Out of hours workload management: Bayesian inference for decision support in secondary care
作者：
Highlights：
• We evaluate electronic technologies to assist management in health care facilities.
• We employ state-space graphical models for the study of out-of-hours care workload.
• We present an exhaustive study of demand patterns across multiple specialities.
• The paper draws and validates conclusions with relevance to out of hours services.
• We emphasize the importance of data-driven staffing and intelligent scheduling.
摘要
Highlights•We evaluate electronic technologies to assist management in health care facilities.•We employ state-space graphical models for the study of out-of-hours care workload.•We present an exhaustive study of demand patterns across multiple specialities.•The paper draws and validates conclusions with relevance to out of hours services.•We emphasize the importance of data-driven staffing and intelligent scheduling.
论文关键词：Healthcare management,Multivariate time series,Count data,Out of hours,Graphical model
论文评审过程：Received 26 April 2016, Revised 29 September 2016, Accepted 29 September 2016, Available online 1 October 2016, Version of Record 7 October 2016.
论文官网地址：https://doi.org/10.1016/j.artmed.2016.09.005
