Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review.
PLoS One
; 17(2): e0263299, 2022.
Article
in English
| MEDLINE | ID: covidwho-1686099
ABSTRACT
BACKGROUND:
Decision-makers for public policy are increasingly utilising systems approaches such as system dynamics (SD) modelling, which test alternative interventions or policies for their potential impact while accounting for complexity. These approaches, however, have not consistently included an economic efficiency analysis dimension. This systematic review aims to examine how, and in what ways, system dynamics modelling approaches incorporate economic efficiency analyses to inform decision-making on innovations (improvements in products, services, or processes) in the public sector, with a particular interest in health. METHODS ANDFINDINGS:
Relevant studies (n = 29) were identified through a systematic search and screening of four electronic databases and backward citation search, and analysed for key characteristics and themes related to the analytical methods applied. Economic efficiency analysis approaches within SD broadly fell into two categories as embedded sub-models or as cost calculations based on the outputs of the SD model. Embdedded sub-models within a dynamic SD framework can reveal a clear allocation of costs and benefits to periods of time, whereas cost calculations based on the SD model outputs can be useful for high-level resource allocation decisions.CONCLUSIONS:
This systematic review reveals that SD modelling is not currently used to its full potential to evaluate the technical or allocative efficiency of public sector innovations, particularly in health. The limited reporting on the experience or methodological challenges of applying allocated efficiency analyses with SD, particularly with dynamic embedded models, hampers common learning lessons to draw from and build on. Further application and comprehensive reporting of this approach would be welcome to develop the methodology further.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Health Policy
Type of study:
Experimental Studies
/
Reviews
/
Systematic review/Meta Analysis
Language:
English
Journal:
PLoS One
Journal subject:
Science
/
Medicine
Year:
2022
Document Type:
Article
Affiliation country:
Journal.pone.0263299
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