Proactive on-call scheduling during a seasonal epidemic

Abstract

Overcrowding in Emergency Departments (EDs) is particularly problematic during seasonal epidemic crises. Each year during this period, EDs set off recourse actions to cope with the increase in workload.Uncertainty in the length and amplitude of epidemics make managerial decisions difficult. We propose in this study a staff allocation model to manage the situation using on-calls. An on-call scheduling policy is proposed to best balance between demand coverage and labor cost under legal constraints of working time.The problem is modelled as a two-stage stochastic Integer Linear Program (ILP) and solved using a Sample Average Approximation (SAA) method. Several epidemic scenarios are defined with data from an ED in Lille, France.

Decision-making tools for healthcare structures in times of pandemic

“…The research team of the CNRS lab LIMOS and Mines Saint-Étienne developed several methods and tools to evaluate and support patient flow and resource management decisions. This research is rooted in several studies conducted on emergency management during epidemics or floods [7] , [8] , [9] , [10] , home health care services [11] and cancer treatments [12] . All these works do not consider some specificities of pandemics like COVID-19, with the burden put on the complete health care network and the high risk of contamination for patients and caregivers.…”

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

“…Initially, Othman et al [178] used multi-agent system along with multiskill task scheduling for helping physicians of a French pediatric ED to anticipate the feature of overcrowding. Another intervention using a mix of OR methods can be seen in El-Rifai et al [196] where a two-stage stochastic integer linear program and sample average approximation were conjointly used for managing staff allocation and consequently coping with congestion in an ED located in Lille, France. Decreasing overcrowding by combining OR methods were also found in González et al [172], Acuna, et al [132], and He et al [109].…”

Personnel scheduling during Covid-19 pandemic

“…(15) Objective function (3) minimizes the total deviation Δ between the amount of weekly contractual hours for each worker (h max e ) and the actual working hours (y wa se ). Constraints (4) impose that each employee must be weekly assigned to exactly one shift s ∈ {1, 2} and one sector a ∈ A. Constraints (5) ensure that if an employee e ∈ E is designated to sector a ∈ A in the first week (w = 1), he/she must work in the same sector in the next week (w = 2).…”

“…According to the classification scheme presented in [5], we can categorize the scheduling made by the company before and after Covid-19 pandemic as demand-based and shift-based, respectively. The latter is extensively adopted in nurse scheduling studies [e.g., 4,17]. In particular, a variant of the problem was tackled in [23], in which nurses with the same skills, or that are married to each other and with children, were not allowed to work together during the same shift.…”