{"id":23025,"date":"2025-12-15T13:10:26","date_gmt":"2025-12-15T18:10:26","guid":{"rendered":"https:\/\/www.ices.on.ca\/?post_type=journal_article&p=23025"},"modified":"2025-12-16T13:25:58","modified_gmt":"2025-12-16T18:25:58","slug":"identifying-patients-with-obesity-from-health-administrative-data-diagnostic-accuracy-of-surgical-billing-claims","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/identifying-patients-with-obesity-from-health-administrative-data-diagnostic-accuracy-of-surgical-billing-claims\/","title":{"rendered":"Identifying patients with obesity from health administrative data: diagnostic accuracy of surgical billing claims"},"content":{"rendered":"

Objectives<\/strong> \u2014 Obesity (body mass index, BMI\u2009\u2265\u200930 kg\/m2) is a predictor of patient outcomes across surgical disciplines, but is not accurately captured by diagnostic codes in administrative databases. The objective of this study was to determine the validity of surgeon and anaesthetist billing claims indicating that their patients had concurrent class III obesity (BMI\u2009>\u200940) as compared to patients\u2019 self-reported BMI.<\/p>\n

Methods<\/strong> \u2014 We performed a cross-sectional study of adult patients who had undergone major abdominopelvic, neck, and hip surgery in Ontario from 2011 to 2019, and had also reported their BMI on either the Canadian Community Health Survey or the Ontario Health Study. Physician billing claims for class III obesity were compared to self-reported BMI, and measures of diagnostic accuracy with 95% confidence intervals were calculated.<\/p>\n

Results<\/strong> \u2014 We identified 52,515 patients who had undergone surgery (80.6% abdominopelvic; 19.4% neck\/hip) with median age 57 years and median BMI 26 (range 15\u2013108); 2189 patients (4.2%) reported a BMI\u2009>\u200940. When self-reported BMI was collected within 1 year of surgery, billing claims submitted by either the surgeon, surgical assistant, or anaesthetist had sensitivity 82.9% (95% CI 79.1\u201386.7), specificity 95.5% (95.0\u201396.0), positive predictive value 52.9% (50.1\u201358.5), and negative predictive value 98.9% (98.7\u201399.2) for the identification of BMI\u2009>\u200940. Positive predictive value for the identification of BMI\u2009>\u200930 was 95.4% (93.7\u201397.0).<\/p>\n

Conclusion<\/strong> \u2014 Physician billing claims are specific and sensitive for the identification of patients with BMI\u2009>\u200940 undergoing surgery, enable accurate selection of a population with BMI\u2009>\u200930, and are valid for use in studies conducted with health administrative data.<\/p>\n","protected":false},"excerpt":{"rendered":"

Objectives \u2014 Obesity (body mass index, BMI\u2009\u2265\u200930 kg\/m2) is a predictor of patient outcomes across surgical disciplines, but is not accurately captured by diagnostic codes in administrative databases. The objective of this study was to determine the validity of surgeon and anaesthetist billing claims indicating that their patients had concurrent class III obesity (BMI\u2009>\u200940) as […]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[59,35],"migration-helper-qa-sample-set":[],"class_list":["post-23025","journal_article","type-journal_article","status-publish","hentry","topic-data-science","topic-public-health"],"acf":{"citation":"Cusimano MC, Baxter NN, Moineddin R, Chiu M, Nguyen L, Aktar S, Liu N, Simpson AN, Johnson C, Ferguson SE. Can J Public Health<\/em>. 2025 Dec 15 [Epub ahead of print].","source_url":"https:\/\/doi.org\/10.17269\/s41997-025-01114-5","ices_scientist":[1177,1327,1358],"site":[6733],"research_program":[6741],"news_release":"","journal_article":"","atlas":"","research_report":"","infographic":"","video":"","downloads":null,"links":null,"sitecore_item_id":"","sitecore_item_name":"","sitecore_field_values":"","previous_url":""},"yoast_head":"\nICES | Identifying patients with obesity from health administrative data: diagnostic accuracy of surgical billing claims<\/title>\n<meta name=\"description\" content=\"Objectives \u2014 Obesity (body mass index, BMI\u2009\u2265\u200930 kg\/m2) is a predictor of patient outcomes across surgical disciplines, but is not accurately captured by\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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