#IXD303 – Digital Health for Patients, with Patients – Article Review

In creating his own disease management app, Weidberg conducted qualitative research through patient interviews to learn about people’s relationship with technology, and what barriers were keeping them from proactively managing their health. From these interviews, there are 5 key takeaways and how app design can address these barriers;

1. The Patient-provider dynamic is changing:

Today, individuals are empowered to take control of their health, and for the introduction of technology in this relationship to work, Weidberg highlights that; 1) patients must be willing to comply and commit to self-management and 2) patients must have trust in advice given by their doctor. Therefore, individuals who trust their doctors will be more likely to use an app if it has been recommended as a treatment plan by their doctor. Weinberg believes that an app should therefore complement rather than replace the patient-doctor relationship.

2. Healthcare is personal:

The article notes how patients’ needs vary, and therefore doctors collect and analyse patients’ medical data to create a treatment plan. Weidberg debates that for technology to add to this and to make it worthwhile for patients to use, data should be collected from various aspects of life, such as information about sleep, exercise and nutrition – alongside important life transitions and emotional wellbeing. Flo, a women’s health tracker, collects data on mood as well as lifestyle, for example – stress trackers are emphasised as particularly important for health apps, as stress is a major contributor in many chronic conditions, such as depression. This creates a more personalised approach for users and makes it easier for doctors to know more about their patient’s needs.

3. Patients don’t believe in ‘digital magic’ 

In the patient interviews, a main concern for patients was the accuracy of such apps and their wearable counterparts. Specifically, they expressed concerns with sensor accuracy and the analysis of data collected. This problem is further intensified by the fact that current health tracking devices on the market make finding this information difficult. For example, the Apple Watch does not communicate sensor accuracy to users. Therefore, Weidberg argues that digital health interactions need to be designed with transparency and clearly communicate with users to increase trust in the technology.

4. Tone of voice can make a big difference:

Empathy is also important in design. By keeping a positive tone when communicating with the user, Weidberg talks about how this could help patients feel more hopeful about outcomes. Prompts that are encouraging and promote positive behavior in users, such as “You’re doing great!” can make users feel acknowledged, improve their overall attitude toward managing their health, and also encourage adherence in sticking to their health management.

5. Patient satisfaction will be measured by time saved – not spent:

Finally, one of the key problems in digital healthcare is in getting patients to stick to and use the app. Weidberg explains that good design is essential for engagement and participation. Through the patient interviews, a common goal amongst them was they wanted to alleviate time spent ‘dealing’ with their illness. Users want tools that will save them time, and so as a designer, it is important to keep effectiveness and efficiency at the forefront.

To do this, Weidberg says about avoiding any design that may come across as ‘gimmicky’ or avoiding any language that appears like ‘marketing talk’, as these types of design will be perceived as a waste of time by users. Interactions need to be quick, frictionless, and non-disruptive to the user’s day. Passive trackers such as wearables are one of the best ways to achieve this; but, where this is not possible such as in mood trackers that need self-reported data, he recommends making data entry as simple as possible. This may be accomplished with the use of daily reminders that take minimal effort. Simple yes/no questions are used in MoodPath as an example.

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