Forecasting emergency department crowding: an external, multicenter evaluation

预测急诊科拥挤情况:一项外部多中心评估

阅读:1

Abstract

STUDY OBJECTIVE: We apply a previously described tool to forecast emergency department (ED) crowding at multiple institutions and assess its generalizability for predicting the near-future waiting count, occupancy level, and boarding count. METHODS: The ForecastED tool was validated with historical data from 5 institutions external to the development site. A sliding-window design separated the data for parameter estimation and forecast validation. Observations were sampled at consecutive 10-minute intervals during 12 months (n=52,560) at 4 sites and 10 months (n=44,064) at the fifth. Three outcome measures-the waiting count, occupancy level, and boarding count-were forecast 2, 4, 6, and 8 hours beyond each observation, and forecasts were compared with observed data at corresponding times. The reliability and calibration were measured following previously described methods. After linear calibration, the forecasting accuracy was measured with the median absolute error. RESULTS: The tool was successfully used for 5 different sites. Its forecasts were more reliable, better calibrated, and more accurate at 2 hours than at 8 hours. The reliability and calibration of the tool were similar between the original development site and external sites; the boarding count was an exception, which was less reliable at 4 of 5 sites. Some variability in accuracy existed among institutions; when forecasting 4 hours into the future, the median absolute error of the waiting count ranged between 0.6 and 3.1 patients, the median absolute error of the occupancy level ranged between 9.0% and 14.5% of beds, and the median absolute error of the boarding count ranged between 0.9 and 2.8 patients. CONCLUSION: The ForecastED tool generated potentially useful forecasts of input and throughput measures of ED crowding at 5 external sites, without modifying the underlying assumptions. Noting the limitation that this was not a real-time validation, ongoing research will focus on integrating the tool with ED information systems.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。