{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:03:58Z","timestamp":1782846238105,"version":"3.54.5"},"reference-count":40,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Preventing adverse drug reactions requires accurate monitoring of drug exposure throughout patient care. Conventional metrics, measured at admission or discharge, fail to capture the dynamic and cumulative nature of drug burden during hospitalization. Improving exposure assessment is essential to support clinical decision-making and medication safety. Clinical data warehouses (CDWs), which integrate detailed drug administration records, enable the retrospective reuse of hospital data to develop more granular and dynamic measures of in-hospital drug exposure.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This exploratory proof-of-concept study aimed to introduce 2 cumulative drug exposure metrics computed from CDW: cumulative drug exposure (CDE) and cumulative drug exposure density (CDED). The study also aimed to compare these metrics with conventional metrics, primarily as a methodological development for characterizing prescribing determinants in hospitalized patients.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We conducted a retrospective study using the eHOP CDW at Rennes University Hospital. Adults hospitalized for hematological malignancies were included. Four prescribing determinants were analyzed: polypharmacy (PP), hyperpolypharmacy (HPP), drug-drug interactions (DDIs), and potentially inappropriate medications (PIMs). CDE quantified the number of days each determinant was present, while CDED normalized this value to hospital length of stay. Analyses combined descriptive statistics, Spearman correlations, and factorial analysis of mixed data (FAMD).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Mean CDE values were 10.5 days for PP, 5.7 for HPP, 64.7 for DDIs, and 19.0 for PIMs (\u226565 years). CDED values ranged from 0.3 to 3.2. Conventional metrics at admission were weakly correlated with cumulative exposure measures (eg, DDIs:\n r<\/jats:italic>\n s<\/jats:sub>\n =0.04,\n P=.<\/jats:italic>\n 752; PP:\n r<\/jats:italic>\n s<\/jats:sub>\n =\u20130.04,\n P=<\/jats:italic>\n .757; HPP:\n r<\/jats:italic>\n s<\/jats:sub>\n =0.11,\n P=<\/jats:italic>\n .364). Stronger, significant correlations emerged at discharge (CDE DDIs:\n r<\/jats:italic>\n s<\/jats:sub>\n =0.44, CDED:\n r<\/jats:italic>\n s<\/jats:sub>\n =0.46; both\n P<<\/jats:italic>\n .001). PIMs showed strong significant correlations at both time points. FAMD highlighted that cumulative metrics contributed independently to the principal components, capturing dynamics of drug exposure not reflected by conventional indicators.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n CDE and CDED, derived from real-time CDW data, offer reproducible and scalable alternatives to conventional metrics for characterizing drug exposure in patients hospitalized for severe conditions. They provide a more accurate characterization of drug burden and hold promise for pharmacoepidemiological research and clinical decision support.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/76961","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T03:15:08Z","timestamp":1764558908000},"page":"e76961-e76961","source":"Crossref","is-referenced-by-count":0,"title":["Methodological Development and Assessing Prescribing Determinants Through Cumulative Drug Exposure in Hospitalized Patients: Proof-of-Concept Retrospective Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9092-4298","authenticated-orcid":false,"given":"Mathilde","family":"Bories","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3637-6558","authenticated-orcid":false,"given":"Guillaume","family":"Bouzill\u00e9","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6943-3937","authenticated-orcid":false,"given":"Marc","family":"Cuggia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4483-0957","authenticated-orcid":false,"given":"Pascal","family":"Le Corre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1631-566X","authenticated-orcid":false,"given":"Aur\u00e9lie","family":"Bannay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,4,16]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1001\/jama.1995.03530010043033","article-title":"Incidence of adverse drug events and potential adverse drug events","volume":"274","author":"Bates","journal-title":"JAMA"},{"issue":"7456","key":"R2","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1136\/bmj.329.7456.15","article-title":"Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients","volume":"329","author":"Pirmohamed","journal-title":"BMJ"},{"issue":"12","key":"R3","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.1001\/archinte.163.12.1409","article-title":"Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review","volume":"163","author":"Kaushal","journal-title":"Arch Intern Med"},{"issue":"6","key":"R4","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1111\/bcp.12732","article-title":"A systematic review of the emerging de\ufb01nition of \u201cdeprescribing\u201d with network analysis: implications for future research and clinical practice","volume":"80","author":"Reeve","journal-title":"Br J Clin Pharmacol"},{"issue":"10","key":"R5","doi-asserted-by":"publisher","DOI":"10.2196\/40511","article-title":"Appropriateness of alerts and physicians\u2019 responses with a medication-related clinical decision support system: retrospective observational study","volume":"10","author":"Park","journal-title":"JMIR Med Inform"},{"key":"R6","unstructured":"Lee TA Pickard AS . 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