COST-EFFECTIVENESS ANALYSES OF BEHAVIORAL INTERVENTIONS- TOWARDS A MORE REALISTIC COST-EFFECTIVENESS RATIO BY INCLUDING INTERMEDIATE OUTCOME MEASURES
Author(s)
Rilana Prenger, MSc, PhD student1, Louise MA Braakman-Jansen, PhD, Assistant Professor1, Marcel E Pieterse, PhD, Assistent Professor1, Job van der Palen, MSc, PhD, Clinical epidemiologist2, Erwin R Seydel, PhD, Head of department11University of Twente, Enschede, Netherlands; 2 Medisch Spectrum Twente Hospital, Enschede, Netherlands
OBJECTIVES: Behavioral health interventions traditionally use a simple dichotomous outcome criterion: ‘success’ or ‘failure’. In reality, though, behavior change is a complex process in which several steps towards success are taken. There has been little consideration, however, about whether future behavior change should be incorporated in cost-effectiveness analyses (CEAs). The aim of the present review is to identify and evaluate the usage of cognitive, intermediate outcomes in CEAs of behavioral interventions. METHODS: Electronic data sources (PsycInfo, WebofScience, Medline, ScienceDirect and Scopus) were searched for CEAs published before February 2008. RESULTS: Most CEAs and CUAs reporting cognitive, intermediate outcomes of behavior change fail to incorporate partial behavior changes. Only nine studies were eligible for inclusion in this review. Smith et al 2007 [1] conducted the only study in which partial behavior change was incorporated in the final outcome by modeling cognitive, intermediate outcomes: the stages of change, derived from the Transtheoretical model (TTM). The TTM is a stage-oriented model that describes the process by which a change in behavior takes place. It describes the readiness to change and the processes employed by individuals to achieve behavioral change. With inclusion of future behavior change, Smith et al showed that the incremental cost-effectiveness ratio declined compared to the standard analysis. CONCLUSIONS: The results suggest that CEAs of behavioral interventions can be further optimized by the measurement of intermediate outcomes and use these to determine partial behavior change at the end of an intervention period as well. In other words, when partial behavior change and relapse rates are incorporated in CEAs of behavioral treatments, a more realistic and transparent final outcome can be calculated. [1] Smith, MY, Cromwell, J, DePue, J, et al. Determining the cost-effectiveness of a computer-based smoking cessation intervention in primary care. Managed Care 2007;16:48-55.
Conference/Value in Health Info
2008-11, ISPOR Europe 2008, Athens, Greece
Value in Health, Vol. 11, No. 6 (November 2008)
Code
PMC19
Topic
Methodological & Statistical Research
Topic Subcategory
Modeling and simulation
Disease
Multiple Diseases