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The American Journal of Managed Care July 2019
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Physician Satisfaction With Health Plans: Results From a National Survey
Natasha Parekh, MD, MS; Sheryl Savage; Amy Helwig, MD, MS; Patrick Alger, BS; Ilinca D. Metes, BS; Sandra McAnallen, MA, BSN; and William H. Shrank, MD, MSHS

Physician Satisfaction With Health Plans: Results From a National Survey

Natasha Parekh, MD, MS; Sheryl Savage; Amy Helwig, MD, MS; Patrick Alger, BS; Ilinca D. Metes, BS; Sandra McAnallen, MA, BSN; and William H. Shrank, MD, MSHS
Several physician and payer characteristics are associated with physician satisfaction with health plans. There is opportunity to improve physician satisfaction with payers, specifically in pharmacy.
Piloting and Validity/Reliability Testing

SPH Analytics then piloted the final survey with 8 health plans that included 1524 provider responders, representing physicians, nurses, office managers, behavioral health clinicians, and other staff. SPH Analytics conducted reliability testing via internal consistency analysis (Cronbach’s alpha) and validity testing via factor analysis. In internal consistency analyses, the Cronbach’s alpha values for the key domains (finance issues, utilization and quality management, network/coordination of care, pharmacy, call center services, and provider relations) ranged from 0.884 to 0.957, indicating that the domains represented reliable measures of provider satisfaction. Factor analysis suggested 4 underlying factors that matched with survey domains—provider relations, quality and accessibility, pharmacy, and finance issues.

Sampling Strategy and Survey Administration

SPH Analytics works with health plans to determine their provider sampling strategies. Strategies generally start with a sample of 1500 providers per health plan, with stratification efforts to include 60% primary care physicians, 30% specialists, and 10% behavioral health clinicians. Physicians with high patient volumes are targeted first because they likely have more interaction with health plans. Based on focus group feedback on desired administration methods, SPH Analytics administers the survey to providers using mail, email, and phone. Of 114,880 email and mail surveys from 2016, 10,240 providers responded (response rate, 8.9%); of 62,632 phone surveys, 12,178 providers responded (response rate, 18.8%). The total response rate was 12.6% for all providers.

Data Collection

SPH Analytics received survey results from providers and built a deidentified data set at the provider–plan level using their survey data and AIS health plan demographic data. Each plan was assigned a unique numerical identifier so responses could be compiled for each plan. SPH Analytics then shared the deidentified data with the University of Pittsburgh Medical Center researchers who conducted analyses. The data set included 22,418 provider surveys for 76 health plans, of which 3158 were completed by physicians.

Outcomes/Covariates of Interest and Statistical Analysis

For each physician–plan dyad, we included the following provider satisfaction domains described previously as outcomes of interest: (1) overall health plan rating, (2) financial issues, (3) utilization and quality management, (4) network/coordination of care, (5) pharmacy, (6) call center experiences, (7) provider relations, and (8) provider recommendation of the sponsor plan to other practices.

We assessed the association between the following characteristics and outcomes of interest using multivariable linear regression, weighted by the number of providers who completed surveys for each plan: vertical integration status, defined as the integration of provider and payer systems and categorized using publicly available lists from Robert Wood Johnson Foundation, McKinsey, and Avalere (eAppendix Table [eAppendix available at ajmc.com])12-14; health plan size (stratified by ≤100,000, 100,001-500,000, 500,001-1 million, 1,000,001-2 million, and >2 million enrollees); practice size (stratified by practices having 1 physician, 2-5 physicians, and >5 physicians); provider type (stratified by primary care, specialists, and behavioral health physicians); and years of practice (stratified by <5 years, 5-15 years, and >15 years). In addition to these variables, we also adjusted our models for HHS region, number of insurance companies accepted by a respective provider’s practice, and proportion of a practice’s managed care volume represented by a respective health plan. We clustered deidentified provider responses based on the sponsored health plans they were assessing and, because we did not have unique identifiers for provider responders, used robust standard error estimation to account for potential correlation in a scenario in which the same provider responded to surveys about multiple health plans. Missing data were deemed missing completely at random through a multistep statistical verification process that included visual inspection of missing data, tabulating missing data for each variable, and performing Little’s test to assess the assumption that missing data were missing completely at random. Analyses were performed using Stata 14 (StataCorp LP; College Station, Texas) and SAS 9.4 (SAS Institute Inc; Cary, North Carolina).


 
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