Behavioral Change for Digital Health Technologies

Digital health technologies have rapidly penetrated many aspects of consumers’ interactions with health care organizations, including how they make health care decisions and interact with their health plan. Below we will briefly introduce the final two topics of discussion for 2020: 1) digital health adoption and behavioral change, and 2) the inequality of digital health adoption. Both topics will be discussed in greater detail over the next couple of weeks.

In the Deloitte 2020 Survey of US Health Care Consumers, more than 60% of baby boomers said their use of digital health technologies led to a great or a moderate deal of behavior change. Additionally, more baby boomers expressed interest in using technology to access care, such as medication reminders and monitoring sensors and devices compared to previous years. The report also found that a growing number of consumers are using technology to monitor their health, measure fitness, and order prescription-drug refills. After a slight decline in willingness to share data before COVID-19, new data shows that consumers are more comfortable sharing data during a crisis. 

Despite the advances in virtual care brought on by COVID-19, providers still have a long way to go to meet consumer expectations and preferences. Problems of low intervention use, high drop-out rates, and low efficacy continue to pose difficulties.

Digital Health Adoption Requires Behavioral Change

One of the most challenging questions health care professionals deal with is how to change a patient’s behavior for the better to improve outcomes and reduce costs? Resistance to change is natural. And although patients may recognize they need to lose weight to prevent another heart attack or eat correctly to manage diabetes, few succeed in doing so.

With so much information and technologies out there, it is not easy to build interventions or technologies easily adapted and effectively used to change lives. Behavioral science has barely scratched the surface of health care. The next decade will see health care begin to embrace behavioral science findings and methodologies, moving beyond the one-size-fits-all transactional delivery of care. 

Behavior change techniques such as goal setting, feedback, rewards, and social factors are often included in fitness technology. However, it is not clear which components are most effective and being used by consumers. User-centered approaches to digital health intervention design can facilitate engagement with interventions for potential health benefits. In other words, designing technology that can meet the customer wherever they are–and in a way that they prefer–can be a key to behavior change.

The Inequality of Adoption

Adopting digital health technologies has not been equal for all Americans, with more significant adoption for those with higher incomes. Households with annual family incomes of $100,000 or more were much more likely to use the Internet to interact with health professionals, access health records, research health information, and use electronic health monitoring services compared to those with annual family incomes less than $25,000 (see Figure 3). Hispanic and American Indian/Alaska Native Households Experienced Greatest Growth in Online Health-related Activities. Comparing the rates of telehealth usage among different racial or ethnic groups showed substantial growth for Hispanic and American Indian/Alaska Native households from 2017 to 2019 (see Figure 5). 

The Five Year Outlook on Digital Health and Behavioral Change

Over the next few years, we will most likely see more academic-industry partnerships and novel funding schemes for research aimed at advancing scientific knowledge. New funding structures and business models will encourage sustainable alliances and focus on delivering practical and equitable digital behavior change interventions. As digital tools become increasingly crucial to discriminating consumers, tools for the digital patient journey will become a core and increasingly important differentiator between providers of choice and those left behind.