An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients

被引:36
作者
Bhise, Viraj [1 ,2 ]
Sittig, Dean F. [3 ]
Vaghani, Viralkumar [1 ,2 ]
Wei, Li [1 ,2 ]
Baldwin, Jessica [1 ,2 ]
Singh, Hardeep [1 ,2 ]
机构
[1] Michael E DeBakey VA Med Ctr, Ctr Innovat Qual Effectiveness & Safety IQuESt, Houston, TX USA
[2] Baylor Coll Med, Dept Med, 2002 Holcombe Blvd,152, Houston, TX 77030 USA
[3] Univ Texas Hlth Sci Ctr Houston, Sch Biomed Informat, Houston, TX 77030 USA
基金
美国医疗保健研究与质量局;
关键词
DIAGNOSTIC ERRORS; TOOL; RELIABILITY; SAFETY; DELAYS;
D O I
10.1136/bmjqs-2017-006975
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
引用
收藏
页码:241 / 246
页数:6
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