{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T06:07:15Z","timestamp":1791958035820,"version":"4.3.4"},"reference-count":23,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T00:00:00Z","timestamp":1681344000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["T32-HL0007633"],"award-info":[{"award-number":["T32-HL0007633"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["T32-HL0007633"],"award-info":[{"award-number":["T32-HL0007633"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIH","award":["R01 HL111024, R01 HL130974, and R01 HL135142"],"award-info":[{"award-number":["R01 HL111024, R01 HL130974, and R01 HL135142"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Objectives<\/jats:title>\n<jats:p>To evaluate methods of identifying patients with systemic sclerosis (SSc) using International Classification of Diseases, Tenth Revision (ICD-10) codes (M34*), electronic health record (EHR) databases and organ involvement keywords, that result in a validated cohort comprised of true cases with high disease burden.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>We retrospectively studied patients in a healthcare system likely to have SSc. Using structured EHR data from January 2016 to June 2021, we identified 955 adult patients with M34* documented 2 or more times during the study period. A random subset of 100 patients was selected to validate the ICD-10 code for its positive predictive value (PPV). The dataset was then divided into a training and validation sets for unstructured text processing (UTP) search algorithms, two of which were created using keywords for Raynaud\u2019s syndrome, and esophageal involvement\/symptoms.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>Among 955 patients, the average age was 60. Most patients (84%) were female; 75% of patients were White, and 5.2% were Black. There were approximately 175 patients per year with the code newly documented, overall 24% had an ICD-10 code for esophageal disease, and 13.4% for pulmonary hypertension. The baseline PPV was 78%, which improved to 84% with UTP, identifying 788 patients likely to have SSc. After the ICD-10 code was placed, 63% of patients had a rheumatology office visit. Patients identified by the UTP search algorithm were more likely to have increased healthcare utilization (ICD-10 codes 4 or more times 84.1% vs 61.7%, p &lt; .001), organ involvement (pulmonary hypertension 12.7% vs 6% p = .011) and medication use (mycophenolate use 28.7% vs 11.4%, p &lt; .001) than those identified by the ICD codes alone.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>EHRs can be used to identify patients with SSc. Using unstructured text processing keyword searches for SSc clinical manifestations improved the PPV of ICD-10 codes alone and identified a group of patients most likely to have SSc and increased healthcare needs.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0283775","type":"journal-article","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T18:29:21Z","timestamp":1681410561000},"page":"e0283775","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":9,"title":["Development and validation of algorithms to build an electronic health record based cohort of patients with systemic sclerosis"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2877-6535","authenticated-orcid":true,"given":"Ann-Marcia C.","family":"Tukpah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan A.","family":"Rose","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diane L.","family":"Seger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul F.","family":"Dellaripa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gary M.","family":"Hunninghake","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David W.","family":"Bates","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,4,13]]},"reference":[{"issue":"3","key":"pone.0283775.ref001","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/S2213-2600(19)30480-1","article-title":"Systemic sclerosis-associated interstitial lung disease","volume":"8","author":"A Perelas","year":"2020","journal-title":"Lancet Respir Med"},{"issue":"5","key":"pone.0283775.ref002","doi-asserted-by":"crossref","first-page":"1700522","DOI":"10.1183\/13993003.00522-2017","article-title":"Pulmonary arterial hypertension: screening challenges in systemic sclerosis and future directions","volume":"49","author":"N Diab","year":"2017","journal-title":"Eur Respir J"},{"issue":"7","key":"pone.0283775.ref003","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1136\/annrheumdis-2016-210503","article-title":"Treatment outcome in early diffuse cutaneous systemic sclerosis: the European Scleroderma Observational Study (ESOS)","volume":"76","author":"AL Herrick","year":"2017","journal-title":"Ann Rheum Dis"},{"issue":"26","key":"pone.0283775.ref004","doi-asserted-by":"crossref","first-page":"2518","DOI":"10.1056\/NEJMoa1903076","article-title":"Nintedanib for systemic sclerosis-associated interstitial lung disease","volume":"380","author":"O Distler","year":"2019","journal-title":"N Engl J Med"},{"issue":"10","key":"pone.0283775.ref005","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1016\/S2213-2600(20)30318-0","article-title":"Denton CP; focuSSced investigators. Tocilizumab in systemic sclerosis: a randomised, double-blind, placebo-controlled, phase 3 trial","volume":"8","author":"D Khanna","year":"2020","journal-title":"Lancet Respir Med"},{"key":"pone.0283775.ref006","first-page":"43","article-title":"Emerging treatments for scleroderma\/systemic sclerosis","volume":"10","author":"JL Zhu","year":"2021","journal-title":"Fac Rev"},{"issue":"6","key":"pone.0283775.ref007","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1007\/s00125-017-4518-6","article-title":"Promises and pitfalls of electronic health record analysis","volume":"61","author":"R Farmer","year":"2018","journal-title":"Diabetologia"},{"issue":"6","key":"pone.0283775.ref008","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1097\/BOR.0000000000000323","article-title":"Interstitial lung disease in systemic sclerosis: progress in screening and early diagnosis","volume":"28","author":"\u00d8 Molberg","year":"2016","journal-title":"Curr Opin Rheumatol"},{"issue":"2","key":"pone.0283775.ref009","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1097\/PTS.0b013e3181dcae06","article-title":"Outpatient adverse drug events identified by screening electronic health records","volume":"6","author":"TK Gandhi","year":"2010","journal-title":"J Patient Saf"},{"issue":"1","key":"pone.0283775.ref010","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1186\/s13075-019-2092-7","article-title":"Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record","volume":"21","author":"L Jamian","year":"2019","journal-title":"Arthritis Res Ther"},{"key":"pone.0283775.ref011","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.compbiomed.2014.07.022","article-title":"Informatics can identify systemic sclerosis (SSc) patients at risk for scleroderma renal crisis","volume":"53","author":"D Redd","year":"2014","journal-title":"Comput Biol Med"},{"issue":"1","key":"pone.0283775.ref012","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1186\/s13075-020-02310-z","article-title":"Use of ICD-10 diagnosis codes to identify seropositive and seronegative rheumatoid arthritis when lab results are not available","volume":"22","author":"JR Curtis","year":"2020","journal-title":"Arthritis Res Ther"},{"key":"pone.0283775.ref013","unstructured":"RPDR\u2014Research Patient Data Registry information. 2022. 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