Data on primary care NPs (primary care, adult, family, general gerontology, and general pediatrics, and had an active registration number for full study year) from the National Provider Identifier registry. Data on primary care physicians (nonfederal employees, provided patient care, and held either a doctor of medicine or a doctor of osteopathy degree in general family medicine, general practice, general internal medicine, or general pediatrics) from the American Medical Association Physician Masterfile. The error bars represent 95% CIs.
aIncome quartile defined by proportion of the population with an income level ≤138% of the federal poverty level ($16 394 for a household with 1 individual per year in 2016). The median household income in 2016 was $64 314 for Q1; $52 270 for Q2; $47 227 for Q3; and $39 109 for Q4.
bPopulation density based on the 2013 US Department of Agriculture Rural-Urban Continuum Codes (metropolitan health service area [HSA] included ≥1 metropolitan county; urban HSA, ≥1 urban county with population >2500; and rural HSA, completely rural status or with population <2500).
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Xue Y, Smith JA, Spetz J. Primary Care Nurse Practitioners and Physicians in Low-Income and Rural Areas, 2010-2016. JAMA. 2019;321(1):102–105. doi:10.1001/jama.2018.17944
Nurse practitioners (NPs) constitute the largest and fastest growing group of nonphysician primary care clinicians.1 As the primary care physician (PCP) shortage persists,1 examination of trends in primary care NP supply, particularly in relation to populations most in need, will inform strategies to strengthen primary care capacity. However, such evidence is limited, particularly in combination with physician workforce trends. We thus characterized the temporal trends in the distribution of primary care NPs in low-income and rural areas compared with the distribution of PCPs.
We analyzed trends in 50 states and Washington, DC, from 2010 to 2016. Data on population characteristics and PCPs (definition appears in the legend of the Figure) were from the Area Health Resources File, a national data set compiled from multiple validated sources including the US Census Bureau and the American Medical Association.2 Data on primary care NPs (definition appears in the legend of the Figure) were from the National Provider Identifier registry, which contains information on health care professionals who had financial transactions with the Centers for Medicare & Medicaid Services.3 These data sources have demonstrated convergent validity in prior studies involving primary care workforce estimates.1,4 We further validated the NP estimates by obtaining comparable results with data from the National Sample Survey of NPs.5 We selected health service area (HSA) as the geographic unit of analysis because it was developed to measure the availability of health care resources (eg, health care professionals). Annual clinician supply was measured as the number of clinicians per 100 000 population in an HSA. Income level in the HSA was assessed by quartile rank of the proportion of population at or below 138% of the federal poverty level; HSA metropolitan, urban, and rural status also was determined.
We calculated clinician supply with 95% CIs and examined the temporal trends in supply across income quartiles and metropolitan, urban, and rural areas, comparing trends between clinician groups using 2-level mixed-effects models that specified intercept and year as random effects and controlled for clustering by HSA. Analyses were performed using SAS version 9.4 (SAS Institute Inc). A 2-sided P<.05 was considered statistically significant. The study was exempted by the University of Rochester institutional review board.
From 2010 to 2016, the number of primary care NPs increased from 59 442 to 123 316, and the number of PCPs increased from 225 687 to 243 738. The number of NPs per 100 000 population increased by a mean of 15.3 (95% CI, 14.1-16.4) in the highest income quartile to 21.4 (95% CI, 19.9-22.8) in the lowest income quartile (Table). In contrast, physician supply remained relatively constant (Figure, part A). Overall, NP supply increased more than physician supply (annual change, 3.0 vs −0.02, respectively; difference of 3.1 [95% CI, 2.8-3.3] per 100 000 population per HSA; P < .001). By 2016, NP supply was 33.1 (95% CI, 30.9-35.2) per 100 000 population in the highest income quartile and increased to 41.1 (95% CI, 38.7-43.4) in the lowest income quartile, whereas physician supply declined from 75.1 (95% CI, 71.6-78.6) in the highest income quartile to 52.0 (95% CI, 49.9-54.1) in the lowest income quartile (Table). Similar trends were observed in metropolitan, urban, and rural HSAs (Figure, part B). Primary care NP supply increased more than physician supply by an annual mean of 2.9 (95% CI, 2.6-3.1; P < .001) per 100 000 population in metropolitan areas, 3.2 (95% CI, 2.9-3.5; P < .001) in urban areas, and 4.3 (95% CI, 2.0-6.5; P < .001) in rural areas (Table). By 2016, the highest NP supply was observed in rural HSAs (41.3 [95% CI, 31.2-51.3] per 100 000 population), whereas the highest physician supply was in metropolitan HSAs (68.0 [95% CI, 66.0-70.0] per 100 000 population) (Table).
This analysis demonstrated a narrowing gap between primary care NP and physician workforce supply over time, particularly in low-income and rural areas. These areas have higher demand for primary care clinicians and larger disparities in access to care.6 The growing NP supply in these areas is offsetting low physician supply and thus may increase primary care capacity in underserved communities. Study limitations include the use of different data sources for NPs and physicians; and it is unknown if observed trends have changed from the most recent data in 2016. Continued monitoring of these trends is warranted.
Accepted for Publication: October 23, 2018.
Corresponding Author: Ying Xue, DNSc, RN, University of Rochester School of Nursing, 601 Elmwood Ave, PO Box SON, Rochester, NY 14642 (email@example.com).
Author Contributions: Dr Xue had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Xue.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Xue.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Xue.
Obtained funding: Xue, Spetz.
Administrative, technical, or material support: Xue, Smith.
Supervision: Xue, Spetz.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Xue reported receiving personal fees from the National Council of State Boards of Nursing. Dr Spetz reported receiving grants from the Health Resources and Services Administration, Robert Wood Johnson Foundation, Public Health Institute, Kaiser Foundation Health Plan, Health Care Cost Institute, University of Washington, and California Health Care Foundation and personal fees from the American Organization for Nurse Executives, Massachusetts General Hospital/Partners Healthcare, AARP Center to Champion Nursing in America, Westat/Assistant Secretary for Planning and Evaluation, and California Board of Registered Nursing. No other disclosures were reported.
Funding/Support: The study was supported by grant R80004 from the National Council of State Boards of Nursing.
Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We acknowledge Elizabeth Greener, BA, and Viji Kannan, MPH (both with the University of Rochester Medical Center, Department of Public Health Sciences), for their research assistance with the project; they received graduate student research assistant stipends.
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