A systematic review of the quality and scope of decision modelling studies in child oral health research

BACKGROUND: Decision analytic models are often used in economic evaluations to estimate long-term costs and effects of treatment which span beyond the time-frame of a clinical trial, therefore providing a better understanding of the long-term implications of decisions that conventional trial-based economic evaluations fail to provide. This is particularly relevant for considering oral health interventions in children as treatments may affect adult oral health. However, in the field of child oral health there has not been an evaluation of the quality and scope of decision analytical models which extend into adulthood. The aim of this review is to examine the scope and quality of decision modelling studies, with horizons extending into adulthood, within the field of child oral health. METHODS: The following databases were searched: NHS Economic Evaluation Database (CRD York), MEDLINE, EMBASE, CINAHL, Web of Science, Scopus, the Cochrane Library and Econlit. Full economic evaluations, in the field of child oral health, published after 1997 which included a decision model with a horizon that extended beyond the age of 18 years old were included. Included studies were appraised against the Drummond checklist and the Consolidated Health Economic Evaluation Reporting Standards by calibrated reviewers. RESULTS: Four hundred studies were identified, of which nine met the inclusion criteria. Of the nine, eight were cost-effectiveness models. The majority focussed on the prevention or management of dental caries. The mean percentage of applicable Drummond checklist criteria met by the studies in this review was 82% (median = 85%, range = 54–100%). Discounting of costs and performing an incremental analysis were noted as key methodological weaknesses. The mean percentage of applicable CHEERS criteria met by each study was 82% (median = 87%, range = 32–96%). Justifying the type of model, analytical methods used, and sources of funding were most commonly unreported. CONCLUSIONS: There is a paucity of decision analytical models in the field of child oral health. Most of those that are available are of high methodological and reporting quality. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12903-021-01680-3.