{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T18:32:36Z","timestamp":1776882756175,"version":"3.51.2"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T00:00:00Z","timestamp":1676937600000},"content-version":"vor","delay-in-days":54,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Center for Advancing Translational Sciences of the National Institutes of Health","award":["UL1TR002553"],"award-info":[{"award-number":["UL1TR002553"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,29]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>Outpatient parenteral antimicrobial therapy (OPAT) is associated with high hospital readmission rates. A 30\u2005day unplanned readmission risk prediction model for OPAT patients has been developed in the UK. Given significant differences in patient mix and methods of OPAT delivery, we explored the model for its utility in Duke University Health System (DUHS) patients receiving OPAT.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We analysed OPAT episodes of adult patients from two hospitals between 1 July 2019 and 1 February 2020. The discriminative ability of the model to predict 30\u2005day unplanned all-cause and OPAT-related admission was examined. An updated model was created by logistic regression with the UK risk factors and additional risk factors, OPAT delivery in a skilled nursing facility, vancomycin use and IV drug abuse.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Compared with patients of the UK cohort, our study patients were of higher acuity, treated for more invasive infections, and received OPAT through different modes. The 30\u2005day unplanned readmission rate in our cohort was 20% (94\/470), with 59.5% (56\/94) of those being OPAT-related. The original model was unable to discriminate for all-cause readmission with a C-statistic of 0.52 (95% CI 0.46\u20130.59) and for OPAT-related readmission with a C-statistic of 0.55 (95% CI 0.47\u20130.64). The updated model with additional risk factors did not have improved performance, with a C-statistic of 0.55 (95% CI 0.49\u20130.62).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The UK 30\u2005day unplanned hospital readmission model performed poorly in predicting readmission for the OPAT population at a US academic medical centre.<\/jats:p><\/jats:sec>","DOI":"10.1093\/jacamr\/dlad019","type":"journal-article","created":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T19:41:11Z","timestamp":1677008471000},"source":"Crossref","is-referenced-by-count":7,"title":["Utility of a risk assessment model in predicting 30\u2005day unplanned hospital readmission in adult patients receiving outpatient parenteral antimicrobial therapy"],"prefix":"10.1093","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6553-8704","authenticated-orcid":false,"given":"Ethan","family":"Brenneman","sequence":"first","affiliation":[{"name":"Department of Pharmacy, Duke 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