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

IF 4.7 2区医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of the American Medical Informatics Association Pub Date : 2024-10-01 DOI:10.1093/jamia/ocae176

Anant Vasudevan, Savanna Plombon, Nicholas Piniella, Alison Garber, Maria Malik, Erin O'Fallon, Abhishek Goyal, Esteban Gershanik, Vivek Kumar, Julie Fiskio, Cathy Yoon, Stuart R Lipsitz, Jeffrey L Schnipper, Anuj K Dalal

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引用次数: 0

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.

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促进医院质量与安全的数字化工具对出院后不良事件的影响。

目的：出院后不良事件（AEs）很常见，并以新症状和恶化症状（NWS）为先兆。我们评估了旨在提高住院患者质量和安全的电子健康记录（EHR）集成数字工具对出院后新症状和不良事件的影响：研究对象为一家社区医院的成人全科患者。我们实施了一个仪表板，临床医生在跨学科查房时用它来评估安全风险。实施后，患者被随机分配填写出院核对表，并将其回复纳入仪表板。结果通过电子病历审查和 30 天呼叫数据进行评估，由两名临床医生裁定，并使用泊松回归进行分析。我们比较了每种暴露对出院后结果的影响，并将选定变量和 NWS 作为独立预测因子，使用多变量逻辑回归对出院后 AEs 进行建模：共有 260 名患者（122 名出院前、71 名出院后[仪表板]、67 名出院后[仪表板加出院检查单]）参加了研究。与实施前相比，实施后 NWS 和 AE 的调整后发病率比 (aIRR) 保持不变。就患者报告的 NWS 而言，与仪表板参与者相比，仪表板加出院核对表参与者的 aIRR 较高，但无显著性差异（1.23 [0.97,1.56]，P = .08）。对于实施后出现 AE 的患者，与仪表板参与者相比，仪表板加出院核对表患者的损伤持续时间（>1 周）的 aIRR 显著降低（0 [0,0.53]，P 讨论）：虽然没有观察到出院后 AE 的明显减少，但出院后发生 AE 的核对表参与者更有可能报告 NWS，且受伤持续时间更短：结论：旨在促使患者报告 NWS 的干预措施可能有助于更早地发现出院后 AE：NCT05232656。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of the American Medical Informatics Association 医学-计算机：跨学科应用

CiteScore

14.50

自引率

7.80%

发文量

230

审稿时长

3-8 weeks

期刊介绍： JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.