Wearables: This Season’s Must-Have Marketing Accessory
Medical devices are generating real-world data on patient populations. Are marketers making the most of this opportunity?
Thanks to the exploding consumer wearables market we’ve become Fitbit-obsessed data bores, tweeting our latest 5K PBs, Instagraming our Strava cycling stats or Facebooking our lucky friends with a daily log of steps taken.
The data from the fast-growing medical wearables market may be less visible but they are starting to tell some rather more interesting stories of better health and longer lives.
Conditions that are yielding compelling data stories thanks to wearables include diabetes and hypertension. Enough data has now been gathered, for example, to start seeing the real-world efficacy of continuous glucose monitors (CGM) and their manufactures are now successfully using the stories the data tells to convince payers, healthcare providers and end users of their worth.
In June, CGM maker Abbott released a meta-analysis from its four-year old FreeStyle Libre system that showed a meaningful decrease in HbA1c in a broad population of people with type 1 and type 2 diabetes compared with conventional finger prick methods. Additionally, real-world evidence from more than 250,000 users showed decreases in glucose variability and improved glucose control for those checking their glucose often.
The data also revealed how users are interacting with their devices, further confirming their usefulness. Using the finger pricking method users typically tested less than three times per day, but this increased among users of the Libre, averaging 13 times per day. Higher frequency scanners spent significantly less time in hypoglycemia during the day compared to lower frequency scanners.
The result is reduced instances of hypo- or hyperglycemia, says Timothy Dunn, Director of Clinical Care and Computational Research. “The clinical monitoring recommendations per day were four to eight times for people using insulin but we knew from the research that vast majority did not meet those criteria. We thought it would be a great success if people scanned 10 times a day.
“Payers rightfully question whether trials are broadly applicable, and the trial data lined up well with the real-world evidence that emerged. The data offers a robust confirmation of the efficacy of the device to providers, payers and patients.”
The results of the study are helping drive sales, contributing to stronger adoption rates from health services and payers in the UK, France, Japan, Australia and the US, says Dunn.
Blood pressure device data offers another good early example of the potential of connected health devices to offer a convincing story of efficacy and more besides. The role of blood pressure devices in helping control hypertension, for example, is now evident from the data they have generated, says Nicolas Schmidt, Head of Healthcare Products at Withings, formerly Nokia Digital Health business (which the Finnish tech firm sold back to its co-founder in May this year).
“Digital disease management programs control rates [for hypertension] are much better than in traditional care settings,” says Schmidt. “The impact is huge. We see a 70% control rate in three months compared with the standard in-person health care figure of around 30%. We also see increased convenience and satisfaction for patients as they don't have to take time off.”
The data are also offering clinicians new insights. Withings has already published studies of blood pressure and its variability over time in the American Journal of Hypertension, says Schmidt. “We have started to generate more knowledge around blood pressure data because we get more data than before.
“Take your blood pressure a few times a week and we can start showing you new indicators.
Devices that monitor activity levels, sleep and weight are the other big ones generating new types of knowledge.”
With wearable medical devices sales expected to exceed $55 billion in 2022, from $10.5 billion in 2017, according to ABI research, the potential to gather even deeper insights will only grow. Pharma and device makers are barely scratching the surface, today.
The potential to understand patients’ conditions in real time and to create new types of biomarker from such data is vast, says Schmidt. “It is extremely valuable, probably one of the most impactful changes we will see in the healthcare system because you are adding data on people all the time. At the moment it is captured between 0% and 1% of time when you are meeting your doctor or clinician. Now there is the opportunity to gather data the rest of that 99% of the time.
“We can use aggregated data sets we never had before to see how this can inform clinical research and help us understand the real-world behaviors of patients outside the lab in their tens of thousands.”
The era of digital therapeutics offers great potential, in which data is gathered and the resulting insights are tailored to a specific user and a specific condition thus improving medication efficacy, symptom management, and reducing rehospitalization or ER visits.
Although it is not yet here, the marketplace for it is evolving fast, says Schmidt. At the group or community health level some patient-generated data is now being shared with healthcare providers to improve healthcare efficacy.
Some healthcare providers are already trialing technology bars modelled on those in Apple stores, offering various connected devices for sale and offering to help to set them up. And it is now possible to connect some of them directly to electronic health records, adds Schmidt.
“The data will go into my hospital electronic health records where coordinators can see if there are any concerns, help me with lifestyle issues, and set up health alerts. At the moment you need a coach for every 80-100 patients but as we generate more data I expect this ratio will increase a lot as we will be able to scale these programs.
It will become fairly common with conditions like hypertension that are easy to treat but which affect a third of the US population. Instead of seeing your doctor every three months, your health will be monitored pretty much every week.”
Further out but looming into view is the transformative impact of years’ worth of data from wearables that will offer even deeper insights and the potential to complement or replace some drugs through better management of a condition.
This poses the question of how this will disrupt existing commercial arrangements, says Schmidt. “Will the insurer pay then for prevention as well as cure? Maybe there is a good business model for pharma to invent thanks to the power of digital therapeutics to avoiding re-admissions for example. If I can create savings I should gain back.”
The barriers that device makers and pharma need to overcome to make the most of wearable’s potential are considerable, however. Pairing other data with those generated from wearables has great potential to deliver deep insights but is much harder to do.
Helping people with diabetes manage their conditions even more effectively still requires diverse and reliable data, for example. “Freestyle Libre gives us is high quality glucose data, so we have made a big step forward there,” says Dunn. “Where we need really high-quality data is around insulin, food and exercise. We have some of that in log book format but is that high quality enough?”
The need to use de-identified data sets presents a further challenge in winnowing finer grained insights from the data, for example the differences between type 1 and type 2 diabetics, says Dunn. “We don't know about individual patients. There are lots of sub groups we have yet to investigate but there are paths forward, but the questions we are interested in take time to answer.”
Another challenge is that the technology is in many cases advancing faster than the regulation or pharma’s ability to evaluate it, says Dr Jeannie Joughin, Executive Vice President and Chief Commercial Officer at Enable Injections, which develops and manufactures on-body delivery devices.
Enable has developed the Smart enFuse Bluetooth sensor that can log and broadcast when drug delivery begins and ends, driving adherence and offering pharma partners the ability to integrate this information with a data platform to gain access to de-identified patient data across multiple devices. “That is a really powerful use of this data. Physicians will know if patients are not taking a drug and will be able to find out why,” says Joughin.
The path to its deployment is likely to be a long one however, she says. “We don't know anyone that has an approved ecosystem that is ready to put Smart enFuse into trials yet. Meanwhile regulators are still trying to define their guidelines.”
Schmidt agrees. Pharma’s relative lack of direct patient contact outside of clinical trials is a further impediment to progress, which will mean they will need to learn how to find the right partners used to developing consumer friendly devices and user experiences. “I don't see pharma creating digital therapeutics departments in the next three to five years.”
While the industry slowly puts the required infrastructure in place to make better sense of all the data, a more immediate but so far largely unrealized commercial application of wearables lies in their use in clinical trials recruitment, says Schmidt. “As it is so costly to find and recruit for clinical trials, wearables give you a link with the patient. The data can help you target some specific patients and enroll them in trials.”