Out of hours workload management: Bayesian inference for decision support in secondary care

Perez, Iker, Brown, Michael, Pinchin, James, Martindale, Sarah, Sharples, Sarah, Shaw, Dominic and Blakey, John (2016) 'Out of hours workload management: Bayesian inference for decision support in secondary care'. Artificial Intelligence in Medicine, Vol 73, Issue October 2016, pp. 34-44.

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Abstract

Objective
In this paper, we aim to evaluate the use of electronic technologies in out of hours (OoH) task-management for assisting the design of effective support systems in health care; targeting local facilities, wards or specific working groups. In addition, we seek to draw and validate conclusions with relevance to a frequently revised service, subject to increasing pressures.

Methods and material
We have analysed 4 years of digitised demand-data extracted from a recently deployed electronic task-management system, within the Hospital at Night setting in two jointly coordinated hospitals in the United Kingdom. The methodology employed relies on Bayesian inference methods and parameter-driven state-space models for multivariate series of count data.

Results
Main results support claims relating to (i) the importance of data-driven staffing alternatives and (ii) demand forecasts serving as a basis to intelligent scheduling within working groups. We have displayed a split in workload patterns across groups of medical and surgical specialities, and sustained assertions regarding staff behaviour and work-need changes according to shifts or days of the week. Also, we have provided evidence regarding the relevance of day-to-day planning and prioritisation.

Conclusions
The work exhibits potential contributions of electronic tasking alternatives for the purpose of data-driven support systems design; for scheduling, prioritisation and management of care delivery. Electronic tasking technologies provide means to design intelligent systems specific to a ward, speciality or task-type; hence, the paper emphasizes the importance of replacing traditional pager-based approaches to management for modern alternatives.

Item Type:	Article
Subjects:	W General Medicine. Health Professions > W 21.5 Allied health personnel. Allied health professions W General Medicine. Health Professions > Health Services. Patients and Patient Advocacy > W 84 Health services. Delivery of health care WX Hospitals and Other Health Facilities > Clinical Departments and Units > WX 203 Medical personnel. Interns. Staff manuals. Ward manuals and precedent books
Faculty: Department:	Clinical Sciences & International Health > Clinical Sciences Department
Digital Object Identifer (DOI):	https://doi.org/10.1016/j.artmed.2016.09.005
Depositing User:	Jessica Jones
Date Deposited:	31 Oct 2016 16:33
Last Modified:	01 Oct 2017 01:02
URI:	https://archive.lstmed.ac.uk/id/eprint/6324

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