Journal of Healthcare Management - May/June 2014 - (Page 232)

J o u r n al of H ealt H care M anage Ment 59:3 M ay /J une 2014 the number of physicians having quality events and the mean number of events, varying by measure. For example, diabetes mellitus measures were represented by more physicians and showed a higher mean number of quality events than did coronary artery disease (CAD) measures. The last stage of physician profiling is developing an output plan in alignment with the organization's policy and P4P or other performance goals. This step of the model is customizable and should be linked to the modelspecification step by the administrating entity. For Health Clinic, the domain scores were combined using weights determined by the governing committee at Health Clinic and implemented for the 2008 rewards program. Payouts were determined from the overall composite score per physician, panel size, and allotted dollars. The payout plan included only the physicians eligible for profiling and excluded all PCPs with a final z score lower than −1. One point was added to each PCP's score, and the sum was multiplied by the PCP's panel size to yield panel points per physician; the additional point allowed all physicians scoring above −1 to receive a positive score for payout calculation. The total of available incentive dollars was then divided by the total panel points across all physicians to yield a dollar per panel point rate. This rate was multiplied by the panel size of each physician to yield individual payout amounts. R E S U LT S The reliability results for each individual measure used at Health Clinic were calculated using the mean rate and mean quality events across providers and are summarized in Table 1. Reliabilities ranged from .11 to .89, with generic prescribing having the highest reliability, highest average number of quality events, and highest percentage of physicians meeting the minimum sample size required to achieve reliability of .70. Colorectal cancer screening and well-adolescent visit measures also had reliability estimates above .70. Overall, reliability results varied considerably across individual measures, typically improving with the number of quality events. As expected, as the reliability of the measures increased, the percentage of physicians meeting the minimum sample size increased. Composite reliabilities were estimated for each physician in two domains: quality of care and efficiency. The results are summarized in Table 2. The median reliability for the quality-ofcare composite was .98, and the median reliability for the efficiency composite was .97, both exceeding the recommended threshold of .70. The approximate sample size across all measures in the domain needed to achieve a reliability estimate greater than .70 was 17 for the quality-of-care composite and 63 for the efficiency composite. The percentage of total evaluated physicians (199) meeting the minimum reliability threshold was 96% for quality of care and 90% for efficiency; all physicians receiving a payout had reliability estimates greater than .70. The model was implemented for the 2008 rewards program at Health Clinic. The payouts calculated for physicians ranged from $0 to approximately 232

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