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      Comparison of Dermatologist Density Between Urban and Rural Counties in the United States

      1 , 1 , 2 , 2 , 1
      JAMA Dermatology
      American Medical Association (AMA)

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          Abstract

          <p class="first" id="d4991205e252">This study analyzes county-level data from nationwide US data to compare dermatologist density between urban and rural areas. </p><div class="section"> <a class="named-anchor" id="ab-doi180042-1"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e258">Questions</h5> <p id="d4991205e260">What are the longitudinal dermatologist density trends, and are there urban and rural disparities? </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-2"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e263">Findings</h5> <p id="d4991205e265">In this study county-level data from the Area Health Resources File, from 1995 to 2013, dermatologist density increased the most in rural followed by nonmetropolitan and metropolitan counties; however, the gap between metropolitan and other areas also widened. Dermatologists were heterogeneously distributed and consistently located in well-resourced communities. </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-3"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e268">Meaning</h5> <p id="d4991205e270">The findings suggest that substantial disparities in the geographic distribution of dermatologists exist and have been increasing with time; correcting workforce disparities is important for patient care. </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-4"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e274">Importance</h5> <p id="d4991205e276">As the US population continues to increase and age, there is an unmet need for dermatologic care; therefore, it is important to identify and understand the characteristics and patterns of the dermatologist workforce. </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-5"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e279">Objective</h5> <p id="d4991205e281">To analyze the longitudinal dermatologist density and urban-rural disparities using a standardized classification scheme. </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-6"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e284">Design, Setting, and Participants</h5> <p id="d4991205e286">This study analyzed county-level data for 1995 to 2013 from the Area Health Resources File to evaluate the longitudinal trends and demographic and environmental factors associated with the geographic distribution of dermatologists. </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-7"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e289">Main Outcomes and Measures</h5> <p id="d4991205e291">Active US dermatologist and physician density.</p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-8"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e294">Results</h5> <p id="d4991205e296">In this study of nationwide data on dermatologists, dermatologist density increased by 21% from 3.02 per 100 000 people to 3.65 per 100 000 people from 1995 to 2013; the gap between the density of dermatologists in urban and other areas increased from 2.63 to 3.06 in nonmetropolitan areas and from 3.41 to 4.03 in rural areas. The ratio of dermatologists older than 55 years to younger than 55 years increased 75% in nonmetropolitan and rural areas (from 0.32 to 0.56) and 170% in metropolitan areas (from 0.34 to 0.93). Dermatologists tended to be located in well-resourced, urban communities. </p> </div><div class="section"> <a class="named-anchor" id="ab-doi180042-9"> <!-- named anchor --> </a> <h5 class="section-title" id="d4991205e299">Conclusions and Relevance</h5> <p id="d4991205e301">Our findings suggest that substantial disparities in the geographic distribution of dermatologists exist and have been increasing with time. Correcting the workforce disparity is important for patient care. </p> </div>

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          Using the 2003 National Survey of Children's Health sponsored by the federal Maternal and Child Health Bureau, we calculated prevalence estimates of eczema nationally and for each state among a nationally representative sample of 102,353 children 17 years of age and under. Our objective was to determine the national prevalence of eczema/atopic dermatitis in the US pediatric population and to further examine geographic and demographic associations previously reported in other countries. Overall, 10.7% of children were reported to have a diagnosis of eczema in the past 12 months. Prevalence ranged from 8.7 to 18.1% between states and districts, with the highest prevalence reported in many of the East Coast states, as well as in Nevada, Utah, and Idaho. After adjusting for confounders, metropolitan living was found to be a significant factor in predicting a higher disease prevalence with an odds ratio of 1.67 (95% confidence interval of 1.19-2.35, P=0.008). Black race (odds ratio 1.70, P=0.005) and education level in the household greater than high school (odds ratio 1.61, P=0.004) were also significantly associated with a higher prevalence of eczema. The wide range of prevalence suggests that social or environmental factors may influence disease expression.
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            Recent specialty choices of graduating US medical students suggest that lifestyle may be an increasingly important factor in their career decision making. To determine whether and to what degree controllable lifestyle and other specialty-related characteristics are associated with recent (1996-2002) changes in the specialty preferences of US senior medical students. Specialty preference was based on analysis of results from the National Resident Matching Program, the San Francisco Matching Program, and the American Urological Association Matching Program from 1996 to 2002. Specialty lifestyle (controllable vs uncontrollable) was classified using earlier research. Log-linear models were developed that examined specialty preference and the specialty's controllability, income, work hours, and years of graduate medical education required. Proportion of variability in specialty preference from 1996 to 2002 explained by controllable lifestyle. The specialty preferences of US senior medical students, as determined by the distribution of applicants across selected specialties, changed significantly from 1996 to 2002 (P<.001). In the log-linear model, controllable lifestyle explained 55% of the variability in specialty preference from 1996 to 2002 after controlling for income, work hours, and years of graduate medical education required (P<.001). Perception of controllable lifestyle accounts for most of the variability in recent changing patterns in the specialty choices of graduating US medical students.
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              Critical factors for designing programs to increase the supply and retention of rural primary care physicians.

              The Physician Shortage Area Program (PSAP) of Jefferson Medical College (Philadelphia, Pa) is one of a small number of medical school programs that addresses the shortage of rural primary care physicians. However, little is known regarding why these programs work. To identify factors independently predictive of rural primary care supply and retention and to determine which components of the PSAP lead to its outcomes. Retrospective cohort study. A total of 3414 Jefferson Medical College graduates from the classes of 1978-1993, including 220 PSAP graduates. Rural primary care practice and retention in 1999 as predicted by 19 previously collected variables. Twelve variables were available for all classes; 7 variables were collected only for 1978-1982 graduates. Freshman-year plan for family practice, being in the PSAP, having a National Health Service Corps scholarship, male sex, and taking an elective senior family practice rural preceptorship (the only factor not available at entrance to medical school) were independently predictive of physicians practicing rural primary care. For 1978-1982 graduates, growing up in a rural area was the only additionally collected independent predictor of rural primary care (odds ratio [OR], 4.0; 95% CI, 2.1-7.6; P<.001). Participation in the PSAP was the only independent predictive factor of retention for all classes (OR, 4.7; 95% CI, 2.0-11.2; P<.001). Among PSAP graduates, taking a senior rural preceptorship was independently predictive of rural primary care (OR, 2.5; 95% CI, 1.3-4.7; P =.004). However, non-PSAP graduates with 2 key selection characteristics of PSAP students (having grown up in a rural area and freshman-year plans for family practice) were 78% as likely as PSAP graduates to be rural primary care physicians, and 75% as likely to remain, suggesting that the admissions component of the PSAP is the most important reason for its success. In fact, few graduates without either of these factors were rural primary care physicians (1.8%). Medical educators and policy makers can have the greatest impact on the supply and retention of rural primary care physicians by developing programs to increase the number of medical school matriculants with background and career plans that make them most likely to pursue these career goals. Curricular experiences and other factors can further increase these outcomes, especially by supporting those already likely to become rural primary care physicians.
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                Author and article information

                Journal
                JAMA Dermatology
                JAMA Dermatol
                American Medical Association (AMA)
                2168-6068
                November 01 2018
                November 01 2018
                : 154
                : 11
                : 1265
                Affiliations
                [1 ]The Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York
                [2 ]Yale University School of Medicine, New Haven, Connecticut
                Article
                10.1001/jamadermatol.2018.3022
                6248119
                30193349
                d48b9538-f38c-41e1-9d08-1f914f85ec1d
                © 2018
                History

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