Digital medication adherence: which metric to use?
Therapeutic adherence is crucial to reach the desired clinical outcomes with drug treatments. The same reasons holds for digital therapeutics too. Indeed, how can someone benefit from a treatment which wasn’t delivered?
And this could also be a much more pressing topic to be addressed for DTx, considering it could be easier to take a pill rather than actively using DTx. For example, a real-world analysis of mental health apps usage highlighted a median 15-day retention of only 3.9% of users.
But how DTx adherence should be measured?
For traditional therapies compliance to prescriptions over time for each patient or defined daily doses (DDD) are considered. For digital therapeutics however it could be a bit more complicated.
Engagement with a digital tool can vary widely, quantitatively and qualitatively.
Completion rate (the proportion of enrolled/randomized study participants who remained in the study when the intervention ended) is often used to evaluate engagement. However, while this is an accessible metric reported in most studies, it may not properly represents user engagement. For example I can complete a video training or answer an assessment questionnaire without paying attention. Time spent using the DTx may seem a better indicator, however human-computer interaction studies have shown that it’s difficult to distinguish frustrating experiences with technology from positive ones based on duration of use, and that a person’s willingness to use that tool again is a more reliable indicator.
Thus, number of accesses, manual inputs or completed tasks/modules may measure engagement more meaningfully then a general completion rate or time spent alone.
In addition to behavioral metrics (such as the above mentioned examples), a range of methodological approaches have been employed to measure engagement, such as neurophysiological techniques (e.g. eye tracking) or patient-reported outcome measures (e.g. questionnaires, diary entries). While every approach has its pros and cons, outside of clinical studies only passive unintrusive measurement like behavioral metrics are likely to be used, in order to not increase patient’s required effort and preserve adherence/engagement.
Opportunities in the digital world
Heterogeneity and personalization
Another aspect to consider, at least for some metrics, is the heterogeneity of people approaches to digital tools. Thus, it could be worth paying attention to trends within each patient user metrics rather than relying on arbitrary cut-offs. This obviously has to be validated through studies but the amount of real-time data available unveil potential huge opportunities.
And unlike for traditional treatments, a suboptimal engagement may be discovered almost in real-time leading to corrective measures (which for examples may range from simple reminders to the replacement of DTx with a traditional medications for those patients who may not well-receive a particular digital treatment).
Flexible reimbursement systems
Due to the technological nature and potential ability to track software usage, even reimbursement strategies may evolve. Rather than paying per each treatment prescribed, a reimbursement strategy that considers active DTx usage may be chosen.
- Wu A, Scult MA, Barnes ED, et al. Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement. NPJ Digit Med. 2021;4(1):20.
- Torous J, Michalak EE, O’Brien HL. Digital Health and Engagement—Looking Behind the Measures and Methods. JAMA Netw Open. 2020;3(7):e2010918.
- Yan K, Balijepalli C, Druyts E. The Impact of Digital Therapeutics on Current Health Technology Assessment Frameworks. Front Digit Health. 2021;3:667016.
- O’Brien HL, Cairns P, Hall M. A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form. International Journal of Human-Computer Studies 2018;112:28-39.