{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T07:04:37Z","timestamp":1790665477603,"version":"4.1.0"},"reference-count":19,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"content-version":"vor","delay-in-days":27,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Rural Health"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>AI can support hospitals\u2019 business workflow as well as their patient care. This study investigates whether rural hospitals' AI adoption is influenced by their proximity to metro areas, which often offer better infrastructure, skilled labor, and other resources, with particular attention to differences across individual clinical and business operation use cases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Using the 2024 American Hospital Association's Annual Survey (\n                      <jats:italic>n<\/jats:italic>\n                      = 6173 hospitals), the likelihood of AI adoption for eight clinical and six business uses by geography was explored. Hospital ownership type and size were controlled. Geography was determined at the county level and used the Rural\u2013Urban Continuum Code (RUCC), with metropolitan hospitals as 1\u20133, non\u2010metro or rural as 4\u20139, and then non\u2010metro and rural were further divided by metro adjacency.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      Across the country, almost 30% of hospitals adopted AI for clinical tasks and 26% adopted AI for administrative tasks. However, the farther a hospital was from a metro area, the less frequently it adopted AI. Compared to metro hospitals, non\u2010metro metro\u2010adjacent hospitals were 29.6% less likely (odds ratio [OR] = 0.70, confidence interval [CI]: 0.53\u20130.93,\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.05) and non\u2010metro not\u2010adjacent hospitals were 61.7% (OR = 0.38, CI: 0.26\u20130.52,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a0.001) less likely to use AI for clinical purposes. As for administrative uses, compared to metro hospitals, non\u2010metro metro\u2010adjacent hospitals were 48.9% (OR = 0.51, CI: 0.40\u20130.66,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.001) less likely and non\u2010metro not\u2010adjacent hospitals were 70.4% (OR = 0.30, CI: 0.22\u20130.39,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.001) less likely to use AI. This same pattern persisted for most individual\u2010use cases.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI adoption remains limited in hospitals, particularly in non\u2010metro areas. The impact on adoption rate differences is unclear, but it is an important consideration moving forward to reduce urban\u2013rural health disparities and improve business operations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jrh.70224","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T06:35:55Z","timestamp":1790663755000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adoption of AI and its Use Cases in Urban and Rural Hospitals"],"prefix":"10.1111","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6944-6620","authenticated-orcid":false,"given":"Nicole M.","family":"Summers\u2010Gabr","sequence":"first","affiliation":[{"name":"Department of Community Development Federal Reserve Bank of St. Louis  St. Louis Missouri 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of Regional Growth and Development Theories","author":"McCann P.","year":"2019"},{"key":"e_1_2_9_13_1","unstructured":"American Hospital Association \u201c2024 AHA Annual Survey \u201dAmerican Hospital Association 2024 https:\/\/www.aha.org\/system\/files\/media\/file\/2025\/03\/2024\u2010AHA\u2010Annual\u2010Survey\u201020250304.pdf."},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/jrh.70100"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.2196\/34678"},{"key":"e_1_2_9_16_1","unstructured":"Chartis \u201c2026 Rural Health State of the State \u201dChartis Healthcare Advisory Services and Analytics 2026 https:\/\/www.chartis.com\/insights\/2026\u2010rural\u2010health\u2010state\u2010state."},{"key":"e_1_2_9_17_1","unstructured":"The Commonwealth Fund \u201cThe State of Rural Primary Care in the United States \u201d issue brief published November2025 https:\/\/www.commonwealthfund.org\/publications\/issue\u2010briefs\/2025\/nov\/state\u2010rural\u2010primary\u2010care\u2010united\u2010states."},{"key":"e_1_2_9_18_1","unstructured":"NTIA \u201cBroadband Equity Access and Deployment (BEAD) Program \u201dNational Telecommunications and Information Administration accessed August 27 2026 https:\/\/broadbandusa.ntia.gov\/funding\u2010programs\/broadband\u2010equity\u2010access\u2010and\u2010deployment\u2010bead\u2010program."},{"key":"e_1_2_9_19_1","unstructured":"Centers for Medicare & Medicaid Services \u201cRural Health Transformation (RHT) Program: Overview \u201dCenters for Medicare & Medicaid Services accessed August 27 2026 https:\/\/www.cms.gov\/initiatives\/rural\u2010health\u2010transformation\u2010rht\u2010program\/overview."},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chbr.2022.100206"}],"container-title":["The Journal of Rural 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