Systematic review of the use and value of computer simulation modelling in population health and health care delivery.
BACKGROUND
The objective of the review was to evaluate the extent, quality and value of computer simulation modelling in population health and health care delivery.


METHODS
A narrative systematic review was carried out of world literature from 1980 to 1999, searching Medline, INSPEC, Embase, HealthSTAR, Science Citation Index, CINAHL, MathSci, INFORMS Online and SIGLE databases, and researchers in the field were contacted. Papers were included if they contained a computer simulation model of individuals in a stochastic system and the topic or setting related to population health or health service delivery.


RESULTS
A total of 182 papers met the inclusion criteria. Simulation modelling has been undertaken in a wide range of health care topic areas, including hospital scheduling and organization, communicable disease, screening, costs of illness and economic evaluation. However, the quality of published papers was variable and few reported on the outcomes of implementation of models, so that the value of modelling could not be assessed.


CONCLUSIONS
Simulation modelling is a powerful method for modelling both small and large populations to inform policy makers in the provision of health care. It has been applied to a wide variety of health care problems. Although the number of modelling papers has grown substantially over recent years, further research is required to assess the value of modelling.
Fone
David
D
Gwent Health Authority, Mamhilad House, Mamhilad Park Estate, Pontypool NP4 0YP, UK. david.fone@nphs.wales.nhs.uk
Hollinghurst
Sandra
S
Temple
Mark
M
Round
Alison
A
Lester
Nathan
N
Weightman
Alison
A
Roberts
Katherine
K
Coyle
Edward
E
Bevan
Gwyn
G
Palmer
Stephen
S
D003140:Communicable Disease Control; D003198:Computer Simulation; D003365:Costs and Cost Analysis; D003695:Delivery of Health Care / Q000191:economics; D008403:Mass Screening; D015233:Models, Statistical; D010561:Personnel Staffing and Scheduling; D012107:Research Design; D013269:Stochastic Processes; D000078329:Workforce