Journal of Healthcare Management - May/June 2014 - (Page 233)

M odel for p rof IlI ng p Hys IcIans a cross d o MaIns of c are TA B L E 2 Reliability Results for the Composites Composites Median Mean Quality Average Reliability Events Across Physician Across Total Physicians Rate Physicians Physicians Approximate % of Physicians Meeting Sample Minimum Size Needed Sample Size for for .70 Reliability .70 Reliability Quality of care 199 252 0.72 0.98 17 96 Efficiency 199 1,115 0.77 0.97 63 90 $14,000. About 90% of physicians received payouts of between $0 and $6,000. DISCUSSION Study Implications The results in Tables 1 and 2 demonstrate the success in using composites to address reliability issues. Our results also confirm the difficulties in using individual measures. To create reliable composite measures, less common and disease-specific measures were included, possibly introducing additional variability and multimodality in the data. We found that the z-score range across physicians per measure was highly influenced by the minimum quality event threshold and the number of physicians profiled. By definition, as the variation in a measure increases, the z-score range becomes compressed (Petruccelli et al., 1999). A sensitivity analysis was carried out at Health Clinic to understand the impact of undetected errors on payout. In the analysis, when 20 quality hits were missed for the highest weighted measure, a 2-3% change in payout occurred for those physicians with at least average network panel size. The payout method minimized the magnitude of misclassification effects on payout by scoring physicians continuously rather than grouping them into discrete levels for payout. The physician profiling model in Figure 2 can be expanded to include additional data sources and domains, supporting applications in diverse healthcare settings. For example, the domains in the Health Clinic model could be expanded to include internally assessed medical home survey data, patient experience survey data, and episode treatment group data. Data sources such as EHRs and satisfaction surveys could also inform additional measures, including health status and comfort (Berwick, 2009; Linder, Kaleba, & Kmetik, 2009). The quality-of-care domain could be divided into three domains of care (acute, preventive, and chronic, shown in gray in Figure 2). The hurdle for regrouping is identifying additional measures that support validity, completeness and accuracy of data, and reliability. 233

Table of Contents for the Digital Edition of Journal of Healthcare Management - May/June 2014

Journal of Healthcare Management - May/June 2014
Contents
Interview With Christopher D. Van Gorder, FACHE, President and CEO of Scripps Health
Successful Strategic Planning for a Reformed Delivery System
You, Inc.
Assessing the Feasibility of a Virtual Tumor Board Program: A Case Study
Physician Clinical Alignment and Integration: A Community–Academic Hospital Approach
Employer-Based Coverage and Medical Travel Options: Lessons for Healthcare Managers
Composite Model for Profiling Physicians Across Domains of Care

Journal of Healthcare Management - May/June 2014