An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients
An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients
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DOI：
10.1136/bmjqs-2017-006975
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发表时间：
2018-03-01
影响因子：
5.4
通讯作者：
Singh, Hardeep
中科院分区：
文献类型：
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作者：
Bhise, Viraj;Sittig, Dean F.;Singh, Hardeep
识别可预防不良事件的方法通常具有低产量和低效率。我们改进了医疗保健改善研究所的全球触发工具（GTT）应用程序的方法，并利用电子健康记录（EHR）数据来改善可预防不良事件的检测，包括诊断错误。方法我们查询了一个大型卫生系统的EHR数据存储库，以确定与护理升级相关的“索引住院”2010年3月至2015年8月期间（定义为入院后15天内转入重症监护室（ICU）或启动快速反应团队（RRT））。为了丰富记录审查样本中的意外事件，我们使用EHR临床数据修改GTT算法，并将符合条件的患者限制为基于年龄较小和存在最小共病条件的护理升级风险较低的患者。我们修改了GTT审查方法，两名医生独立审查合格的“电子触发器”的积极记录，以确定可预防的诊断和护理管理events.Results的88 428住院，887与护理升级（712 ICU转移和175 RRT），其中92标记为阳性和审查。在41例病例中检测到可排除的不良事件，触发阳性预测值为44.6%（评审员一致性79.35%; Cohen's kappa 0.573）。我们确定了7例（7.6%）诊断错误和34例（37.0%）护理管理相关事件：24例（26.1%）药物不良事件、4例（4.3%）患者福尔斯、4例（4.3%）手术相关并发症和2例（2.2%）医院相关感染。在大多数事件（73.1%），有可能暂时harm.Conclusion使用EHR数据为基础的触发器和修改后的审查过程，以有效地识别住院患者可预防的不良事件，包括诊断错误的方法。这种电子触发器可以帮助克服现有方法的局限性，以检测住院患者中可预防的伤害。
Background Methods to identify preventable adverse events typically have low yield and efficiency. We refined the methods of Institute of Healthcare Improvement's Global Trigger Tool (GTT) application and leveraged electronic health record (EHR) data to improve detection of preventable adverse events, including diagnostic errors.Methods We queried the EHR data repository of a large health system to identify an 'index hospitalization' associated with care escalation (defined as transfer to the intensive care unit (ICU) or initiation of rapid response team (RRT) within 15 days of admission) between March 2010 and August 2015. To enrich the record review sample with unexpected events, we used EHR clinical data to modify the GTT algorithm and limited eligible patients to those at lower risk for care escalation based on younger age and presence of minimal comorbid conditions. We modified the GTT review methodology; two physicians independently reviewed eligible 'e-trigger' positive records to identify preventable diagnostic and care management events.Results Of 88 428 hospitalisations, 887 were associated with care escalation (712 ICU transfers and 175 RRTs), of which 92 were flagged as trigger-positive and reviewed. Preventable adverse events were detected in 41 cases, yielding a trigger positive predictive value of 44.6% (reviewer agreement 79.35%; Cohen's kappa 0.573). We identified 7 (7.6%) diagnostic errors and 34 (37.0%) care management-related events: 24 (26.1%) adverse drug events, 4 (4.3%) patient falls, 4 (4.3%) procedure-related complications and 2 (2.2%) hospital-associated infections. In most events (73.1%), there was potential for temporary harm.Conclusion We developed an approach using an EHR data-based trigger and modified review process to efficiently identify hospitalised patients with preventable adverse events, including diagnostic errors. Such e-triggers can help overcome limitations of currently available methods to detect preventable harm in hospitalised patients.