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. 2025 May 22;39(9):305-324.
doi: 10.1108/JHOM-10-2024-0422.

Managing and measuring performance of health prevention services: a simulation-based approach

Guido Noto  1 , Francesca De Domenico  1 , Sandra C Buttigieg  2   3 , Gustavo Barresi  1
Affiliations

Managing and measuring performance of health prevention services: a simulation-based approach

Guido Noto et al. J Health Organ Manag. .

Abstract

Purpose: This study focuses on the application of performance management (PM) in health prevention services. Unlike other healthcare services that focus on individual health results, prevention activities aim at community-wide benefits, often related to the avoidance of negative health outcomes. This, coupled with delayed effects of prevention activities, external influences on results and multiple stakeholders, poses challenges for the management, measurement and accountability of the results achieved by healthcare organisations and systems. To address these challenges, the research proposes the adoption of simulation techniques, specifically system dynamics (SD), to enhance PM in the prevention sector.

Design/methodology/approach: SD is a methodological approach developed for modelling and simulating complex systems and experimenting with the models to design strategies and policies. It provides a systemic perspective and a set of conceptual tools that enable one to frame the structure and behaviour of complex, nonlinear, multi-loop feedback systems through an illustrative case focused on the management of primary and secondary prevention of chronic care conditions within a Beveridge healthcare system.

Findings: By employing SD, the study aims to provide decision-makers with the capability to understand the link between immediate outputs and long-term outcomes, facilitating the evaluation of alternative policy options and scenarios that are otherwise untestable due to the long latency of diseases, delayed impact of preventive actions and systemic fragmentation.

Originality/value: Through the development of an SD model, this research contributes to the field by offering a novel approach to overcoming the measurement and accountability obstacles in prevention as part of healthcare PM.

Keywords: Healthcare; Performance management; Prevention; Simulation; System dynamics.

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Further reading

    1. Chen, H.J., Xue, H., Liu, S., Huang, T.T.K., Wang, Y.C. and Wang, Y. (2018), “Obesity trend in the United States and economic intervention options to change it: a simulation study linking ecological epidemiology and system dynamics modelling”, Public Health, Vol. 161, pp. 20-28, doi: 10.1016/j.puhe.2018.01.013.
    1. Degeling, C., Johnson, J., Kerridge, I., Wilson, A., Ward, M., Stewart, C. and Gilbert, G. (2015), “Implementing a one health approach to emerging infectious disease: reflections on the socio-political, ethical and legal dimensions”, BMC Public Health, Vol. 15, pp. 1-11, doi: 10.1186/s12889-015-2617-1.
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    1. Fusco, F., Marsilio, M. and Guglielmetti, C. (2023), “Co-creation in healthcare: framing the outcomes and their determinants”, Journal of Service Management, Vol. 34 No. 6, pp. 1-26, doi: 10.1108/josm-06-2021-0212.
    1. Ghaffarzadegan, N., Lyneis, J. and Richardson, G.P. (2011), “How small system dynamics models can help the public policy process”, System Dynamics Review, Vol. 27 No. 1, pp. 22-44, doi: 10.1002/sdr.442.

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