A competency framework on simulation modelling-supported decision-making for Master of Public Health graduates

Author:

Hrzic Rok12,Cade Maria Vitoria12,Wong Brian Li Han12,McCreesh Nicky34,Simon Judit56,Czabanowska Katarzyna127

Affiliation:

1. Department of International Health , Care and Public Health Research Institute – CAPHRI, , Maastricht, 6200 MD , Netherlands

2. Maastricht University , Care and Public Health Research Institute – CAPHRI, , Maastricht, 6200 MD , Netherlands

3. Department of Infectious Disease Epidemiology and Dynamics , Centre for Mathematical Modelling of Infectious Diseases, , London, WC1E 7HT , UK

4. London School of Hygiene and Tropical Medicine , Centre for Mathematical Modelling of Infectious Diseases, , London, WC1E 7HT , UK

5. Department of Health Economics , Center for Public Health, , Vienna, 1090 , Austria

6. Medical University of Vienna , Center for Public Health, , Vienna, 1090 , Austria

7. Department of Health Policy Management, Institute of Public Health, Jagiellonian University , Krakow, 31-066 , Poland

Abstract

Abstract Background Simulation models are increasingly important for supporting decision-making in public health. However, due to lack of training, many public health professionals remain unfamiliar with constructing simulation models and using their outputs for decision-making. This study contributes to filling this gap by developing a competency framework on simulation model-supported decision-making targeting Master of Public Health education. Methods The study combined a literature review, a two-stage online Delphi survey and an online consensus workshop. A draft competency framework was developed based on 28 peer-reviewed publications. A two-stage online Delphi survey involving 15 experts was conducted to refine the framework. Finally, an online consensus workshop, including six experts, evaluated the competency framework and discussed its implementation. Results The competency framework identified 20 competencies related to stakeholder engagement, problem definition, evidence identification, participatory system mapping, model creation and calibration and the interpretation and dissemination of model results. The expert evaluation recommended differentiating professional profiles and levels of expertise and synergizing with existing course contents to support its implementation. Conclusions The competency framework developed in this study is instrumental to including simulation model-supported decision-making in public health training. Future research is required to differentiate expertise levels and develop implementation strategies.

Funder

Maastricht University

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health,General Medicine

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