Do different decision-analytic modeling approaches produce different results? A systematic review of cross-validation studies.
When choosing a modeling approach for health economic evaluation, certain criteria are often considered (e.g., population resolution, interactivity, time advancement mechanism, resource constraints). However, whether these criteria and their associated modeling approach impacts results remain poorly understood. A systematic review was conducted to identify cross-validation studies (i.e., modeling a problem using different approaches with the same body of evidence) to offer insight on this topic. With respect to population resolution, reviewed studies suggested that both aggregate- and individual-level models will generate comparable results, although a practical trade-off exists between validity and feasibility. In terms of interactivity, infectious-disease models consistently showed that, depending on the assumptions regarding probability of disease exposure, dynamic and static models may produce dissimilar results with opposing policy recommendations. Empirical evidence on the remaining criteria is limited. Greater discussion will therefore be necessary to promote a deeper understanding of the benefits and limits to each modeling approach.
Clinical Epidemiology and Biostatistics, McMaster University, 25 Main Street West, Suite 2000 Hamilton, Ontario L8P 1H1, Canada.
Bernice
B
Tsoi
Ron
R
Goeree
Jathishinie
J
Jegathisawaran
Jean-Eric
JE
Tarride
Gord
G
Blackhouse
Daria
D
O'Reilly
D003141:Communicable Diseases / Q000191:economics* / Q000453:epidemiology; D003661:Decision Support Techniques; D006291:Health Policy; D006801:Humans; D018803:Models, Economic; D054928:Validation Studies as Topic
Markov model; compartmental models; decision analysis; decision trees; health economic evaluation; microsimulation; state-transition models; systematic review; validity