Physicians, insurers, and health care organizations have long recognized that unhealthy behaviors, such as smoking and drinking, are the root cause of many illnesses. We also know that positive behavior change, whether stopping a bad behavior or starting a good one, can reduce morbidity and mortality.
However, the quest to improve behaviors at an individual and population level is stymied by lack of resources, provider training, and provider time21. Moreover, research suggests that longitudinal motivation is the most effective method to improve behavior, in contrast to the one-time office-based encounter that most physicians use22.
Mobile health technologies for remote patient monitoring (RPM) may overcome these resource and provider obstacles. We are working to moving from identifying populations within our structured electronic health data, as dictated by Stage 2 Meaningful Use criteria, to the “intervention” phase of MU323. Digital health presents a key opportunity for health systems to achieve the so-called “triple aim” (improving individual patient experience; improving population health; and reducing per capita cost of care).
A growing body of research suggests that well-designed mobile health interventions can reduce risky behaviors and increase health-promoting behaviors among a wide variety of patients24. Below, we outline the evidence behind three primary forms of mobile health (mHealth) for behavior change: text-messaging, apps, and wearables.
- Text Messaging
Because text message enabled phones are nearly universally prevalent and are the most broadly understood communication format, the largest body of research on mHealth-enabled behavior change is through text messaging25. Text messages have effectively promoted a variety of behavior changes, including an increased rate of smoking cessation26,27, increased highly active antiretroviral therapy (HAART) adherence 28, and improved diabetes self-management29.
Studies have repeatedly demonstrated that tailored, two-way text messaging is more acceptable and efficacious than unidirectional or universal messaging25. Despite messaging being the “oldest” of the mHealth mediums, most studies are limited in scope and insufficiently powered to measure efficacy30. More recent interventions fail to take full advantage of the medium (e.g. using unidirectional messages)
The second major category of mHealth for behavior change is the use of “apps,” or mobile platform applications. mHealth apps can leverage many mobile phone capabilities, including accelerometry, GPS, self-tracking, and Bluetooth communication. Despite a proliferation of behavior change mobile phone applications, a minority are currently based on evidence(31,32) and many are only available on iOS platforms, which excludes about two-thirds of American smart phones that are Android-based. Some pilot studies have suggested that mobile applications can monitor signs of depression [Ginger.io] and enhance adherence to medication regimes [unpublished data from Medisafe]. However, self-management mobile apps for more complex medical conditions such as chronic pain and asthma are currently too simplistic and lack medical professional involvement.
Increasing evidence suggests that gamification, applying game thinking and mechanics to engage and motivate users in non-game contexts, can increase end-user uptake of intervention and behavior management mobile apps and effect actual behavior change. Successful apps in this category that have increased patient participation and behavior change include disease specific monitoring36, medication administration adherence 33, depression symptoms management34. Other work suggests that gamification may be applied to clinical decision support interventions to encourage provider behavior changes35. Syandus is exploring this using treatment simulation software for conditions including Chronic Obstructive Pulmonary Disease (COPD) and Multiple Sclerosis. While these results appear promising, further research is needed to examine the impact of these challenging technologies.
- Social Sharing as a Tool for Patient Engagement
Utilizing social interaction is a key component of digital health patient engagement tools. Disease-specific digital communities have become exceedingly prevalent on social media sites (e.g., PatientsLikeMe), with many volunteering their clinical data with others. This sharing often leads to support and advice from those with similar conditions. Studies of Facebook pages that have incorporated an uploaded photo have been shown to draw 104% more user’s comments. However, digital health management social interactions are complex. While sharing of fitness data could be very motivational for some, the Pricewaterhouse Coopers Health Research Institute report from this year found that 43% of consumers did not want to share any information about themselves, and only 23% felt comfortable sharing health data with friends and family37. For text messaging services, apps, and wearable technologies to be accepted by the majority healthcare consumers, social interaction features that motivate some must be balanced with maintaining data privacy desired by others.
- Integration of Wearable RPM Into Behavior Change
Increasingly, RPM is being incorporated into mobile interventions. For instance, a recent study by emergency physicians demonstrated that using “wearables” can detect patients’ use of opioids and cocaine in real-time.38 A possible future research opportunity could be to deliver targeted behavior change interventions when a relapse is identified. Ongoing studies are examining other RPM applications to decrease or prevent (through advanced predictive analytics) other types of high-risk behaviors and enable intelligent interventions by clinicians and other caregivers. Others are investigating RPM to increase health-centric behaviors, such as functional recovery from illnesses.39