Insights
How to Design Digital Health Companions for Engagement
digital health companions

Chronic conditions and comprehensive treatment programs place substantial pressure on patients to keep track of their symptoms, medications and healthy behaviors. Clinical guidelines put an emphasis on self-management as one of the most important pillars associated with improved health outcomes. Internet and mobile technologies could be an excellent vehicle for engaging people and motivating them to change behavior. (1) However, tracking can become a daunting and burdensome task and people will eventually disengage. More than half of those who download a health app stop using it, primarily due to high data entry burden and loss of interest. (2)

Applying human-centered design principles, involving patients and clinicians in the process of co-design, using evidence-based behavior change methods and techniques, and designing comprehensive engagement strategies can allow us not only to design effective self-management tools, but also to provide empowerment and support to patients and ensure long-term use and benefit. 

Interactive and comprehensive experiences with a Digital Health Companion have the potential to address unmet patient needs, educate patients about their condition, enhance patients success with a given therapy, enable access to medication, facilitate meaningful patient-clinician communication, empower patient to be more involved in managing their health, and win patient loyalty over time. The results could include increased medication adherence, better value of the therapy overall, improved health outcomes and quality of life for patients with diabetes mellitus, chronic lung disease, cardiovascular disease, autoimmune disease, cancer, hormonal disorders, and mental health disorders. (3,4,5,6,7,8,9,10) 

Mad*Pow Workshop

Design Considerations

Given our experience with the design and development of these digital experiences, we recognize that successful Digital Companions will include:

Collaboration and Co-Design with Patients/Clinicians

Working with patients and clinicians throughout the process will help us validate our assumptions and design a solution that addresses unmet needs. Additionally, these contacts will help build credibility and overall relationships with clinicians or patient advocacy groups. (11,12)

Evidence and Behavior Change Research

Every good behavior change intervention starts with research because we need to understand behaviors in context in order to identify the types of interventions and behavior change techniques likely to be effective. Our goal is to identify what is causing the problem, what, if anything, needs to be changed and can be, and for whom. Ultimately, we want to create a holistic behavior change intervention targeting root causes of the problems using evidence-based techniques.(13)

Easy Data Tracking

Tracking as much information as possible with limited effort will help make the experience less of a burden. Passive/effortless tracking should be utilized as much as possible, and manual tracking and surveys should be as simple as possible.

Personalized Feedback

Patients are more engaged with the experience if it speaks to their specific context, behaviors, priorities and values. For example, coaching and tips based on results of their specific activity will be more appealing. (14)

Friendly, Conversational, Modern Tone and Design

An attractive and well-executed design won’t just impress patients; it will make them forget the clinical nature of the Digital Companion and encourage them to use it regularly as a companion for their health, rather than a reminder of their illness.

Local Tone and Content Development

Understanding and accounting for the variations of audience expectations and values in different countries from the start will help build a solution that allows for flexibility per market, yet retains the core essence of the features and functionality.

Meaningful Support of Patient/Provider Communication

By answering unmet patient needs between visits, augmenting patient/provider dialog around condition, and informing clinicians with relevant summary information, the experience will maximize the value of clinical interactions.

Long Term Engagement and Re-Engagement Strategies

Planning for changing usage patterns, appropriate cadence of messaging, and content needs over time will raise retention and ensure optimal usage.

Mad*Pow Behavior Change Methodology
Mad*Pow Behavior Change Methodology

Where to Start?

Build an Understanding of the Problem Space

What is causing the problem? What, if anything, needs to be changed? For whom? Your activities may include, but not be limited to, one-on-one interviews, focus groups, evidence-based literature review, client & public dataset analysis, ethnographic studies, problem definition & context framing, identifying gaps & opportunities, COM-B analysis, current state journey mapping, or creation of Logic Model of Problem.

Establish Business and Health Outcome Goals

What business objectives do you aim to achieve? What health outcomes do you aim to improve? How do you expect your solution to work? What is the logic behind it? Your activities might include, but not be limited, to patient and stakeholder workshops, defining outcome measurements, developing Logic Model of Change, ideal state journey mapping, or designing an intervention strategy. Involve patients and stakeholders in the co-design process. What is the priority audience for your patients? What are their unmet needs? Are there any solutions that are already trying to address these needs? What works and doesn’t work about them? Who are your key stakeholders? What is your value proposition for the stakeholders? Your activities might include, but not be limited to, patient and stakeholder co-design workshops, more qualitative research with patients and stakeholders, co-designing program strategy, co-designing concepts generation and ideation, desirability and usability testing with patients.

Design the Evaluation and Measurement Plan

How will you measure that the program was implemented as intended? What would be your indicators and measures for process evaluation? What will success of the program mean? How will you measure that the program worked and achieved the business goals and improved the health outcomes? What would be your indicators and measures for impact evaluation? Could you design a pilot project to test the program? What would be the hypotheses that need to be tested? Your activities might include, but not be limited to writing the process and impact questions, developing the process and impact indicators, identifying the most optimal pilot project design.

References:

1. Sawesi, Suhila, et al. "The impact of information technology on patient engagement and health behavior change: a systematic review of the literature." JMIR medical informatics 4.1 (2016). 2. Krebs, Paul, and Dustin T. Duncan. "Health app use among US mobile phone owners: a national survey." JMIR mHealth and uHealth 3.4 (2015). 3. Chen, Fang, et al. "Clinical and Economic Impact of a Digital, Remotely-Delivered Intensive Behavioral Counseling Program on Medicare Beneficiaries at Risk for Diabetes and Cardiovascular Disease." PloS one 11.10 (2016): e0163627. 4. Heldenbrand, Seth, et al. "Assessment of medication adherence app features, functionality, and health literacy level and the creation of a searchable Web-based adherence app resource for health care professionals and patients." Journal of the American Pharmacists Association 56.3 (2016): 293-302. 5. Kessel, Kerstin A., et al. "Mobile apps in oncology: a survey on health care professionals’ attitude toward telemedicine, mHealth, and oncological apps." Journal of medical Internet research 18.11 (2016). 6. Tinschert, Peter, et al. "The Potential of Mobile Apps for Improving Asthma Self-Management: A Review of Publicly Available and Well-Adopted Asthma Apps." JMIR mHealth and uHealth 5.8 (2017). 7. McCabe, Catherine, Margaret McCann, and Anne Marie Brady. "Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease." The Cochrane Library (2014). 8. The Alexa Diabetes Challenge http://www.alexadiabeteschallenge.com/ (2017). 9. Laranjo, Liliana, et al. "mHealth technologies for chronic disease prevention and management." (2015). 10. Whitehead, Lisa, and Philippa Seaton. "The effectiveness of self-management mobile phone and tablet apps in long-term condition management: a systematic review." Journal of medical Internet research 18.5 (2016). 11. Nicholas, Jennifer, et al. "The Reviews Are in: A Qualitative Content Analysis of Consumer Perspectives on Apps for Bipolar Disorder." Journal of medical Internet research 19.4 (2017). 12. Arnhold, Madlen, Mandy Quade, and Wilhelm Kirch. "Mobile applications for diabetics: a systematic review and expert-based usability evaluation considering the special requirements of diabetes patients age 50 years or older." Journal of medical Internet research 16.4 (2014). 13. Michie, Susan, et al. "The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions." Annals of behavioral medicine 46.1 (2013): 81-95. 14. Morrison, Leanne, et al. "Optimizing engagement with internet-based health behaviour change interventions: Comparison of self-assessment with and without tailored feedback using a mixed methods approach." British journal of health psychology 19.4 (2014): 839-855.

Contributed by
Name
Olga Elizarova
Job Title
Behavior Change Director