Villa Stephen, Weber Ellen J, Polevoi Steven, Fee Christopher, Maruoka Andrew, Quon Tina
Department of Emergency Medicine, UCSF, 535 Parnassus Ave, San Francisco, CA, USA.
IT Clinical Applications and Analytics, UCSF, 400 Parnassus Ave, San Francisco, CA, USA.
Int J Qual Health Care. 2018 Jun 1;30(5):375-381. doi: 10.1093/intqhc/mzy056.
To determine if adapting a widely-used triage scale into a computerized algorithm in an electronic health record (EHR) shortens emergency department (ED) triage time.
Before-and-after quasi-experimental study.
Urban, tertiary care hospital ED.
Consecutive adult patient visits between July 2011 and June 2013.
A step-wise algorithm, based on the Emergency Severity Index (ESI-5) was programmed into the triage module of a commercial EHR.
Duration of triage (triage interval) for all patients and change in percentage of high acuity patients (ESI 1 and 2) completing triage within 15 min, 12 months before-and-after implementation of the algorithm. Multivariable analysis adjusted for confounders; interrupted time series demonstrated effects over time. Secondary outcomes examined quality metrics and patient flow.
About 32 546 patient visits before and 33 032 after the intervention were included. Post-intervention patients were slightly older, census was higher and admission rate slightly increased. Median triage interval was 5.92 min (interquartile ranges, IQR 4.2-8.73) before and 2.8 min (IQR 1.88-4.23) after the intervention (P < 0.001). Adjusted mean triage interval decreased 3.4 min (95% CI: -3.6, -3.2). The proportion of high acuity patients completing triage within 15 min increased from 63.9% (95% CI 62.5, 65.2%) to 75.0% (95% CI 73.8, 76.1). Monthly time series demonstrated immediate and sustained improvement following the intervention. Return visits within 72 h and door-to-balloon time were unchanged. Total length of stay was similar.
The computerized triage scale improved speed of triage, allowing more high acuity patients to be seen within recommended timeframes, without notable impact on quality.
确定将一种广泛使用的分诊量表改编为电子健康记录（EHR）中的计算机化算法是否能缩短急诊科（ED）的分诊时间。
前后对照的准实验研究。
城市三级护理医院急诊科。
2011年7月至2013年6月期间连续就诊的成年患者。
基于急诊严重程度指数（ESI-5）的逐步算法被编程到商业EHR的分诊模块中。
算法实施前后12个月内所有患者的分诊持续时间（分诊间隔），以及在15分钟内完成分诊的高 acuity 患者（ESI 1和2）百分比的变化。多变量分析对混杂因素进行了调整；中断时间序列显示了随时间的影响。次要结果检查了质量指标和患者流程。
干预前纳入约32546例患者就诊，干预后纳入33032例。干预后患者年龄稍大，人口普查人数较多，入院率略有增加。干预前分诊间隔中位数为5.92分钟（四分位间距，IQR 4.2 - 8.73），干预后为2.8分钟（IQR 1.88 - 4.23）（P < 0.001）。调整后的平均分诊间隔减少了3.4分钟（95% CI：-3.6，-3.2）。在15分钟内完成分诊的高 acuity 患者比例从63.9%（95% CI 62.5，65.2%）增加到75.0%（95% CI 73.8，76.1）。每月时间序列显示干预后立即且持续改善。72小时内的复诊和门球时间未改变。总住院时间相似。
计算机化分诊量表提高了分诊速度，使更多高 acuity 患者能够在推荐的时间范围内就诊，且对质量无显著影响。
