Five classic mistakes in digital healthcare

Mantas Cerniauskas
Classic healthcare mistakes

Digital healthcare has huge potential but only if we get it right and make it easy for doctors, administrators and patients to adopt it.

And while there have been hundreds, if not thousands, of digital health initiatives, not all have been successful. We won’t deliver on the promise of digital health unless we talk to users and gatekeepers about what they actually need.

Ideas for digital tools can come from multiple sources, doctors, patient groups as well as pharma companies but, regardless of ownership models, many fail to invest at the development stage in the consumer insight that will enable them to succeed.

Our experience of working with multiple pharma companies and projects in this area allows us to identify five classic mistakes.

1. Lack of a clear and distinct purpose

Most areas of health are already covered by some kind of symptom tracking digital tool, so what makes yours different and more useful, either at a patient or doctor level? If you are thinking of building a pain tracker app, for example, ask yourself how it can be more effective and useful than the 30 plus that are already available for free on the app store.

2. The tool isn’t integrated or can’t be scaled

For many digital health tools to reach their maximum value, they need to be integrated into electronic medical records (EMR), however there is a lot of variety in the EMR systems within countries, let alone across countries. Ensuring that if a link to EMR is needed, that your tool works across the main providers is essential.

And just as we only have so much screen space on our mobile phones, healthcare providers can only cope with a certain number of apps/ digital health tools. Making it easy for hospital IT Managers to integrate your range of tools can be very valuable when it comes to gaining traction.

For example, if they only have to onboard and integrate one platform to access to lots of tools across therapy areas, this is seen as a big positive. One brand that has managed this well is Roche Diagnostics’ Navify Algorithm Suite, which provides a single platform that can host lots of different AI/ algorithm based digital health tools.

3. The tool doesn't provide a clear benefit for the user

Without a clear benefit, people often jump onboard quickly to try a tool out (especially if it sounds innovative/ interesting), but then rapidly give up if they don’t gain value from using it within the first few weeks. For example, digital symptom trackers can be very useful but we also know that compliance with these tools drops for many patients after the first few weeks of use, as they often do not see any direct benefits. For most patients the symptom data is discussed with their doctor at best every three months so there’s little reward on a day-to-day basis. Gamification, as used on consumer apps such as Strava, which offers badges and prizes, could provide some kind of incentive to keep it up.

If the tool simply tracks a condition but doesn’t trigger doctors to adjust treatments and improve outcomes then it’s not providing an answer, it’s just gathering data and causing anxiety. Wired recently ran a story about why symptom tracking alone often makes people feel worse..

If a tool helps identify people for a potential diagnosis (e.g. ranking people by risk of developing a condition), or treatment, but the healthcare system doesn’t have a pathway to act on the information, then the tool doesn’t offer value.

The key to avoiding this mistake is to identify the unmet need/challenge that requires a solution and then design tools ‘with’ your planned end user and not ‘for’ them.

4. Not considering the long term value of the tool for the users

We often see clients mapping out patient journeys to identify ‘problem statements’ that digital health tools could solve. However, this process often ends early and doesn’t look for the challenges of living with the chronic condition in the long term. As a result, the tools developed are only relevant to people while they are in the early stages of diagnosis and first treatment decisions, so are only used for this relatively short period of time.

5. Creating tools that aren't easy to use 

We see this in other consumer technology too but testing for ease of use should be an integral part of the development process for digital health tools. BeCare MS Link is a great example of a well set-up symptom tracker that links results to the patient’s doctor and is well validated. Where it falls down, like so many others, is that patients still have to manually enter the data or complete tasks, which takes too much effort. The ideal in the MS space is sensors in shoes, or the use of data from smart watches etc to track changes in patients’ motion/ mobility, speech and vision.

Digital healthcare will transform healthcare as it becomes part of the mainstream delivery of health. Many tools will be created to join this evolution, but only those that are both useful and easy to use will succeed.

That means better understanding of the exact problem/ need the tool will solve, how stakeholders use them, what they expect to get from them and how they are going to integrate into the health system are all essential for success.

If you haven’t answered these questions as part of the development process then you are likely to fail.