{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T03:45:19Z","timestamp":1790912719381,"version":"4.1.0"},"reference-count":16,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T00:00:00Z","timestamp":1531353600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100004331","name":"Johnson and Johnson","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004331","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmacoepidemiology and Drug"],"published-print":{"date-parts":[[2018,10]]},"abstract":"Abstract<\/jats:title>Purpose<\/jats:title>To quantify the sensitivity and positive predictive value (PPV) of body mass index (BMI)\u2010related ICD\u20109\u2010CM and ICD\u201010\u2010CM diagnosis codes in claims data.<\/jats:p><\/jats:sec>Methods<\/jats:title>De\u2010identified electronic health record (EHR) and claims data were obtained from the Optum Integrated Claims\u2010Clinical Database for cross\u2010sections of commercial and Medicare Advantage health plan members age\u00a0\u2265\u00a020\u00a0years in 2013, 2014, and 2016. In each calendar year, health plan members' BMI as coded in the insurance claims data (error\u2010prone measure) was compared with their BMI as recorded in the EHR (gold standard) to estimate the sensitivity and PPV of BMI\u2010related ICD\u20109\u2010CM and ICD\u201010\u2010CM diagnosis codes. The unit of analysis was the person\u2010year.<\/jats:p><\/jats:sec>Results<\/jats:title>The study sample included 746\u00a0763 distinct health plan members who contributed 1\u00a0116\u00a0283 eligible person\u2010years (median age 56\u00a0years; 57% female; 65% commercially insured and 35% with Medicare Advantage). BMI\u2010related diagnoses were coded for 14.6%. The sensitivity of BMI\u2010related diagnoses codes for the detection of underweight, normal weight, overweight, and obesity was 10.1%, 3.7%, 6.0%, and 25.2%, and the PPV was 49.0% for underweight, 89.6% for normal weight, 73.4% for overweight, and 92.4% for obesity, respectively. The sensitivity of BMI\u2010related diagnosis codes was higher in the ICD\u201010\u2010CM era relative to the ICD\u20109\u2010CM era.<\/jats:p><\/jats:sec>Conclusions<\/jats:title>The PPV of BMI\u2010related diagnosis codes for normal weight, overweight, and obesity was high (>70%) but the sensitivity was low (<30%). BMI\u2010related diagnoses were more likely to be coded in patients with class II or III obesity (BMI \u226535\u00a0kg\/m2<\/jats:sup>), and in 2016 relative to 2013 or 2014.<\/jats:p><\/jats:sec>","DOI":"10.1002\/pds.4617","type":"journal-article","created":{"date-parts":[[2018,7,13]],"date-time":"2018-07-13T02:35:06Z","timestamp":1531449306000},"page":"1092-1100","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":71,"title":["Validation of body mass index (BMI)\u2010related ICD\u20109\u2010CM and ICD\u201010\u2010CM administrative diagnosis codes recorded in US claims data"],"prefix":"10.1002","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5882-5388","authenticated-orcid":false,"given":"Eric M.","family":"Ammann","sequence":"first","affiliation":[{"name":"Epidemiology, Medical Devices Johnson & Johnson New Brunswick NJ USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iftekhar","family":"Kalsekar","sequence":"additional","affiliation":[{"name":"Epidemiology, Medical Devices Johnson & Johnson New Brunswick NJ USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Yoo","sequence":"additional","affiliation":[{"name":"Epidemiology, Medical Devices Johnson & Johnson New Brunswick NJ USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen S.","family":"Johnston","sequence":"additional","affiliation":[{"name":"Epidemiology, Medical Devices Johnson & Johnson New Brunswick NJ USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,7,12]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamacardio.2018.0022"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.2337\/dc07-1934"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00268-006-0305-0"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/0163278714553661"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/1472-6963-14-70"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12913-016-1636-7"},{"key":"e_1_2_10_8_1","article-title":"Under\u2010coding of secondary conditions in coded hospital health data: impact of co\u2010existing conditions, death status and number of codes in a record","author":"Peng M","year":"2016","journal-title":"Health Informatics J"},{"issue":"2","key":"e_1_2_10_9_1","first-page":"51S","article-title":"Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults\u2014The Evidence Report","volume":"6","year":"1998","journal-title":"Obes Res"},{"key":"e_1_2_10_10_1","unstructured":"HealthIT.Gov. Step 5: Achieve Meaningful Use Stage 2: Record Vital SignsHow to Implement EHRs2014;https:\/\/www.healthit.gov\/providers\u2010professionals\/achieve\u2010meaningful\u2010use\/core\u2010measures\u20102\/record\u2010vital\u2010signs. Accessed 2017 November 13."},{"key":"e_1_2_10_11_1","unstructured":"PinsonRD.Body Mass Index and Malnutrition: Interrelated Comorbidities.2011;http:\/\/www.hcpro.com\/content\/271737.pdf. Accessed Nov 13 2017."},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11999-012-2352-1"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1475-6773.2007.00822.x"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.1619"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.spinee.2014.04.025"},{"key":"e_1_2_10_16_1","unstructured":"National Center for Health Statistics.FastStats: Births and Natality.2017;https:\/\/www.cdc.gov\/nchs\/fastats\/births. htm. 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