{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T14:19:09Z","timestamp":1788185949576,"version":"build-2803163510"},"reference-count":26,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"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":["Health Care Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Social determinants of health (SDoH) are pivotal in influencing health outcomes and disparities across various populations. Real\u2010world data rich in SDoH information, such as electronic medical records (EMRs), can considerably enhance public health interventions. However, in Chinese medical practice, these non\u2010clinical factors are often neglected, with many healthcare providers failing to recognize the importance of SDoH information in the improvement of patient care. The objective of this study is to explore the feasibility and effectiveness of extracting SDoH information from Chinese EMRs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed a China\u2010specific SDoH classification framework by integrating findings from relevant research using real\u2010world data. This framework was applied to over three million patient records from Chinese EMRs to examine the completeness and availability of SDoH\u2010related attributes within relevant fields. We also developed a quantitative assessment framework for evaluating SDoH information in EMR fields. This two\u2010dimensional evaluation system measures data completeness and availability using a three\u2010level hierarchical scoring approach, progressing from basic to advanced criteria. Additionally, we analyzed variations in SDoH information extraction across different healthcare institutions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Drawing on the literature and 2000 manually annotated EMRs, we established a standardized framework of SDoH factors, comprising 50 features tailored to the Chinese medical diagnostic and treatment environment. We analyzed over 5.6 million EMRs from 40 hospitals within the National Clinical Research Data Center and found that tables and fields in Chinese EMRs cover all six primary SDoH categories, encompassing 25 out of 50 specific attributes. However, data extraction feasibility was relatively poor, with only seven features being fully extractable, with most \u201csocial and community context\u201d data missing. Our evaluation of 43 electronic health record fields containing SDoH data revealed significant disparities between completeness and availability metrics. The composite completeness score averaged 1.47 (95% confidence interval: 1.20\u20131.73) out of a maximum score of 3. Availability assessments demonstrated notably higher performance with a mean score of 2.14 (95% confidence interval: 1.83\u20132.44) out of a maximum score of 3.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This research established a culturally adapted SDoH framework for China and demonstrated the feasibility of extracting SDoH attributes from Chinese EMRs. Although some SDoH information in EMRs still cannot be captured or requires more advanced data processing to be usable, Chinese EMRs contain a wealth of SDoH data, allowing us to use large existing EMR databases to support ongoing SDoH research. Natural language processing technology has a critical role in this process, underscoring the importance of medical informatics and current artificial intelligence techniques in medicine and public health. Our research lays a foundation for future SDoH studies in China, enabling more comprehensive research and encouraging the government and relevant agencies to focus on SDoH interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/hcs2.70094","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T14:08:56Z","timestamp":1788185336000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Feasibility Assessment of Extracting Social Determinants of Health From Electronic Medical Records: A Multicenter Study Across Chinese Healthcare Institutions"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8197-6643","authenticated-orcid":false,"given":"Mengchun","family":"Gong","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering, Guangdong Medical University Dongguan China"},{"name":"Vice President's Office DHC Technologies Ltd. Beijing China"},{"name":"National Clinical Research Center for Aging Fudan University Affiliated Huashan Hospital Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0495-5918","authenticated-orcid":false,"given":"Zihao","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Medical Research Department DHC Technologies Ltd. Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dandan","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Information Management, State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qilin","family":"Wang","sequence":"additional","affiliation":[{"name":"Medical Research Department DHC Technologies Ltd. Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Endi","family":"Cai","sequence":"additional","affiliation":[{"name":"Medical Research Department DHC Technologies Ltd. Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Liu","sequence":"additional","affiliation":[{"name":"Medical Research Department DHC Technologies Ltd. Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Yu","sequence":"additional","affiliation":[{"name":"Medical Research Department DHC Technologies Ltd. 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