Decision-support Simulation of Patient Treatment Process.
Year: 2021
Type: conference-paper
Abstract: The transition from being a medical student, with limited responsibilities and a high level of supervision, to becoming a medical intern or newly qualified doctor, with medical responsibility for individ- ual patients and less supervision, is difficult and stressful. Occasionally medical trainees experience high levels of uncertainties in diagnosing pa- tients’ issues and making decisions about proper treatment for them which may be life-threatening for patients. Therefore preparing medi- cal interns and junior doctors with the skills necessary to deal with real medical experiences is crucial. For efficient acquisition of medical knowl- edge and skill without compromising patient safety, a simulation-based approach can be considered as an appropriate option. The main contri- bution of this research lies in developing a decision-support simulation tool for the patient treatment process to assist medical interns and junior doctors to transform their theoretical knowledge into practice. To do so, we propose the combined process mining and data mining techniques to analyze and discover patient treatment process models to support the construction of simulation models.
Author: Camelia Maleki
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3203925360