Regulation and accreditation of addictive behaviour applications-navigating the landscape

Mobile Health Interventions for Substance Use Disorders

Substance use disorders (SUDs) have an enormous negative impact on individuals, families, and society as a whole. Most individuals with SUDs do not receive treatment because of the limited availability of treatment providers, costs, inflexible work schedules, required treatment-related time commitments, and other hurdles. A paradigm shift in the provision of SUD treatments is currently underway. Indeed, with rapid technological advances, novel mobile health (mHealth) interventions can now be downloaded and accessed by those that need them anytime and anywhere. Nevertheless, the development and evaluation process for mHealth interventions for SUDs is still in its infancy. This review provides a critical appraisal of the significant literature in the field of mHealth interventions for SUDs with a particular emphasis on interventions for understudied and underserved populations. We also discuss the mHealth intervention development process, intervention optimization, and important remaining questions.

Navigating Medical Device Certification: A Qualitative Exploration of Barriers and Enablers Amongst Innovators, Notified Bodies and Other Stakeholders

BACKGROUND

Medical device certification has undergone significant changes in recent years. However, exploration of stakeholder experiences remains relatively limited, particularly in the context of software as a medical device. This study sought to explore stakeholder experiences of medical device certification across both the UK and EU.

METHODS

Semi-structured interviews (n = 22) analysed using inductive-thematic analysis, synthesised using activity theory.

RESULTS

Innovators, consultants and notified bodies share more similarities than differences when discussing barriers and enablers to achieving medical device certification. Systemic tensions between existing rules, tools, community understanding and division of labour currently undermine the intended aim of certification processes. Existing rules are considered complex, with small and medium-sized enterprises considered disproportionality affected, resulting in several unintended outcomes including the perceived 'killing' of innovation. Existing certification processes are described as unfit for purpose, unethical and unsustainable.

CONCLUSION

Stakeholder experiences suggest that the intention of establishing a robust and sustainable regulatory framework capable of ensuring a high level of safety whilst also supporting innovation is not yet being realised. Failure to enact desired changes may further jeopardise future innovations, outcomes and care quality.

Novel Implementation Strategy to Electronically Screen and Signpost Patients to Health Behavior Apps: Mixed Methods Implementation Study (OptiMine Study)

BACKGROUND

Behavior change apps have the potential to provide individual support on a population scale at low cost, but they face numerous barriers to implementation. Electronic health records (EHRs) in acute care hospitals provide a valuable resource for identifying patients at risk, who may benefit from behavior change apps. A novel, emerging implementation strategy is to use digital technologies not only for providing support to help-seeking individuals but also for signposting patients at risk to support services (also called proactive referral in the United States).

OBJECTIVE

The OptiMine study aimed to increase the reach of behavior change apps by implementing electronic signposting for smoking cessation and alcohol reduction in a large, at-risk population that was identified through an acute care hospital EHR.

METHODS

This 3-phase, mixed methods implementation study assessed the acceptability, feasibility, and reach of electronic signposting to behavior change apps by using a hospital's EHR system to identify patients who are at risk. Phase 1 explored the acceptability of the implementation strategy among the patients and staff through focus groups. Phase 2 investigated the feasibility of using the hospital EHR to identify patients with target risk behaviors and contact them via SMS text message, email, or patient portal. Phase 3 assessed the impact of SMS text messages sent to patients who were identified as smokers or risky drinkers, which signposted them to behavior change apps. The primary outcome was the proportion of participants who clicked on the embedded link in the SMS text message to access information about the apps. The acceptability of the SMS text messages among the patients who had received them was also explored in a web-based survey.

RESULTS

Our electronic signposting strategy-using SMS text messages to promote health behavior change apps to patients at risk-was found to be acceptable and feasible and had good reach. The hospital sent 1526 SMS text messages, signposting patients to either the National Health Service Smokefree or Drink Free Days apps. A total of 13.56% (207/1526) of the patients clicked on the embedded link to the apps, which exceeded our 5% a priori success criterion. Patients and staff contributed to the SMS text message content and delivery approach, which were perceived as acceptable before and after the delivery of the SMS text messages. The feasibility of the SMS text message format was determined and the target population was identified by mining the EHR.

CONCLUSIONS

The OptiMine study demonstrated the proof of concept for this novel implementation strategy, which used SMS text messages to signpost at-risk individuals to behavior change apps at scale. The level of reach exceeded our a priori success criterion in a non-help-seeking population of patients receiving unsolicited SMS text messages, disconnected from hospital visits.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/23669.

The current evidence for substance use disorder apps

PURPOSE OF REVIEW

New mHealth (smartphone) apps for substance use disorders (SUD) are emerging at an accelerated rate, with consumer choice typically guided by app-store user ratings rather than their effectiveness. The expansive reach, low-cost and accessibility of mHealth apps have driven their popularity and appeal as alternatives to traditional treatment; as such, rigorously establishing their effectiveness is of paramount importance.

RECENT FINDINGS

Several systematic reviews conclude that the evidence-base for mHealth SUD apps is weak, inconclusive and hampered by substantial heterogeneity in study designs. However, there have been a number of interesting and novel developments in this area in recent years, which have not been synthesised to date.

SUMMARY

Most mHealth apps deliver either multiple-component behaviour change techniques, discrete psychological interventions or cognitive training interventions, or are designed to act as adjuncts to facilitate the delivery of clinical or continuing care. There are promising signals of their feasibility, acceptability and preliminary effectiveness in numerous open-label pilot studies of mHealth apps targeting alcohol and smoking. However, only a handful of sufficiently-powered, well-designed randomised controlled trials have been conducted to date with mixed findings. Furthermore, there has been limited recent attention on mHealth apps aiming to improve outcomes for individuals using other drugs.

Smartphone Apps for Vaping Cessation: Quality Assessment and Content Analysis

Background

As the prevalence of electronic cigarette (e-cigarette) use, or vaping, continues to grow, particularly among young people, so does the need for research and interventions to address vaping.

Objective

This study examines the quality of free vaping cessation apps, their contents and features, popularity among users, and adherence to evidence-based principles.

Methods

A systematic search of existing apps for vaping cessation was conducted in December 2020. Eligible apps were free, in English, and included features specifically targeting vaping cessation. Each app included in the analysis was used daily for at least seven consecutive days, assessed using the Mobile App Rating Scale, and rated by at least two authors (AK, EL, or SS) based on adherence to evidence-based practices. Intraclass correlation coefficient (ICC) estimates were computed to assess interrater reliability (excellent agreement; ICC 0.92; 95% CI 0.78-0.98).

Results

A total of 8 apps were included in the quality assessment and content analysis: 3 were developed specifically for vaping cessation and 5 focused on smoking cessation while also claiming to address vaping cessation. The mean of app quality total scores was 3.66 out of 5. Existing vaping cessation apps employ similar approaches to smoking cessation apps. However, they are very low in number and have limited features developed specifically for vaping cessation.

Conclusions

Given the lack of vaping cessation interventions at a time when they are urgently needed, smartphone apps are potentially valuable tools. Therefore, it is recommended that these apps apply evidence-based practices and undergo rigorous evaluations that can assess their quality, contents and features, and popularity among users. Through this process, we can improve our understanding of how apps can be effective in helping users quit vaping.

Comparison of Healthcare Resource Utilization Between Patients Who Engaged or Did Not Engage With a Prescription Digital Therapeutic for Opioid Use Disorder

Background

A prescription digital therapeutic (PDT) (reSET-O^®) may expand access to behavioral treatment for patients with opioid use disorder (OUD) treated with buprenorphine, but long-term data on effectiveness are lacking.

Objective

To compare real-world healthcare resource utilization (HCRU) among patients who engaged with reSET-O and buprenorphine compared to similar patients in recovery treated with buprenorphine who did not fill their reSET-O script or engage with the PDT beyond week one.

Methods

A retrospective analysis of facility and clinical service claims data was conducted in adults with PDT initiation and between 12 weeks and 9 months of continuous enrollment in a health plan after initiation. Patients who filled their prescription and engaged with the therapeutic were compared to patients who filled the prescription but did not engage beyond week one (NE), and patients who did not fill the prescription (NR) (the latter two groups combined into one group hereafter referred to as “non-engagers”). Comparisons were analyzed using a repeated-measures negative binomial model of encounters/procedures, adjusted for number of days in each period. Associated cost trends assessed using current Medicare reimbursement rates.

Results

A total of 444 patients redeemed a prescription and engaged with the PDT (mean age 37.5 years, 63.1% female, 84% Medicaid), and 64 patients did not engage with the PDT (mean age 39.5 years, 32.8% female, 73.4% Medicaid). Total cost of hospital facility encounters was $2693 for engaged patients vs $6130 for non-engaged patients. Engaged patients had somewhat higher rates of certain clinician services. Total facility and clinician services costs for engaged vs non-engaged patients were $8733 vs $11,441, for a net cost savings over 9 months of $2708 per patient who engaged with reSET-O.

Conclusion

Patients who engaged with an OUD-specific PDT had a net cost reduction for inpatient and outpatient services of $2708 per patient over 9 months compared to patients who did not engage with the PDT, despite similar levels of buprenorphine adherence.