Navapat Nananukul, Mayank Kejriwal<\/h3>\n\n\n\nJAMA Netw Open. <\/em>2025;8(5):e2512474. doi:10.1001\/jamanetworkopen.2025.12474<\/h3>\n\n\n\nIntroduction<\/p>\n\n\n\n
The US has experienced a chronic shortage of physicians in certain geographic regions, especially those that may be deprived.1<\/a><\/sup> Understanding the factors influencing the practice locations of newly licensed physicians is important for addressing health inequities.2<\/a><\/sup> Although previous studies have examined overall physician distribution, less is known about the associations between physicians\u2019 characteristics and the likelihood of initially practicing in socioeconomically deprived areas, particularly for physicians from top-tier medical schools, who often have access to more resources and advanced training and whose placement in underserved areas may be valuable for closing health equity gaps.3<\/a><\/sup>,4<\/a><\/sup> This study quantifies the association between physicians\u2019 characteristics, including stated gender, medical school, and specialty, with their likelihood of practicing in socioeconomically deprived areas.<\/a><\/p>\n\n\n\nMethods<\/p>\n\n\n\n
Physician data from the Centers for Medicare & Medicaid Services National Downloadable File was combined with socioeconomic data from the Area Deprivation Index (ADI) Neighborhood Atlas (eMethods and eTable in Supplement 1<\/a>). ADI is a validated measure of neighborhood socioeconomic disadvantage, incorporating factors such as income, education, employment, and housing quality.5<\/a><\/sup> We performed a cross-sectional study by analyzing 2 cohorts of newly licensed physicians (2015 and 2020) for which ADI ranks are available. This study analyzed publicly available, open-government data and was therefore not considered human participants research. Institutional review board approval and informed consent were not required in accordance with federal guidelines (45 CFR \u00a746). STROBE<\/a> reporting guidelines were followed.<\/a><\/p>\n\n\n\nWe used regression analysis to measure associations between physicians\u2019 characteristics and likelihood of practicing in high ADI-ranked (ie, socioeconomically deprived) areas. The primary outcome variable was binary, indicating whether a physician practiced in an area at or above the 80th percentile of the national ADI ranking, vs lower ADI area. Factors include gender, specialty group, and graduation from top-ranked medical schools (eMethods in Supplement 1<\/a>).<\/a><\/p>\n\n\n\nResults<\/p>\n\n\n\n
Of the 83\u202f833 physicians in 2015, those from top-ranked medical institutions had 52% lower odds of practicing in socioeconomically deprived areas compared with physicians from lower-ranked institutions (odds ratio [OR], 0.48; 95% CI, 0.43-0.54; P<\/em>\u2009<\u2009.001), with similar findings in 2020 (OR, 0.50; 95% CI, 0.41-0.61; P<\/em>\u2009<\u2009.001) (Table<\/a>). Compared with primary care physicians, specialists from 11 of 13 specialties had lower odds of practicing in socioeconomically deprived areas in 2015, whereas 8 of 13 had lower odds in 2020.<\/a><\/p>\n\n\n\nThe distribution of physicians across the US was different when comparing physicians from top-ranked institutions and lower-ranked institutions. The\u00a0Figure<\/a>\u00a0shows that the number of physicians from top-ranked institutions was negatively associated with the location\u2019s socioeconomic deprivation, even after controlling for population. In contrast, physicians from lower-ranked institutions exhibited the inverse trend.<\/p>\n\n\n\n![\"\"\/](\"https:\/\/cdn.jamanetwork.com\/ama\/content_public\/journal\/jamanetworkopen\/939603\/zld250072f1_1747416636.152.png?Expires=1756174316&Signature=l8lkemwHUBht6zq2QK7E2BOuKn--Yq-Bm8aojbHmTYA4Rkk5yRsqXxJh3d7sqmkC9d7hqGVtpZFdl65Sw~8JnNNafq64RpK2X-o9VrZGtkOMxOk9dR8mFu6FdwCx4hRYZ3eUoyyJ6ICQ27LJr5WAM8nGS08uWy4LoNmoneRk~vZqrCmQXyD8EXqI03aZWm17u89gUioCR6f4kq2eAPr6dL36UsISZLp7HI6Y7n2ZHbiq~0yIt3bM7Ch3LcB2UjILZ-kSHa~3RgSC955dDXJ7inlPZSp9oSwLrQ-oo3IW-156pg9mqQkkEdSZExj7GfOrtImfjlDXnO3eipQ-62aYFw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\")
<\/figure>\n\n\n\n![\"\"\/](\"https:\/\/cdn.jamanetwork.com\/ama\/content_public\/journal\/jamanetworkopen\/939603\/zld250072t1_1747416636.142.png?Expires=1756174316&Signature=eCm1U~F3hB1IrPHe7Z83kbpb68g7Qg09JxSHA4dDpae7J8isxwsn6Lk31nybarwS3KqUF-W2s5XgyjFAqALrc9NdITZcTIL~zjy4-9f8XzR-~jHqMgzdOYC0jCruD5keHKw0Ei67qJa8HJaeIduizgZF1fJDLJhKvFDu4MN~u~~e5K36eVa6soWDWtkHv47Nm1OR3jQee6eyvecusHvmX0vsZ3bX8A~tMLQYB27mmFQFMQ3X4VyirPkGVgozj2mp82BeTBLcYnXkFfkXbN5rWltAKwzrNwbrqZAboIjuC1ooAtgUxZvAv2ZQXOOpjW5OfONlav5oY4Eht~deBJFW3g__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\")
<\/figure>\n\n\n\nDiscussion<\/p>\n\n\n\n
This cross-sectional study found that an area\u2019s ADI was significantly associated with newly licensed health care physicians\u2019 decision to practice in that area, and the association was especially acute for physicians from top-ranked institutions and certain specialties. One possible reason is that factors associated with high ADI areas\u2014limited resources, lower income potential, or fewer professional development opportunities\u2014may demotivate ambitious physicians from working in these areas.6<\/a><\/sup> However, the analysis does not permit a causal investigation. Regardless of the reason, the data show that many medical specialties have lower representation in socioeconomically deprived areas compared with primary care, which may contribute to disparities in specialized health care access in deprived areas. The findings underscore the need for targeted initiatives to incentivize physicians, particularly specialists and top medical graduates, to practice in socioeconomically disadvantaged regions.<\/a><\/p>\n\n\n\nThis study has limitations. Although medical school ranking was considered, data on the actual residency training location and race and ethnicity were unavailable. These 2 factors potentially affect initial practice preferences. Physicians\u2019 childhood environments and financial debt could also impact their career location decisions. Finally, the study year of 2020 overlapped with the COVID-19 pandemic, which disproportionately affected underserved communities and may have introduced bias.<\/p>\n","protected":false},"excerpt":{"rendered":"
Research Letter Equity, Diversity, and Inclusion […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[32,23],"tags":[],"_links":{"self":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/28556"}],"collection":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=28556"}],"version-history":[{"count":2,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/28556\/revisions"}],"predecessor-version":[{"id":28884,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/28556\/revisions\/28884"}],"wp:attachment":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=28556"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=28556"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=28556"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Introduction<\/p>\n\n\n\n
The US has experienced a chronic shortage of physicians in certain geographic regions, especially those that may be deprived.1<\/a><\/sup> Understanding the factors influencing the practice locations of newly licensed physicians is important for addressing health inequities.2<\/a><\/sup> Although previous studies have examined overall physician distribution, less is known about the associations between physicians\u2019 characteristics and the likelihood of initially practicing in socioeconomically deprived areas, particularly for physicians from top-tier medical schools, who often have access to more resources and advanced training and whose placement in underserved areas may be valuable for closing health equity gaps.3<\/a><\/sup>,4<\/a><\/sup> This study quantifies the association between physicians\u2019 characteristics, including stated gender, medical school, and specialty, with their likelihood of practicing in socioeconomically deprived areas.<\/a><\/p>\n\n\n\n Methods<\/p>\n\n\n\n Physician data from the Centers for Medicare & Medicaid Services National Downloadable File was combined with socioeconomic data from the Area Deprivation Index (ADI) Neighborhood Atlas (eMethods and eTable in Supplement 1<\/a>). ADI is a validated measure of neighborhood socioeconomic disadvantage, incorporating factors such as income, education, employment, and housing quality.5<\/a><\/sup> We performed a cross-sectional study by analyzing 2 cohorts of newly licensed physicians (2015 and 2020) for which ADI ranks are available. This study analyzed publicly available, open-government data and was therefore not considered human participants research. Institutional review board approval and informed consent were not required in accordance with federal guidelines (45 CFR \u00a746). STROBE<\/a> reporting guidelines were followed.<\/a><\/p>\n\n\n\n We used regression analysis to measure associations between physicians\u2019 characteristics and likelihood of practicing in high ADI-ranked (ie, socioeconomically deprived) areas. The primary outcome variable was binary, indicating whether a physician practiced in an area at or above the 80th percentile of the national ADI ranking, vs lower ADI area. Factors include gender, specialty group, and graduation from top-ranked medical schools (eMethods in Supplement 1<\/a>).<\/a><\/p>\n\n\n\n Results<\/p>\n\n\n\n Of the 83\u202f833 physicians in 2015, those from top-ranked medical institutions had 52% lower odds of practicing in socioeconomically deprived areas compared with physicians from lower-ranked institutions (odds ratio [OR], 0.48; 95% CI, 0.43-0.54; P<\/em>\u2009<\u2009.001), with similar findings in 2020 (OR, 0.50; 95% CI, 0.41-0.61; P<\/em>\u2009<\u2009.001) (Table<\/a>). Compared with primary care physicians, specialists from 11 of 13 specialties had lower odds of practicing in socioeconomically deprived areas in 2015, whereas 8 of 13 had lower odds in 2020.<\/a><\/p>\n\n\n\n The distribution of physicians across the US was different when comparing physicians from top-ranked institutions and lower-ranked institutions. The\u00a0Figure<\/a>\u00a0shows that the number of physicians from top-ranked institutions was negatively associated with the location\u2019s socioeconomic deprivation, even after controlling for population. In contrast, physicians from lower-ranked institutions exhibited the inverse trend.<\/p>\n\n\n\n Discussion<\/p>\n\n\n\n This cross-sectional study found that an area\u2019s ADI was significantly associated with newly licensed health care physicians\u2019 decision to practice in that area, and the association was especially acute for physicians from top-ranked institutions and certain specialties. One possible reason is that factors associated with high ADI areas\u2014limited resources, lower income potential, or fewer professional development opportunities\u2014may demotivate ambitious physicians from working in these areas.6<\/a><\/sup> However, the analysis does not permit a causal investigation. Regardless of the reason, the data show that many medical specialties have lower representation in socioeconomically deprived areas compared with primary care, which may contribute to disparities in specialized health care access in deprived areas. The findings underscore the need for targeted initiatives to incentivize physicians, particularly specialists and top medical graduates, to practice in socioeconomically disadvantaged regions.<\/a><\/p>\n\n\n\n This study has limitations. Although medical school ranking was considered, data on the actual residency training location and race and ethnicity were unavailable. These 2 factors potentially affect initial practice preferences. Physicians\u2019 childhood environments and financial debt could also impact their career location decisions. Finally, the study year of 2020 overlapped with the COVID-19 pandemic, which disproportionately affected underserved communities and may have introduced bias.<\/p>\n","protected":false},"excerpt":{"rendered":" Research Letter Equity, Diversity, and Inclusion […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[32,23],"tags":[],"_links":{"self":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/28556"}],"collection":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=28556"}],"version-history":[{"count":2,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/28556\/revisions"}],"predecessor-version":[{"id":28884,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/28556\/revisions\/28884"}],"wp:attachment":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=28556"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=28556"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=28556"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}<\/figure>\n\n\n\n<\/figure>\n\n\n\n