Digitalization as an Engine for Change? Building a Vision Pathway towards a Sustainable Health Care System by Using the MLP and Health Economic Decision Modelling

Grand social challenges, such as type 2 diabetes (T2D), are increasing, which creates sustainability problems for health care service systems. To reduce socio-economic burdens, changes are required in the socio-technical system. However, there is an uncertainty of the most cost-effective policy action that can create sustainability while providing health benefits. To find potential solutions to these challenges, the multi-level perspective (MLP) and health economic decision modelling was used to study socio-technical change and project potential health economic consequences of different scenarios. The study focuses on creating a vision pathway for reducing T2D in Finland. In total, 23 interviews were carried out and the results were analyzed utilizing the MLP model. As a result, five themes towards prevention of T2D were identified. Digitalization was found to be a cross-cutting theme for preventing T2D and was thus taken as the object of study and the main focus of this paper. As a result, this paper reports on the opportunities and barriers for using digital tools in a transition towards T2D prevention. A health economic decision modelling revealed that the highest expected savings could be obtained by prioritizing prevention programs based on T2D risk. Finally, the model was converted into a web-based online tool by combining vision pathway, transition-focused storylines and forward-looking health economic scenario analysis to give the policy makers an overall picture of the needed societal changes and support the impact assessment of alternative policies in a case of T2D prevention in Finland.

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.