Journal of Healthcare Management - May/June 2014 - (Page 226)

J o u r n al of H ealt H care M anage Ment 59:3 M ay /J une 2014 proposed to address reliability concerns (Scholle et al., 2008; Smith, Sussman, Bernstein, & Hayward, 2013). Scholle et al. (2008) introduced a model that creates a composite measure for each physician using weighted z scores across measures. Because z scores measure performance in terms of standard deviations from the mean, the same measurement scale is, in effect, employed for all measures. Composites may be focused on a particular diagnosis (e.g., diabetes) or a type of care (e.g., preventive) (Lovett & Liang, 2012; Sequist, Schneider, Li, Rogers, & Safran, 2011). Such composites have been shown in some cases to create reliable measures (Smith et al., 2013; van Doorn-Klomberg et al., 2013). In this study, we present a method for creating a reliable physician profiling model by pooling patient-level data across multiple payers and data sources and combining measures into domains of care using Scholle et al.'s (2008) approach to increase sample size and variation across primary care physicians (PCPs). We demonstrate its use at a multiple-clinic healthcare organization, which we call Health Clinic (a fictitious name), at which the scores were used to calculate incentive payments. The model is expandable to include various domain types (e.g., acute, chronic, preventive, patient experience, medical home), sources of data (e.g., electronic health record [EHR] data, Medicaid and Medicare data), and stratification within domains for patient mix or clinical practice characteristics. Healthcare organizations can tailor the model to match organizational characteristics. METHODS Case Study Setting and Data The model presented here was used to profile PCPs in a managed care network in Massachusetts. The study population included 199 physicians across pediatric primary care, family medicine, and general internal medicine specialties from 68 Massachusetts outpatient clinics, which were part of the integrated Health Clinic system. We illustrate the use of the model with data from 2008. The case study site, Health Clinic, provided the 2008 measure rates, numerators, and denominators per individual physician for selected measures. Data were pulled from a central claims repository for three health plans, the clinical system's lab results, and billing and scheduling information. Health plan administrative claims and enrollment data across the three payers represented roughly 75% of all paid claims. Additional information included panel size per physician, physician specialty, active employment status per physician, and externally vetted benchmark performance per measure. Model Development To build our model, we used the iterative process shown in Figure 1, which illustrates major steps and highlights important decisions that must be made at each step. These decisions are guided by the desire to create robust and reliable profiling scores within the given organizational context and the limitations of the available data. The process begins with model specification, which involves defining the 226

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