Reducing waiting times at out-of-hours general practitioner departments

Reducing waiting times at out-of-hours general practitioner departments: A data-driven simulation modelling and optimization study

Post, Hanneke (TU Delft Technology, Policy and Management)

Hinrichs-Krapels, S. (graduation committee)
Verbraeck, A. (mentor)
Huang, Yilin (mentor)
de Bruijn, Thijs (graduation committee)

Delft University of Technology

Engineering and Policy Analysis

2021-11-17

The pressure on healthcare systems is increasing all over the world. With an ageing world population, the costs for healthcare and the shortages in medical staff are continually increasing. In the Netherlands, out-of-hours general practitioner departments, or ‘huisartsenposten’, suffer from this increasing pressure in their telephone triage systems: the departments are crowded and the staff capacity is too low to adequately handle the amount of patients. This often leads to long waiting times on the phone for patients in need of potentially urgent medical care and to high pressure work environments for staff. There is no insight into when and why it is crowded, how high waiting times emerge from this, and how changes can be made in the departments internally and beyond to reduce this problem. In this thesis, research is presented that addresses the practical and scientific lack of knowledge of the factors that influence the out-of-hours departments and that identifies how waiting times can be reduced. The results of this thesis focus on the identification of the factors that influence the demand for healthcare and the service times of people at the out-of-hours departments, and they focus on the practical implications for reducing waiting times at these departments. Based on extensive data analysis of two out-of-hours departments in the Netherlands, it was found that temporal factors such as season, part of the week, day of the week and hour of the day, but also the weather conditions and the urgency of the problem of the patient have an impact on demand for healthcare and on service times at these departments. These factors determine how busy it will be and whether or not waiting times will emerge. With the knowledge of these factors, a discrete event simulation model was implemented to identify what system changes are necessary to reduce waiting times at these out-of-hours departments. It was found that there are several quick-win interventions that can help reduce waiting times: shifting of patients from peak demand, implementation of overlapping work shifts for staff and automatic retrieval of patient information when they are waiting in the queue on the phone. There are also some long term interventions, more focused on behavior change of people, that can be implemented: increased accessibility and understanding of the primary healthcare system, a small (dis)incentive for out-of-hours care, separate telephone lines for home care and implementation of working from home for staff.

healthcare
discrete event simulation
simulation model
out-of-hours care
data
python
modeling
healthcare system

http://resolver.tudelft.nl/uuid:7bf3a10c-6844-4507-b293-752f113d625b

Student theses

master thesis

© 2021 Hanneke Post