One of the first validation studies we completed at Partners HealthCare Pivot Labs was on a mobile application for diabetes patients, who would receive text message alerts reminding them to get up and move or take their medication. But the data kept showing something bizarre for one patient in particular—he was receiving his “Add some steps to your day during your commute back home!” messages nearly every day at 4 am. After we apologized for this experience at his next appointment, he looked puzzled and asked, “Why?” We explained that there must have been a bug in the algorithm and hoped he wasn’t losing too much sleep. But he just laughed and said,
“Well, I work the night shift.”
The potential of digital technology to hyper-personalize and learn the minutiae of patient’s daily lives is incredible. Harnessing this power unveils unbelievable opportunity to engage patients with these digital platforms in a seamless way that integrates with their daily lives. Artificial intelligence has a virtually unlimited capacity to uncover details that might take doctors 20 visits to learn, while simultaneously getting smarter and tailoring these platforms to personal patient routines and behaviors (think: “Netflixing” digital healthcare).
However, patient engagement is not without its myriad of challenges.
Another validation study we conducted was on a mobile application our team designed for patients with atrial fibrillation (AF), primarily to support medication adherence. Providers didn’t support the idea of the incorporating an app feature that used the camera sensor on patients’ smartphones to capture their heart rates. Clinically, there was no way to determine whether or not this was an episode of anxiety or actual atrial fibrillation. What we learned directly from patients is that most AF patients were using other apps to track their heart rate. Including the heart rate monitoring feature in the patient-facing app would help keep them engaged and actively using our solution, which also provided medication reminders and adherence tracking that were valuable to both parties.
After understanding this behavior, we concluded this was an essential feature to initiate patients’ use of the app, which then guided self-care management and medication adherence. Simultaneously, we worked around the doctors’ apprehension of patients’ self-reported irregular heart rates by not including these data in the reports that doctors received.
Ultimately, patient engagement is about figuring out the best ways that people will engage with applications to reach the end-goal of engaging with their health. Even if
not every app feature has direct clinical value, it can still serve as a significant motivator for getting people more involved in their care.
Siloed Healthcare and the Power of Digital to Move Beyond
With the market flooded with countless digital health apps, we run the risk of following medicine down the rabbit hole of siloed care; imagine, for example, a 63-year-patient with a history of depression and COPD just beginning his treatment for prostate cancer. Do we expect him to log into 4 different mobile applications daily? What happens when his pulmonologist sees a drop-off on patient-entered information from her end of the portal, without knowing his new diagnosis?
This is the fine line we walk in the digital health sphere, where amassing volumes of data can quickly become information inundation. Considering our patient also has three small grandchildren, still works in construction management, and refinishes furniture on the weekends, the question of how much responsibility we are placing on patients themselves to do more, log more, engage more, becomes even more critical.
While traditional American care systems are highly specialized and granular, digital solutions are positioned to take on a people-centered approach rather than a system-centered one. It is critical for digital technology to avoid the pitfalls of narrow specialization that has created issues like transitions of care, information gaps, and EMR compatibility that we are seeing currently in the medical system. The ultimate challenge lies in designing applications that are engaging by integrating into people’s lives and allowing for the care of the whole person.
Design: Shifting from Minimum Viable Product to Minimum Effective Product
The question we should be asking when designing digital health solutions is not whether our product is minimally viable, but whether it is minimally effective. Too often, while following the consumer tech industry, designers and developers start by building a minimum viable product (MVP). MVP strategies prioritize releasing the first version of a product, which contains just one or two complete features sufficient enough to prove business viability. Developers then start incrementally building subsequent versions with additional features. While this approach has been successful in consumer tech, it may not be a feasible or even an appropriate strategy for healthcare; in the field of medicine, the effectiveness of the product in achieving better patient outcomes is the most relevant factor in determining long-term product success.
Focusing on product effectiveness rather than viability requires User Experience Strategists and Designers to deeply understand and design for improved outcomes such as quality of life, self-care management, clinical/health outcomes, reduced emergency visits, or fewer missed appointments. With a deeper understanding of these outcomes, the first versions of these products need to include a minimum set of built-out features necessary for showing effectiveness and ability of the product to achieve these outcomes. Ultimately, instead of proving market viability, a Minimum Effective Product strategy seeks to prove patients’ engagement with their own health and the personal and system-wide benefits that accompany it.
The goal of digital health applications should not be to flood patients with a feature for every facet of their disease management, but to design a product with the minimum features needed to affect change. Developing good quality tools comes from iterative design process that ensures effectiveness during every step. The ultimate goal of these solutions should be to build interventions that improve patient health outcomes first and foremost, that can be refined and scaled while keeping patient engagement simple and streamlined.