{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T01:48:57Z","timestamp":1792028937092,"version":"4.4.0"},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T00:00:00Z","timestamp":1708560000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T00:00:00Z","timestamp":1708560000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UM1CA221940"],"award-info":[{"award-number":["UM1CA221940"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UM1CA221940"],"award-info":[{"award-number":["UM1CA221940"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UM1CA221940"],"award-info":[{"award-number":["UM1CA221940"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UM1CA221940"],"award-info":[{"award-number":["UM1CA221940"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UM1CA221940"],"award-info":[{"award-number":["UM1CA221940"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Health Serv Res"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Efficiently identifying patients with human immunodeficiency virus (HIV) using administrative health care data (e.g., claims) can facilitate research on their quality of care and health outcomes. No prior study has validated the use of only ICD-10-CM HIV diagnosis codes to identify patients with HIV.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We validated HIV diagnosis codes among women enrolled in a large U.S. integrated health care system during 2010\u20132020. We examined HIV diagnosis code-based algorithms that varied by type, frequency, and timing of the codes in patients\u2019 claims data. We calculated the positive predictive values (PPVs) and 95% confidence intervals (CIs) of the algorithms using a medical record-confirmed diagnosis of HIV as the gold standard.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A total of 272 women with \u2265\u20091 HIV diagnosis code in the administrative claims data were identified and medical records were reviewed for all 272 women. The PPV of an algorithm classifying women as having HIV as of the first HIV diagnosis code during the observation period was 80.5% (95% CI: 75.4\u201384.8%), and it was 93.9% (95% CI: 90.0-96.3%) as of the second. Little additional increase in PPV was observed when a third code was required. The PPV of an algorithm based on ICD-10-CM-era codes was similar to one based on ICD-9-CM-era codes.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>If the accuracy measure of greatest interest is PPV, our findings suggest that use of \u2265\u20092 HIV diagnosis codes to identify patients with HIV may perform well. However, health care coding practices may vary across settings, which may impact generalizability of our results.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12913-024-10685-x","type":"journal-article","created":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T17:02:13Z","timestamp":1708621333000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan"],"prefix":"10.1186","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0481-6168","authenticated-orcid":false,"given":"Gaia","family":"Pocobelli","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Malia","family":"Oliver","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ladia","family":"Albertson-Junkans","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabrielle","family":"Gundersen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aruna","family":"Kamineni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,22]]},"reference":[{"issue":"11","key":"10685_CR1","doi-asserted-by":"publisher","first-page":"e28620","DOI":"10.2196\/28620","volume":"5","author":"SB May","year":"2021","unstructured":"May SB, Giordano TP, Gottlieb A. A phenotyping algorithm to identify people with HIV in Electronic Health Record Data (HIV-Phen): development and evaluation study. JMIR Form Res. 2021;5(11):e28620.","journal-title":"JMIR Form Res"},{"issue":"3\u201304","key":"10685_CR2","first-page":"84","volume":"60","author":"Y Liu","year":"2021","unstructured":"Liu Y, Siddiqi KA, Cook RL, Bian J, Squires PJ, Shenkman EA, et al. Optimizing identification of people living with HIV from Electronic Medical Records: computable phenotype development and validation. Methods Inf Med. 2021;60(3\u201304):84\u201394.","journal-title":"Methods Inf Med"},{"issue":"8","key":"10685_CR3","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1111\/hiv.12757","volume":"20","author":"JR Kramer","year":"2019","unstructured":"Kramer JR, Hartman C, White DL, Royse K, Richardson P, Thrift AP, et al. Validation of HIV-infected cohort identification using automated clinical data in the Department of Veterans affairs. HIV Med. 2019;20(8):567\u201370.","journal-title":"HIV Med"},{"issue":"2","key":"10685_CR4","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1093\/jamia\/ocx061","volume":"25","author":"DW Paul","year":"2018","unstructured":"Paul DW, Neely NB, Clement M, Riley I, Al-Hegelan M, Phelan M, et al. Development and validation of an electronic medical record (EMR)-based computed phenotype of HIV-1 infection. J Am Med Inf Assoc. 2018;25(2):150\u20137.","journal-title":"J Am Med Inf Assoc"},{"key":"10685_CR5","unstructured":"Leavy M, Swenson A. Chapter 2. Data Sources. In: Gliklich R, Leavy M, Dreyer N, editors. Tools and Technologies for Registry Interoperability, Registries for Evaluating Patient Outcomes: A User\u2019s Guide, 3rd Edition, Addendum 2 (Prepared by L&M Policy Research, LLC under Contract No 290-2014-00004-C) AHRQ Publication No 19(20)-EHC017-EF. Rockville, MD: Agency for Healthcare Research and Quality; 2019."},{"issue":"8 Suppl 2","key":"10685_CR6","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1097\/01.mlr.0000223670.00890.74","volume":"44","author":"SL Fultz","year":"2006","unstructured":"Fultz SL, Skanderson M, Mole LA, Gandhi N, Bryant K, Crystal S, et al. Development and verification of a virtual cohort using the National VA Health Information System. Med Care. 2006;44(8 Suppl 2):25\u201330.","journal-title":"Med Care"},{"key":"10685_CR7","unstructured":"Centers for Disease Control and Prevention\/National Center for Health Statistics. International Classification of Diseases, Tenth Revision, Clinical Modificiation (ICD-10-CM). Available from: http:\/\/www.cdc.gov\/nchs\/icd\/icd10cm.htm."},{"key":"10685_CR8","unstructured":"Centers for Disease Control and Prevention\/National Center for Health Statistics. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). Available from: https:\/\/www.cdc.gov\/nchs\/icd\/icd9cm.htm."},{"key":"10685_CR9","unstructured":"Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the Use of Antiretroviral Agents in Adults and Adolescents with HIV. Department of Health and Human Services. Available at https:\/\/clinicalinfo.hiv.gov\/en\/guidelines\/adult-and-adolescent-arv. Accessed (November 13, 2023)."},{"key":"10685_CR10","doi-asserted-by":"crossref","unstructured":"Beaber EF, Kamineni A, Burnett-Hartman AN, Hixon B, Kobrin SC, Li CI et al. Evaluating and improving Cancer screening process quality in a Multilevel Context: the PROSPR II Consortium Design and Research Agenda. Cancer epidemiology, biomarkers & prevention: a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2022;31(8):1521\u201331.","DOI":"10.1158\/1055-9965.EPI-22-0100"},{"issue":"2","key":"10685_CR11","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1214\/ss\/1009213286","volume":"16","author":"LD Brown","year":"2001","unstructured":"Brown LD, Cai T, DasGapta A. Interval estimation for a binomial proportion. Statist Sci. 2001;16(2):101\u201333.","journal-title":"Statist Sci"},{"issue":"2","key":"10685_CR12","doi-asserted-by":"publisher","first-page":"042","DOI":"10.1093\/ofid\/ofu042","volume":"1","author":"AC Davis","year":"2014","unstructured":"Davis AC, Watson G, Pourat N, Kominski GF, Roby DH. Disparities in CD4\u2009+\u2009T-Lymphocyte monitoring among human immunodeficiency virus-positive Medicaid beneficiaries: evidence of Differential Treatment at the point of Care. Open Forum Infect Dis. 2014;1(2):042.","journal-title":"Open Forum Infect Dis"},{"issue":"1","key":"10685_CR13","first-page":"3","volume":"49","author":"J Shepheard","year":"2020","unstructured":"Shepheard J. Clinical coding and the quality and integrity of health data. Health Inf Manag. 2020;49(1):3\u20134.","journal-title":"Health Inf Manag"},{"issue":"3","key":"10685_CR14","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/j.jclinepi.2011.09.002","volume":"65","author":"J Chubak","year":"2012","unstructured":"Chubak J, Pocobelli G, Weiss NS. Tradeoffs between accuracy measures for electronic health care data algorithms. J Clin Epidemiol. 2012;65(3):343\u20139. e2.","journal-title":"J Clin Epidemiol"},{"issue":"4","key":"10685_CR15","doi-asserted-by":"publisher","first-page":"1392","DOI":"10.1093\/ije\/dyaa090","volume":"49","author":"MP Fox","year":"2020","unstructured":"Fox MP, Lash TL, Bodnar LM. Common misconceptions about validation studies. Int J Epidemiol. 2020;49(4):1392\u20136.","journal-title":"Int J Epidemiol"}],"container-title":["BMC Health Services Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12913-024-10685-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12913-024-10685-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12913-024-10685-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T17:07:12Z","timestamp":1708621632000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmchealthservres.biomedcentral.com\/articles\/10.1186\/s12913-024-10685-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,22]]},"references-count":15,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["10685"],"URL":"https:\/\/doi.org\/10.1186\/s12913-024-10685-x","relation":{},"ISSN":["1472-6963"],"issn-type":[{"value":"1472-6963","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,22]]},"assertion":[{"value":"3 October 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 February 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was approved by the Kaiser Permanente Washington (KPWA) institutional review board (IRBNet number 1751301) and was in accordance with the Belmont Report and the Common Rule. The KPWA institutional review board issued a waiver of informed consent to collect patient health record data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"GP has worked on grants awarded to Kaiser Foundation Health Plan of Washington that were funded by Amgen (to evaluate the accuracy of using electronic health record data to identify individuals with reduced ejection fraction heart failure) and Jazz Pharmaceuticals (to evaluate motor vehicle accident risk in relation to obstructive sleep apnea). No other authors report conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"234"}}