Drop Out Rates for Apps- The Right Metric to Track?

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A recent annual report from Liftoff cites a 3.6% 30-day retention rate in health and fitness apps and suggests app companies are more focused on acquiring new users over retaining the current ones. Will this work for digital therapeutics? Surely a successful company will have multiple foci if it wants to stay in business.,  Health care systems will want to see usage beyond 30 days if they are going to be making investments. Most chronic conditions require a lifetime of phased support.  How will companies differentiate themselves on their products with such high dropout rates? They will need to be a different caliber of the product.

A new paper from Dr. John Torous and colleagues and Harvard published in the Journal of Affective Disorders examines dropout rates in the context of mental health app-related clinical trials. The authors conducted a systematic review of clinical trials that yielded 18 independent studies with a total number of participants of 3,336 who were either randomized to smartphone interventions for depression or a control group. Retention rates in the studies did not differ between control or intervention groups, and the authors report a pooled drop out rate of 26.2%. When adjustments for publication bias were made, this dropout rate jumped to 47.8%.

New opportunities exist to better match a consumer with an intervention; those who experience a warm handoff from a therapist or clinician experience better outcomes and less drop out rates. It would seem new models of care are worth developing to better calibrate a mixture of human touchpoints with digital supports. The scale and reach of these tools can, in theory, support more people in healing, but this can only happen when systematized approaches are modeled and tested. We have reached a point in digital therapeutics evolution that demonstrates digital cognitive behavioral therapy as an evidence-based approach. The next steps are to ensure these new tools are embedded into standard care, so scale and reach can be realized. We must also expand our definition of drop out to view different arcs of engagement- one size does not fit all in digital health- we need to develop thresholds of demonstrable benefit where constant change can be shown. Drop-out is useful but no sufficient to examine in the context of digital health.


Thanks for reading – Trina
(Opinions are my own).



Liftoff Mobile App Trends 2019

Dropout rates in clinical trials

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