Medical Decision Making
“Our mission is to contribute to optimal evidence-based and personalized decisions in healthcare. ... We apply our methods in collaboration with multiple clinical groups within and outside Erasmus MC to directly improve patient care."
Medical decision-making aims to support patients, clinicians and healthcare policymakers in making the best decisions about diagnostic, therapeutic and other medical interventions. Our mission is to contribute to optimal evidence-based and personalized decisions in healthcare. We work on the development of quantitative methods such as prediction modelling, quasi-experimental study designs, measuring quality of care, and comparative effectiveness research (CER). We apply our methods in collaboration with multiple clinical groups within and outside Erasmus MC to directly improve patient care. During the pandemic we worked on two projects to aid decision making during the pandemic. With colleagues from other Erasmus MC departments and with partners from the US we developed the COPE model to predict outcome in COVID-19 patients presenting to the Emergency Department. With colleagues from other Erasmus MC departments we developed a model to prioritize surgeries in case of scarcity due to COVID-19 care.
Highlights
of Medical Decision Making in 2020
Prioritizing surgery
COVID-19 has put unprecedented pressure on healthcare systems worldwide, leading to a reduction of the available healthcare capacity. Together with colleagues from different other departments within Erasmus MC we developed a decision model to estimate the impact of postponing semi-elective surgeries on health, to support prioritization of care from a utilitarian perspective.
A cohort state-transition model was developed and applied to semi-elective surgeries commonly performed in academic hospitals. Scenarios of delaying surgery from two weeks were compared with delaying up to one year, and no surgery at all. Model parameters were based on registries, scientific literature, and the World Health Organization. The model transparently and consistently aggregates best available objective evidence across disciplines to estimate expected health loss due to surgical delay. It is available as web application and can be used to guide prioritization of surgeries to minimize population health loss in times of scarcity.
Smarter choices for better health
Improved health care and an ageing population cause healthcare costs to rise. Without effective intervention, there is the risk that health care will become unaffordable in the long run. It is therefore vital that we examine how we can achieve the best results for the health of as many people as possible with limited resources. Within the Smarter Choices for Better Health initiative of the Erasmus University, we work with academics from other disciplines, such as health economics, to make health care systems fairer and more effective with the existing financial resources. In a study on quality improvement in stroke care we showed that, to facillitate benchmarking between providers to achieve quality improvement it is crucial to collect and present information on processes of care instead of only patient outcomes.
