{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T11:58:17Z","timestamp":1778068697996,"version":"3.51.4"},"reference-count":55,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T00:00:00Z","timestamp":1721088000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"CRICO"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>Post-discharge adverse events (AEs) are common and heralded by new and worsening symptoms (NWS). We evaluated the effect of electronic health record (EHR)-integrated digital tools designed to promote quality and safety in hospitalized patients on NWS and AEs after discharge.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>Adult general medicine patients at a community hospital were enrolled. We implemented a dashboard which clinicians used to assess safety risks during interdisciplinary rounds. Post-implementation patients were randomized to complete a discharge checklist whose responses were incorporated into the dashboard. Outcomes were assessed using EHR review and 30-day call data adjudicated by 2 clinicians and analyzed using Poisson regression. We conducted comparisons of each exposure on post-discharge outcomes and used selected variables and NWS as independent predictors to model post-discharge AEs using multivariable logistic regression.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>A total of 260 patients (122 pre, 71 post [dashboard], 67 post [dashboard plus discharge checklist]) enrolled. The adjusted incidence rate ratios (aIRR) for NWS and AEs were unchanged in the post- compared to pre-implementation period. For patient-reported NWS, aIRR was non-significantly higher for dashboard plus discharge checklist compared to dashboard participants (1.23 [0.97,1.56], P\u2009=\u2009.08). For post-implementation patients with an AE, aIRR for duration of injury (&amp;gt;1 week) was significantly lower for dashboard plus discharge checklist compared to dashboard participants (0 [0,0.53], P\u2009&amp;lt;\u2009.01). In multivariable models, certain patient-reported NWS were associated with AEs (3.76 [1.89,7.82], P\u2009&amp;lt;\u2009.01).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>While significant reductions in post-discharge AEs were not observed, checklist participants experiencing a post-discharge AE were more likely to report NWS and had a shorter duration of injury.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Interventions designed to prompt patients to report NWS may facilitate earlier detection of AEs after discharge.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>ClinicalTrials.gov<\/jats:title>\n                  <jats:p>NCT05232656<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocae176","type":"journal-article","created":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T22:02:34Z","timestamp":1721167354000},"page":"2304-2314","source":"Crossref","is-referenced-by-count":5,"title":["Effect of digital tools to promote hospital quality and safety on adverse events after discharge"],"prefix":"10.1093","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9894-8576","authenticated-orcid":false,"given":"Anant","family":"Vasudevan","sequence":"first","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, United States"},{"name":"Harvard Medical School, Boston, MA 02115, United States"}]},{"given":"Savanna","family":"Plombon","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, United States"},{"name":"Mass General Brigham, Boston, MA 02145, United States"}]},{"given":"Nicholas","family":"Piniella","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, United States"}]},{"given":"Alison","family":"Garber","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, United States"}]},{"given":"Maria","family":"Malik","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, United States"}]},{"given":"Erin","family":"O\u2019Fallon","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, United States"},{"name":"Harvard Medical School, Boston, MA 02115, United 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