Using industry tools to improve health-care workloads
Canada’s health-care sector is struggling with worker retention and burnout, according to the Canadian federal government in its information on the health workforce. By applying best practices and workload management tools from the manufacturing industry, two Toronto Metropolitan University (TMU) researchers are helping better understand and manage frontline health-care employees’ workloads and patient care.
TMU nursing professor Sue Bookey-Bassett and engineering professor Patrick Neumann have developed workload simulation models, to provide key insights to health-care decision makers. Their initial research focused on nurses prior to the COVID-19 epidemic. They have since expanded their studies to different health-care settings and to include personal support workers along with nurses. By using computer models to create virtual simulations of health-care units, they can input variables and data drawn from real-life care teams to understand the workloads and explore new scenarios related to care delivery and quality.
"Many nurses experience moral distress and trauma due to the fact that they cannot provide the quality of care they want to provide because they don’t have the time,” said professor Bookey-Bassett. The trauma and burnout can lead to retention issues. In the manufacturing industry, workload and task management are often carefully measured. The workload facing Canada’s health-care providers is not currently objectively measured. “How do you know you’re not overloading them, in which case both the workers and patients suffer?” said professor Neumann. The researchers’ simulation models can help balance workload management and health-care system design, he said.
Exploring workload routines and questions
In collaboration with a Toronto-area hospital, their research team has set up simulation models for units including medical-surgical, complex continuing care and an emergency department. A long-term care project is planned for the future. Created in consultation with hospital collaborators, the simulation models can explore a variety of questions or situations to examine impacts on routines and workloads. Questions can range from how to better minimize pressure injuries – more commonly known as bedsores – to how much time donning personal protective equipment (PPE) can add to a nurse’s tasks or looking for instances of missed care. More time spent on tasks like donning and doffing PPE can result in other aspects of care being missed, professor Bookey-Bassett explained, such as emotional support or teaching patients how to manage their care at home. “Missed care is important because when nurses are looking after too many patients, they can’t complete all their work in a day,” she said. Missed care can also result in patients returning to hospitals.
The virtual simulation models created by the research team are customized to each health-care setting. They use data ranging from hospital ward architectural information and bed layout to patient characteristics and care task priorities to ensure they capture current operations before modelling potential alternatives. Gathering the data to achieve exceptional accuracy involves an intense process, including staff surveys, focus groups, interviews and observing workers during their shifts. To understand the physical requirements of a task and the demands on workers' bodies, they have started filming workers in simulated care scenarios has been added to their data collection techniques.
Creating adaptable models
One of the goals is to capture the range of the durations and impacts of tasks – not to create an average, but to understand how they can vary between workers and patients. This will create robust datasets that can be used in adaptable models. “The variability is really important because there is no average patient and there is no average nurse,” said professor Bookey-Bassett. They hope that as they gather more data, they can streamline the development and customization of models for different health-care settings, enabling individual organizations insights into the workload undertaken by their nursing and personal support worker staff through these tools.
The research of professors Bookey-Bassett and Neumann has attracted the interest of senior leaders in health-care organizations as well as provincial and national nursing organizations. The pair have presented at national and international conferences for a variety of disciplines, such as nursing, ergonomics and engineering.
Additional collaborators for this project include professor Marcus Yung of Conestoga College, professor Kevin Woo from Queen’s University, and postdoctoral fellows Michael Greig and Sadeem Qureshi from professor Neumann’s lab. Hospital staff and managers have also provided crucial support for the project through their participation.
This research is supported by the Natural Sciences and Engineering Research Council of Canada, the Canadian Institutes of Health Research and the Centre of Research Expertise for the Prevention of Musculoskeletal Disorders.
Related links
Researchers to develop simulation to manage COVID-19 nurse workload (April 2020)
