OBJECTIVES: Inadequate treatment response in serious mental illness (SMI) patients is widespread, with contributing factors including poor adherence, lifestyle (e.g. activity, sleep and mood) and treatment regimen. Digital interventions that increase the quality and quantity of information available to clinicians have the potential to improve clinical decision making and hence patient outcomes in SMI, as well as leading to cost savings from a reduced need for unplanned care. This study aimed to develop a conceptual framework to assess the savings arising from using digital interventions to support decision making, and to identify value drivers and evidence gaps.

METHODS: A conceptual economic model was developed to predict the impact of a digital intervention on SMI patients’ treatment and outcomes from a UK National Health Service perspective over a 5-year time horizon. The intervention was assumed to provide clinicians with information on the adherence of patients to their current treatment regimen for 3 months, enabling more personalised patient support and better-informed decisions when adjusting or switching treatments. Model inputs were informed by targeted literature searches and expert opinion. Scenario analyses investigated a range of intervention efficacies in the absence of relevant clinical data.

RESULTS: Base case model results showed that cost savings per patient of £1,929 in year 1 and at least £7,500 over 5 years could be achieved when using the digital intervention. Using a conservatively estimated eligible population of 22,000, the intervention could generate savings of £42.4 million in year 1 and £165 million over 5 years.

CONCLUSIONS: This conceptual model demonstrates that using digital interventions can lead to cost savings and improved patient outcomes; it can also be readily adapted to specific interventions. However, robust, quantitative data on the impact of digital interventions on clinician decision making are needed to ensure the analysis is useful for resource allocation decisions.