{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T01:29:27Z","timestamp":1762997367520},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"e1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Background and objective: There is an increasing desire to share de-identified electronic health records (EHRs) for secondary uses, but there are concerns that clinical terms can be exploited to compromise patient identities. Anonymization algorithms mitigate such threats while enabling novel discoveries, but their evaluation has been limited to single institutions. Here, we study how an existing clinical profile anonymization fares at multiple medical centers.<\/jats:p>\n               <jats:p>Methods: We apply a state-of-the-art k -anonymization algorithm, with k set to the standard value 5, to the International Classification of Disease, ninth edition codes for patients in a hypothyroidism association study at three medical centers: Marshfield Clinic, Northwestern University, and Vanderbilt University. We assess utility when anonymizing at three population levels: all patients in 1) the EHR system; 2) the biorepository; and 3) a hypothyroidism study. We evaluate utility using 1) changes to the number included in the dataset, 2) number of codes included, and 3) regions generalization and suppression were required.<\/jats:p>\n               <jats:p>Results: Our findings yield several notable results. First, we show that anonymizing in the context of the entire EHR yields a significantly greater quantity of data by reducing the amount of generalized regions from \u223c15% to \u223c0.5%. Second, \u223c70% of codes that needed generalization only generalized two or three codes in the largest anonymization.<\/jats:p>\n               <jats:p>Conclusions: Sharing large volumes of clinical data in support of phenome-wide association studies is possible while safeguarding privacy to the underlying individuals.<\/jats:p>","DOI":"10.1093\/jamia\/ocv154","type":"journal-article","created":{"date-parts":[[2015,11,14]],"date-time":"2015-11-14T02:39:24Z","timestamp":1447468764000},"page":"e131-e137","source":"Crossref","is-referenced-by-count":11,"title":["A multi-institution evaluation of clinical profile anonymization"],"prefix":"10.1093","volume":"23","author":[{"given":"Raymond","family":"Heatherly","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA"}]},{"given":"Luke V","family":"Rasmussen","sequence":"additional","affiliation":[{"name":"Feinberg School of Medicine, Northwestern University, Chicago, IL, USA"}]},{"given":"Peggy L","family":"Peissig","sequence":"additional","affiliation":[{"name":"Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI, USA"}]},{"given":"Jennifer A","family":"Pacheco","sequence":"additional","affiliation":[{"name":"Feinberg School of Medicine, Northwestern University, Chicago, IL, USA"}]},{"given":"Paul","family":"Harris","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA"},{"name":"Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA"}]},{"given":"Joshua C","family":"Denny","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA"},{"name":"Department of Medicine, Vanderbilt University, Nashville, TN, USA"}]},{"given":"Bradley A","family":"Malin","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA"},{"name":"Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, USA"}]}],"member":"286","published-online":{"date-parts":[[2015,11,13]]},"reference":[{"key":"2020110612431661900_ocv154-B1","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1001\/jama.2013.393","article-title":"The inevitable application of big data to health care","volume":"309","author":"Murdoch","year":"2013","journal-title":"JAMA."},{"key":"2020110612431661900_ocv154-B2","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1377\/hlthaff.2014.0041","article-title":"Big data in health care: using analytics to identify and manage high-risk and high-cost patients","volume":"33","author":"Bates","year":"2014","journal-title":"Health Aff."},{"key":"2020110612431661900_ocv154-B3","first-page":"e226","article-title":"Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory","volume":"2","author":"Richesson","year":"2013","journal-title":"JAMIA."},{"key":"2020110612431661900_ocv154-B4","doi-asserted-by":"crossref","first-page":"e206","DOI":"10.1136\/amiajnl-2013-002428","article-title":"Electronic health records-driven phenotyping: challenges, recent advances, and perspectives","volume":"2","author":"Pathak","year":"2013","journal-title":"J Am Med Inform."},{"key":"2020110612431661900_ocv154-B5","first-page":"576","article-title":"PCORnet: turning a dream into reality","volume":"21(4)","author":"Collins","year":"2014","journal-title":"JAMIA."},{"key":"2020110612431661900_ocv154-B6","volume-title":"NIH genomic data sharing policy","author":"National Institutes of Health"},{"key":"2020110612431661900_ocv154-B7","volume-title":"Final NIH Statement on Sharing Research Data","author":"National Institutes of Health"},{"key":"2020110612431661900_ocv154-B8","volume-title":"Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies (GWAS)","author":"National Institutes of Health"},{"key":"2020110612431661900_ocv154-B9","volume-title":"Standards for privacy of individually identifiable health information","author":"U.S. Department of Health and Human Services"},{"key":"2020110612431661900_ocv154-B10","doi-asserted-by":"crossref","first-page":"e28071","DOI":"10.1371\/journal.pone.0028071","article-title":"A systematic review of re-identification attacks on health data","volume":"6","author":"El Emam","year":"2011","journal-title":"PLoS One."},{"key":"2020110612431661900_ocv154-B11","first-page":"322","article-title":"The disclosure of diagnosis codes can breach research participants\u2019 privacy","volume":"17","author":"Loukides","year":"2010","journal-title":"JAMIA."},{"key":"2020110612431661900_ocv154-B12","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.jbi.2014.06.002","article-title":"Publishing data from electronic health records while preserving privacy a survey of algorithms","volume":"50","author":"Gkoulalas-Divanis","year":"2014","journal-title":"J Biomed Inform."},{"key":"2020110612431661900_ocv154-B13","doi-asserted-by":"crossref","first-page":"7898","DOI":"10.1073\/pnas.0911686107","article-title":"Anonymization of electronic medical records for validating genome-wide association studies","volume":"107","author":"Loukides","year":"2010","journal-title":"Proc Natl Acad Sci USA."},{"key":"2020110612431661900_ocv154-B14","doi-asserted-by":"crossref","first-page":"e53875","DOI":"10.1371\/journal.pone.0053875","article-title":"Enabling genomic-phenomic association discovery without sacrificing anonymity","volume":"8","author":"Heatherly","year":"2013","journal-title":"PLoS One."},{"key":"2020110612431661900_ocv154-B15","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.jbi.2014.07.005","article-title":"Size matters: how population size influences genotype-phenotype association studies in anonymized 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Ther."},{"key":"2020110612431661900_ocv154-B29","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1016\/j.ajhg.2011.09.008","article-title":"Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome-and phenome-wide studies","volume":"89","author":"Denny","year":"2011","journal-title":"Am J Hum Genet."},{"key":"2020110612431661900_ocv154-B30","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1142\/S0218488502001648","article-title":"k\n              -anonymity: a model for protecting privacy","volume":"10","author":"Sweeney","year":"2002","journal-title":"Int J Uncertain, Fuzziness, Knowledge-based Sys."},{"issue":"12","key":"2020110612431661900_ocv154-B31","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1038\/nbt.2749","article-title":"Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study 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