{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:36:50Z","timestamp":1740202610416,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>We explored how drug switching impacts adherence measures for common chronic oral medications. Switching between ingredients with the same indication was detected within a 30-day grace period. The proportion of days covered (PDC) and adherent status (cutoff 0.8) for each ingredient was calculated and compared between different censoring approaches: censoring drug switching (PDCswitch), censoring the end of dispensing (PDCend), and fixed 365-day period (PDC365). Overall, 854,380 (15.9%) patients in the Optum ClinFormatics (Optum) and 150,785 (22.0%) patients in the MarketScan Multi-state Medicaid (MDCD) had at least one switch within one year. Compared with PDC365 in Optum, PDCswitch means were higher: 0.85 vs. 0.41 for antihypertensive, 0.82 vs. 0.46 for antihyperglycemics, and 0.84 vs. 0.33 for antihyerlipidemia. Further, the percentages of adherent patients were higher: 95.8% vs. 17.9% for antihypertensive, 85.5% vs. 18.9% for antihyperglycemics, and 72.1% vs. 5.3% for antihyerlipidemia. Significant and modest changes were observed between PDCswitch and PDCend.<\/jats:p>","DOI":"10.3233\/978-1-61499-830-3-1200","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:13:02Z","timestamp":1740157982000},"source":"Crossref","is-referenced-by-count":0,"title":["The Impact of Censoring Drug Switching in Medication Adherence Measures of Chronic Single Ingredient Oral Drugs"],"prefix":"10.3233","author":[{"family":"Zhu Vivienne J.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Overhage J. Marc","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ma Qianli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ryan Patrick B.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2017: Precision Healthcare through Informatics"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:53:50Z","timestamp":1740160430000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-829-7&spage=1200&doi=10.3233\/978-1-61499-830-3-1200"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-830-3-1200","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}