing). We created an abstraction manual and data collection tool for all QMs. Phase 3 involved a retrospective chart review in 7 LTC homes on 33 QMs with trained data abstractors. Data were sufficient to analyze performance for 26 QMs. Lastly, in phase 4 results and psychometric properties were reviewed with an expert panel. They ranked the tested measures for validity and feasibility for use by a nonphysician auditor to evaluate medical provider performance based on medical record review. In total, we examined data from 343 resident charts from 7 LTC homes and 49 providers. Our process yielded 10 QMs as being specified for measurement, feasible to collect, and had good test performance. This is the only study to systematically identify a subset of QMs for feasible collection from the medical record by various data collectors. This pragmatic approach to measuring practice-based quality and quantifying select medical provider competencies allows for the evaluation of individual and facility-level performance and facilitates quality improvement initiatives. Future work should perform broader testing and validate and refine operationalized QMs.