{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T08:48:40Z","timestamp":1769244520221,"version":"3.49.0"},"reference-count":40,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T00:00:00Z","timestamp":1628812800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100000850","name":"National Heart and Lung Institute","doi-asserted-by":"publisher","award":["K01 HL 141538"],"award-info":[{"award-number":["K01 HL 141538"]}],"id":[{"id":"10.13039\/501100000850","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000850","name":"National Heart and Lung Institute","doi-asserted-by":"publisher","award":["R01 HL 117918"],"award-info":[{"award-number":["R01 HL 117918"]}],"id":[{"id":"10.13039\/501100000850","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Health Services Research"],"published-print":{"date-parts":[[2022,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>Medication nonadherence is linked to worsened clinical outcomes and increased costs. Existing system\u2010level adherence interventions rely on insurer claims for patient identification and outcome measurement, yet suffer from incomplete capture and lags in data acquisition. Data from pharmacies regarding prescription filling, captured in retail dispensing, may be more efficient.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Sources<\/jats:title><jats:p>Pharmacy fill and insurer claims data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Design<\/jats:title><jats:p>We compared adherence measured using pharmacy fill data to adherence using insurer claims data, expressed as proportion of days covered (PDC) over 12\u2009months. Agreement was evaluated using correlation\/validation metrics. We also explored the relationship between adherence in both sources and disease control using prediction modeling.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Extraction Methods<\/jats:title><jats:p>Large pragmatic trial of cardiometabolic disease in an integrated delivery network.<\/jats:p><\/jats:sec><jats:sec><jats:title>Principal Findings<\/jats:title><jats:p>Among 1113 patients, adherence was higher in pharmacy fill (mean\u00a0=\u00a050.0%) versus claims data (mean\u00a0=\u00a047.4%), although they had moderately high correlation (R\u00a0=\u00a00.57, 95% CI: 0.53\u20130.61) with most patients (86.9%) being similarly classified as adherent or nonadherent. Sensitivity and specificity of pharmacy fill versus claims data were high (0.89, 95% CI: 0.86\u20130.91 and 0.80, 95% CI: 0.75\u20130.85). Pharmacy fill\u2010based PDC predicted better disease control slightly more than claims\u2010based PDC, although the difference was nonsignificant.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Pharmacy fill data may be an alternative to insurer claims for adherence measurement.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1475-6773.13714","type":"journal-article","created":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T10:38:59Z","timestamp":1628851139000},"page":"524-536","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Comparison of measures of medication adherence from pharmacy dispensing and insurer claims data"],"prefix":"10.1111","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8253-1598","authenticated-orcid":false,"given":"Constance P.","family":"Fontanet","sequence":"first","affiliation":[{"name":"Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine Brigham and Women's Hospital and Harvard Medical School  Boston Massachusetts USA"},{"name":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine Brigham and Women's Hospital and Harvard Medical School  Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niteesh K.","family":"Choudhry","sequence":"additional","affiliation":[{"name":"Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine Brigham and Women's Hospital and Harvard Medical School  Boston Massachusetts USA"},{"name":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine Brigham and Women's Hospital and Harvard Medical School  Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Isaac","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine Atrius Health  Newton Massachusetts 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A.","family":"Jackevicius","sequence":"additional","affiliation":[{"name":"Pharmacy Practice and Administration Department Western University of Health Sciences  Pomona California USA"},{"name":"Department of Cardiology VA Greater Los Angeles Healthcare System  Los Angeles California USA"},{"name":"Institute for Health Policy, Management and Evaluation University of Toronto  Toronto Ontario Canada"},{"name":"ICES University Health Network  Toronto Ontario Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael A.","family":"Fischer","sequence":"additional","affiliation":[{"name":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine Brigham and Women's Hospital and Harvard Medical School  Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel H.","family":"Solomon","sequence":"additional","affiliation":[{"name":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine 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