JMIR Publications

ABSTRACT

Background:

Many people relapse after achieving abstinence in substance use disorders. Digital technologies have potential to predict relapse allowing interventions to be targeted thus reducing relapse rate.

Objective:

This study aims to assess the potential of such digital technologies to offer cost savings or be cost-effective for healthcare providers using a case study of the mobile app/web platform, Subreal App. We explored the threshold price and clinical effectiveness required to deliver cost savings and cost-effectiveness.

Methods:

Deterministic early health economic models estimating health and social care costs in the UK, costs per relapse and quality adjusted life years over 1, 5 and 20-year time horizons for people who have achieved abstinence after treatment for alcohol or opioid misuse. The intervention is a digital technology predicting relapse provided for one year post achievement of abstinence in addition to standard care. In our case study using Subreal App, patients report biomarker data daily through the app. Data is collected and an artificial intelligence (AI) enhanced risk-assessment flags patients who require additional care. Care is provided as determined by the individual’s care plan. The comparator is treatment as usual generally including event-driven reactive response to relapse. Costs and quality of life estimates are calculated using decision analytic models with parameter estimates from existing published sources. Evidence for the clinical effectiveness of Subreal App is not available but there is evidence in the literature from another digital technology designed to predict relapse in this population. The base case estimate of 15% reduction in relapse rates during the first year was based on evidence for this technology.

Results:

Digital technologies such as Subreal App have the potential to be cost saving and cost effective from a UK Health and Social Care perspective especially when used over a longer time horizon. Assuming a reduction in first-year relapse rates of 15%, digital technologies have potential to be cost-effective (cost saving) providing they do not cost more than £350 (£300) per patient per annum for alcohol use disorder and £700 (£460) per patient for opioid use disorder. No cost is included for post-alert care as it is assumed that this could be met within existing resources. Cost savings are predominantly achieved through a reduction in treatment requirements as less people relapse. Price thresholds would reduce correspondingly if a reduction in relapses greater than 15% were achieved.

Conclusions:

Developers of digital technologies that aim to reduce relapse need to focus on the generation of evidence of clinical effectiveness and develop a commercially-sustainable pricing model that allows healthcare providers to benefit from cost savings. Clinical Trial: Not required