{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T15:08:04Z","timestamp":1745420884806},"reference-count":13,"publisher":"Georg Thieme Verlag KG","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n          Background\u2003With increasing use of real world data in observational health care research, data quality assessment of these data is equally gaining in importance. Electronic health record (EHR) or claims datasets can differ significantly in the spectrum of care covered by the data.<\/jats:p><jats:p>\n          Objective\u2003In our study, we link provider specialty with diagnoses (encoded in International Classification of Diseases) with a motivation to characterize data completeness.<\/jats:p><jats:p>\n          Methods\u2003We develop a set of measures that determine diagnostic span of a specialty (how many distinct diagnosis codes are generated by a specialty) and specialty span of a diagnosis (how many specialties diagnose a given condition). We also analyze ranked lists for both measures. As use case, we apply these measures to outpatient Medicare claims data from 2016 (3.5 billion diagnosis\u2013specialty pairs). We analyze 82 distinct specialties present in Medicare claims (using Medicare list of specialties derived from level III Healthcare Provider Taxonomy Codes).<\/jats:p><jats:p>\n          Results\u2003A typical specialty diagnoses on average 4,046 distinct diagnosis codes. It can range from 33 codes for medical toxicology to 25,475 codes for internal medicine. Specialties with large visit volume tend to have large diagnostic span. Median specialty span of a diagnosis code is 8 specialties with a range from 1 to 82 specialties. In total, 13.5% of all observed diagnoses are generated exclusively by a single specialty. Quantitative cumulative rankings reveal that some diagnosis codes can be dominated by few specialties. Using such diagnoses in cohort or outcome definitions may thus be vulnerable to incomplete specialty coverage of a given dataset.<\/jats:p><jats:p>\n          Conclusion\u2003We propose specialty fingerprinting as a method to assess data completeness component of data quality. Datasets covering a full spectrum of care can be used to generate reference benchmark data that can quantify relative importance of a specialty in constructing diagnostic history elements of computable phenotype definitions.<\/jats:p>","DOI":"10.1055\/s-0041-1732404","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T22:30:24Z","timestamp":1628116224000},"page":"729-736","source":"Crossref","is-referenced-by-count":3,"title":["Linking Provider Specialty and Outpatient Diagnoses in Medicare Claims Data: Data Quality Implications"],"prefix":"10.1055","volume":"12","author":[{"given":"Vojtech","family":"Huser","sequence":"additional","affiliation":[{"name":"Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nick D.","family":"Williams","sequence":"additional","affiliation":[{"name":"Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Craig S.","family":"Mayer","sequence":"additional","affiliation":[{"name":"Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"194","published-online":{"date-parts":[[2021,8,4]]},"reference":[{"issue":"12","key":"ref1","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1080\/03007995.2018.1524751","article-title":"Meta-analyses using real-world data to generate clinical and epidemiological evidence: a systematic literature review of existing recommendations","volume":"34","author":"J-B Briere","year":"2018","journal-title":"Curr Med Res Opin"},{"issue":"06","key":"ref2","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1080\/13696998.2019.1588737","article-title":"Cost-effectiveness analyses using real-world data: an overview of the literature","volume":"22","author":"K Bowrin","year":"2019","journal-title":"J Med Econ"},{"issue":"01","key":"ref3","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1002\/cpt.1486","article-title":"What does it take to transform real-world data into real-world evidence?","volume":"106","author":"A Ramamoorthy","year":"2019","journal-title":"Clin Pharmacol Ther"},{"issue":"03","key":"ref5","doi-asserted-by":"crossref","first-page":"621","DOI":"10.4338\/ACI-2014-04-RA-0036","article-title":"JADE: a tool for medical researchers to explore adverse drug events using health claims data","volume":"5","author":"D Edlinger","year":"2014","journal-title":"Appl Clin Inform"},{"issue":"05","key":"ref6","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1055\/s-0040-1718756","article-title":"A method to improve availability and quality of patient race data in an electronic health record system","volume":"11","author":"M M Cusick","year":"2020","journal-title":"Appl Clin Inform"},{"issue":"02","key":"ref7","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1055\/s-0039-1681054","article-title":"Impact of electronic versus paper-based recording before EHR implementation on health care professionals' perceptions of EHR use, data quality, and data reuse","volume":"10","author":"E Joukes","year":"2019","journal-title":"Appl Clin Inform"},{"key":"ref9","first-page":"489","article-title":"A visual interface designed for novice users to find research patient cohorts in a large biomedical database","volume":"2003","author":"S N Murphy","year":"2003","journal-title":"AMIA Annu Symp Proc"},{"issue":"08","key":"ref10","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1007\/s11606-012-2033-5","article-title":"Use of an electronic problem list by primary care providers and specialists","volume":"27","author":"A Wright","year":"2012","journal-title":"J Gen Intern Med"},{"issue":"03","key":"ref11","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1055\/s-0038-1666994","article-title":"Identifying asthma exacerbation-related emergency department visit using electronic medical record and claims data","volume":"9","author":"A S Sundaresan","year":"2018","journal-title":"Appl Clin Inform"},{"issue":"06","key":"ref14","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1136\/amiajnl-2011-000121","article-title":"A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record","volume":"18","author":"A Wright","year":"2011","journal-title":"J Am Med Inform Assoc"},{"issue":"01","key":"ref16","first-page":"1244","article-title":"A harmonized data quality assessment terminology and framework for the secondary use of electronic health record data","volume":"4","author":"M G Kahn","year":"2016","journal-title":"EGEMS (Wash DC)"},{"issue":"04","key":"ref17","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1055\/s-0040-1715567","article-title":"A rule-based data quality assessment system for electronic health record data","volume":"11","author":"Z Wang","year":"2020","journal-title":"Appl Clin Inform"},{"key":"ref19","first-page":"628","article-title":"Methods for examining data quality in healthcare integrated data repositories","volume":"23","author":"V Huser","year":"2018","journal-title":"Pac Symp Biocomput"}],"container-title":["Applied Clinical Informatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/s-0041-1732404.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T22:31:14Z","timestamp":1628116274000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/s-0041-1732404"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":13,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2021,8,4]]},"published-print":{"date-parts":[[2021,8]]}},"URL":"https:\/\/doi.org\/10.1055\/s-0041-1732404","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["1869-0327"],"issn-type":[{"value":"1869-0327","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8]]}}}