A systematic review of whole disease models for informing healthcare resource allocation decisions

Abstract

Background Whole disease models (WDM) are large-scale, system-level models which can evaluate multiple decision questions across an entire care pathway. Whilst this type of model can offer several advantages as a platform for undertaking economic analyses, the availability and quality of existing WDMs is unknown. Objectives This systematic review aimed to identify existing WDMs to explore which disease areas they cover, to critically assess the quality of these models and provide recommendations for future research. Methods An electronic search was performed on multiple databases (MEDLINE, EMBASE, the NHS Economic Evaluation Database and the Health Technology Assessment database) on 23rd July 2023. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) appraisal checklist for economic evaluations. Model characteristics were descriptively summarised. Results Forty-four WDMs were identified, of which thirty-two were developed after 2010. The main disease areas covered by existing WDMs are heart disease, cancer, acquired immune deficiency syndrome and metabolic disease. The quality of included WDMs is generally low. Common limitations included failure to consider the harms and costs of adverse events (AEs) of interventions, lack of probabilistic sensitivity analysis (PSA) and poor reporting. Conclusions There has been an increase in the number of WDMs since 2010. However, their quality is generally low which means they may require significant modification before they could be re-used, such as modelling AEs of interventions and incorporation of PSA. Sufficient details of the WDMs need to be reported to allow future reuse/adaptation.

Is Economic Evaluation and Care Commissioning Focused on Achieving the Same Outcomes? Resource-Allocation Considerations and Challenges Using England as a Case Study

“…By extension, this also facilitates an assessment of the potential suitability of that surrogate for achieving endpoint outcomes of interest. However, decision-analytic tools for HTA often focus on cohort-based disease and/or care pathway models (e.g., whole-disease models) that are not necessarily sufficient to represent the complex systems within which commissioning decisions occur [64,65]. In comparison, more complex models such as discrete event simulations (DES) and agentbased models can better represent individuals and the system within which they reside, but require additional knowledge and data to develop [66,67].…”