{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:07:21Z","timestamp":1782846441787,"version":"3.54.5"},"reference-count":29,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Cancer"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Residents in persistent poverty areas experience higher cancer mortality due to social determinants of health that negatively affect multiple factors, including health behaviors.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to characterize demographic, clinical, and social determinant of health factors among survivors of cancer in persistent poverty areas using electronic health record (EHR) data\u2014including an embedded social risk screener and natural language processing (NLP) of social work notes\u2014to inform community-engaged adaptation of lifestyle interventions.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n EHR data from a large multispecialty group practice were extracted for patients with cancer residing in zip codes inclusive of persistent poverty areas targeted for a health behavior intervention and receiving care between January 2018 and November 2023. Self-reported social determinant of health data were obtained using the Protocol for Responding to and Assessing Patients\u2019 Assets, Risks, and Experiences (PRAPARE) and through NLP of social histories from a social work visit.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n We identified 2672 unique patients with cancer, of whom 578 (21.6%) had PRAPARE data and 1597 (59.8%) had social history data available for analysis. The most common cancers among survivors (n=1420, 53.1% female; n=1299, 48.6% Black individuals; mean age 65.2, SD 13.7 years) included breast (n=536, 20.1%), prostate (n=400, 15%), and lymphoid or hematopoietic (n=323, 12.1%) cancer. Among survivors in persistent poverty areas (n=509, 19%; all with a high Social Vulnerability Index), 34.6% (176\/509) were single, 55.4% (282\/509) had Medicare coverage (with only 73\/509, 14.3% having private insurance), 36.5% (186\/509) had obesity, 63.9% (325\/509) had hypertension, and 31.2% (159\/509) had diabetes. Of survivors in persistent poverty areas with PRAPARE data, 15.8% (19\/120) lacked transportation, 4.2% (5\/120) lived with housing insecurity, and 6.7% (8\/120) felt unsafe where they lived.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Innovative EHR and NLP approaches identified several socioeconomic and safety-related challenges along with opportunities for health behavior interventions to leverage Medicare coverage and target multiple comorbidities when adapting interventions for survivors of cancer living in persistent poverty areas.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/81054","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T19:01:25Z","timestamp":1776106885000},"page":"e81054-e81054","source":"Crossref","is-referenced-by-count":0,"title":["Leveraging Innovative Electronic Health Record Data to Characterize Social Determinants of Health Among Survivors of Cancer in Persistent Poverty Areas: Cross-Sectional Study"],"prefix":"10.2196","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4223-9127","authenticated-orcid":false,"given":"Shiori","family":"Tanaka","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4216-8381","authenticated-orcid":false,"given":"Laura Q","family":"Rogers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0728-2237","authenticated-orcid":false,"given":"Lisa","family":"Zubkoff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4705-165X","authenticated-orcid":false,"given":"Lori","family":"Bateman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5241-932X","authenticated-orcid":false,"given":"Wendy","family":"Demark-Wahnefried","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4188-9785","authenticated-orcid":false,"given":"Gabrielle","family":"Rocque","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9982-3223","authenticated-orcid":false,"given":"Sejong","family":"Bae","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9329-3268","authenticated-orcid":false,"given":"Maria","family":"Pisu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4290-6014","authenticated-orcid":false,"given":"James","family":"Booth","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6554-6237","authenticated-orcid":false,"given":"Carrie R","family":"Howell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,4,13]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3322\/caac.21820","article-title":"Cancer statistics, 2024","volume":"74","author":"Siegel","journal-title":"CA Cancer J Clin"},{"issue":"10","key":"R2","doi-asserted-by":"publisher","first-page":"1949","DOI":"10.1158\/1055-9965.EPI-20-0007","article-title":"Persistent poverty and cancer mortality rates: an analysis of county-level poverty designations","volume":"29","author":"Moss","journal-title":"Cancer Epidemiol Biomarkers Prev"},{"issue":"8","key":"R3","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.43445","article-title":"Addressing cancer disparities through community engagement: lessons and best practices","volume":"15","author":"Kale","journal-title":"Cureus"},{"issue":"3","key":"R4","doi-asserted-by":"publisher","first-page":"2877","DOI":"10.1007\/s00520-021-06582-2","article-title":"Feasibility, acceptability, and effects of behavior change interventions for improving multiple dietary behaviors among cancer survivors: a systematic review","volume":"30","author":"Gan","journal-title":"Support Care Cancer"},{"issue":"5","key":"R5","doi-asserted-by":"publisher","first-page":"3745","DOI":"10.1007\/s00520-021-06739-z","article-title":"Benefits of weight loss programs for breast cancer survivors: a systematic reviews and meta-analysis of randomized controlled trials","volume":"30","author":"Wang","journal-title":"Support Care Cancer"},{"issue":"5","key":"R6","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1093\/tbm\/ibz176","article-title":"A systematic review and meta-analysis of physical activity interventions among colorectal cancer survivors","volume":"10","author":"Mbous","journal-title":"Transl Behav Med"},{"key":"R7","unstructured":"Benson C Bishaw A Glassman B . Persistent poverty in counties and census tracts. United States Census Bureau; 2023. 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Introducing the Social Interventions Research and Evaluation Network. SIREN; 2017."},{"key":"R15","unstructured":"Billioux A Verlander K Anthony S Alley D . Standardized screening for health-related social needs in clinical settings: the accountable health communities screening tool. National Academy of Medicine. 2017. 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