Effect of digital tools to promote hospital quality and safety on adverse events after discharge

Author:

Vasudevan Anant12ORCID,Plombon Savanna13,Piniella Nicholas1,Garber Alison1,Malik Maria1,O’Fallon Erin12,Goyal Abhishek12,Gershanik Esteban12,Kumar Vivek12,Fiskio Julie3,Yoon Cathy1,Lipsitz Stuart R12,Schnipper Jeffrey L12,Dalal Anuj K12ORCID

Affiliation:

1. Division of General Internal Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, United States

2. Harvard Medical School, Boston, MA 02115, United States

3. Mass General Brigham, Boston, MA 02145, United States

Abstract

Abstract Objectives 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. Materials and Methods 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. Results 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 = .08). For post-implementation patients with an AE, aIRR for duration of injury (>1 week) was significantly lower for dashboard plus discharge checklist compared to dashboard participants (0 [0,0.53], P < .01). In multivariable models, certain patient-reported NWS were associated with AEs (3.76 [1.89,7.82], P < .01). Discussion 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. Conclusion Interventions designed to prompt patients to report NWS may facilitate earlier detection of AEs after discharge. ClinicalTrials.gov NCT05232656

Funder

CRICO

Publisher

Oxford University Press (OUP)

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