Alan Menius

	I read with interest a recent article in MobiHealthNews that provides a perspective on HeartStrong, a randomized study of 1,500-plus patients that was published in JAMA Internal Medicine. HeartStrong studied the effectiveness of the combination of wireless technology, such as electronic pill bottles with reminders (Vitality Glowcap), and behavioral economic approaches, including financial incentives and social support, compared with usual care (a study arm with 500-plus patients), on the ability to delay subsequent vascular events in patients following acute myocardial infarction (AMI).

	Based on the primary study results, the study authors cast doubt on the ability to improve medication adherence or 

clinical outcomes using the compound intervention: there were no statistically significant differences between study arms in time to first rehospitalization for a vascular event or death, medication adherence, or total medical cost.

	These findings were the focus of the article, but when I delved deeper into the study results, I noted a couple of things. First, 12.5% of the intervention group did not activate their pill bottles. Second, I assume the authors must have surmised that these patients greatly impacted the study because a secondary analyses was performed in which these patients were omitted.

	But what happened when these participants were removed in the secondary analyses? The intervention group (those who engaged with the technology and recruited a feedback partner) had statistically significantly lower readmission rates, higher mean adherence rates, and lower mean annual medical spending.

	Therefore, I ask: If more of the intervention group had used the technology, would the group differences in adherence and other primary endpoints in the primary analyses have been significant?

	I believe that these observations raise a couple of other questions.

	How can we better engage patients for greater adherence rates? Perhaps if we took the time to understand the differences in characteristics between the adopters and nonadopters within the intervention group we might be able to identify patients who are the most difficult to engage. Then we could develop and evaluate different strategies to improve their medication adherence and, therefore, outcomes.

	What technology characteristics result in greater adherence? Perhaps it is not technology per se that affects adherence, but rather the specific technology. For the elderly, multiple prescriptions, multiple prescribing doctors, potential memory issues, and lack of support all challenge medication management. Technologies that simplify a patient’s medication schedule and alerts, help create a daily regimen and encourage interaction with the health-care community might have a better chance at successfully engaging patients. Instead, as used in the HeartStrong study, the Vitality Glowcap requires a separate pill bottle for each medication, which results in multiple electronic notifications and adds complexity to what are typically already complex health-care management situations for many elderly persons. We need to think about how to create engaging technologies rather than just creating technology for technology’s sake.

	My conclusion from the study results is that a simpler and more user-friendly technology might help reach nonadopters and further increase adherence levels of adopters. A new breed of pharmacy technology should address the underlying behavior around nonadherence, instead of nonadherence itself.

Alan Menius, MHS, is Chief Data Scientist at HAP Innovations. HAP Innovations is a consumer health technology company with a mission of making it easier for people to live healthy and independent lives.

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How can we better engage patients for greater adherence rates? 

Author | Alan Menius

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