Date Published: April 9, 2019
Publisher: Public Library of Science
Author(s): Keith B. Naylor, Joshua Tootoo, Olga Yakusheva, Scott A. Shipman, Julie P. W. Bynum, Matthew A. Davis, Tayyab Ikram Shah.
Growing physician maldistribution and population demographic shifts have contributed to large geographic variation in healthcare access and the emergence of advanced practice providers as contributors to the healthcare workforce. Current estimates of geographic accessibility of physicians and advanced practice providers rely on outdated “provider per capita” estimates that have shortcomings.
To apply state of the art methods to estimate spatial accessibility of physician and non-physician clinician groups and to examine factors associated with higher accessibility.
We used a combination of provider location, medical claims, and U.S. Census data to perform a national study of health provider accessibility. The National Plan and Provider Enumeration System was used along with Medicare claims to identify providers actively caring for patients in 2014 including: primary care physicians (i.e., internal medicine and family medicine), specialists, nurse practitioners, and chiropractors. For each U.S. ZIP code tabulation area, we estimated provider accessibility using the Variable-distance Enhanced 2 step Floating Catchment Area method and performed a Getis-Ord Gi* analysis for each provider group. Generalized linear models were used to examine associations between population characteristics and provider accessibility.
National spatial patterns of the provider groups differed considerably. Accessibility of internal medicine most resembled specialists with high accessibility in urban locales, whereas relative higher accessibility of family medicine physicians was concentrated in the upper Midwest. In our adjusted analyses independent factors associated with higher accessibility were very similar between internal medicine physicians and specialists–presence of a medical school in the county was associated with approximately 70% higher accessibility and higher accessibility was associated with urban locales. Nurse practitioners were similar to family medicine physicians with both having higher accessibility in rural locales.
The Variable-distance Enhanced 2 step Floating Catchment Area method is a viable approach to measure spatial accessibility at the national scale.
By the year 2020, the Health Resources and Services Administration (HRSA) estimates that there will be a shortage of 20,400 primary care physicians in the United States. Policymakers have long debated potential solutions to the national shortfall of physicians–of which, the most straightforward being to simply increase supply. However, approaches aimed at increasing the number of physicians graduating from medical schools neglect to consider the financial incentive for students to enter into procedural and surgical based non-primary care specialties and the forces that drive physicians to practice in already oversupplied locales. Interestingly, in part due to strategic efforts coupled with changes in professional education, advanced practice providers such as nurse practitioners (NPs) and physician assistants have played an increasingly important role in the U.S. healthcare workforce.[3, 4] In 2010, greater than 55,000 NPs were practicing primary care in the U.S., and the American Association of Nurse Practitioners estimates that of the greater than 23,000 NPs who graduated in 2015–2016, 85% were trained in primary care.[5, 6]
We used a combination of national data on provider location and administrative claims to estimate spatial accessibility of primary care physicians (comparing internal medicine to family medicine), specialists, nurse practitioners, and chiropractors using the VE2SFCA method.[16–18] We then merged data from the U.S. Census Bureau to examine population factors associated with spatial accessibility.
The objective of our study was to compare spatial accessibility of different healthcare provider types using current state of the art geospatial methodology and to examine factors associated with higher spatial accessibility. To our knowledge this is the first study to examine spatial accessibility at the ZCTA level using the VE2SFCA method across the contiguous U.S. Overall, we found spatial accessibility was not equally distributed across geographic areas among all of the five provider types examined–each were found to have distinct areas of concentrated high (and low) spatial accessibility. Most notably, we found that despite both being considered a “primary care physician”, spatial accessibility differed considerably between internal medicine and family medicine physicians (rs = 0.2693, p < 0.001). Internal medicine physicians more resembled specialists, being more likely to be in condensed urban locales and strongly associated with the presence of a medical school (rs = 0.8082, p < 0.001). There are several limitations that should be considered when interpreting the study findings. First, healthcare access represents more than spatial accessibility alone. The concept of access also includes acceptability (patient attitudes and beliefs), accommodation (wait times, provider workload), affordability (cost, insurance coverage), and availability (treatments and services offered). We chose to examine spatial accessibility because it is the fundamental requirement for the other components of access. Second, the VE2SFCA method assumes that all providers and populations that are located within a drive-time based catchment area have equal accessibility. We cede that even within small areas, healthcare accessibility is inequitable. For this reason, we have included sociodemographic population characteristics in the analysis, such as: age, sex, median household income, poverty level, and race/ethnicity. Third, a single PPR of 1:3,500 was used as the threshold value. We selected this value due to its real world use in defining primary care related health professional shortage areas by the U.S. Department of Health and Human Services. Ratios below this value are not felt to be adequate for providing primary care medical services. Forth, discrete distance decay weights were applied to differentiate travel time zones across provider types instead of a continuous function. To properly apply differing distance decay functions to each provider type, patient specific data of actual utilization of health services for each provider type would be necessary. Fifth, linear models examining associations between population characteristics and PRP utilized cross-sectional data and therefore their findings represent associations and we cannot rule out reverse causality. Sixth, provider practice locations were determined based on data from the NPPES and practice addresses were not confirmed for their accuracy. However, in a recent comparison study, the NPPES had the highest accuracy for provider contact information in comparison to other commonly used national sources such as the American Medical Association Physician Masterfile and the SK&A file. Lastly, some sparsely populated areas did not contain healthcare providers or sufficient numbers of residents to be included in the study analysis. These areas are typically located in small rural or remote frontier communities and their representation within the study may be underreported. Disparities in access to primary care services greatly impacts population health.[34, 40] Through use of the VE2SFA method, we have estimated spatial accessibility to primary care providers on a national scale, at ZCTA-level resolution. Unlike, per-capita based provider-to-population rations, VE2SFA spatial accessibility measurements employ dynamic, drive-time based, catchment areas that incorporate population thresholds and an estimation of distance decay in utilization. Our findings indicate that the primary care workforce is unequally distributed across the nation, with internal medicine physicians, family medicine physicians, and nurse practitioners each displaying a unique pattern for their spatial accessibility. The characteristics of populations that live within the areas of high and low spatial accessibility also differed by provider type. In light of these findings, future programs and policies intended to address maldistribution of the primary care workforce may need to be individualized according to provider type, target population, and geographic location. Additional research is needed to explore the factors that influence geographic patterns of spatial accessibility and the interaction between primary care provider groups. Source: http://doi.org/10.1371/journal.pone.0215016