Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto

TL;DR

This paper presents a hierarchical optimization-based scheduling tool that automates nurse scheduling in Toronto's long-term care homes, significantly reducing planning time and increasing staff satisfaction.

Contribution

The paper introduces a novel spreadsheet-based scheduling tool with a hierarchical optimization model that efficiently generates feasible, preference-aware nurse schedules under complex seniority constraints.

Findings

Schedules generated in minutes versus hours manually

Over 94% of shifts were assigned to nurses' top preferences

The tool improved scheduling efficiency and staff satisfaction

Abstract

The City of Toronto Long Term Care Homes & Services (LTCH&S) division is one of the largest providers of long-term care in the Canadian province of Ontario, providing care to 2,640 residents at 10 homes across Toronto. Our collaboration with LTCH&S was initiated to facilitate the increasingly challenging task of scheduling nursing staff and reduce high absenteeism rate observed among the part-time nurses. We developed a spreadsheet-based scheduling tool to automate the generation of schedules and incorporate nurses' preferences for different shifts into the schedules. At the core of the scheduling tool is a hierarchical optimization model that generates a feasible schedule with the highest total preference score while satisfying the maximum possible demand. Feasible schedules had to abide by a set of complex seniority requirements which prioritized more senior nurses when allocating the available shifts. Our scheduling tool was implemented in a 391-bed home in Toronto. The tool allowed nursing managers to generate feasible schedules within a fraction of an hour, in contrast to the status-quo manual approach which could took up to tens of hours. In addition, the schedules successfully accounted for preferences with on average above 94% of the allocated shifts ranked as most preferred.