by MarksMan Healthcare | 0 Comments Real World Evidence , RWE , Wearables
The health and fitness wearable market is on the rise since the last few years. Analysts expect that by 2020, almost half a billion smart wearable devices will have been sold. However, despite the fast-growing market, only 10% of those consumers are using the product daily. This is an opportunity for innovative life science companies to tap into the market and create value-added services for consumers. Demand for wearables which include wristbands, smart garments, chest straps, sports watches and other health monitors is being driven by consumer fascination in quantifying personal health metrics, but it also opens up a world of opportunities to the wider healthcare and pharmaceutical industries. Pharma wants to take wearables beyond fitness trackers to add value through disease diagnosis and monitoring solutions in the form of medical-grade wearables, while also generating evidence in the form of real-world data.
In line with the evolution of patient-centricity, wearables have enabled us to become personal data creators, with constant streams of fitness and medical information being generated of our own volition. The question is can this be harnessed by the healthcare industry to drive efficiencies and enhance products and healthcare services in the long term? Apple thinks so. It launched the Apple CareKit this year: software that makes it easier for individuals to keep track of care plans and monitor symptoms and medication, with the ability to share that information with doctors or family. It delivers the promise of empowering the patient and personalizing their care patient centricity at its very best. Apple also offers a ResearchKit, providing a software framework for apps that enables medical researchers to gather robust and meaningful data. Interestingly in July 2016, GlaxoSmithKline launched a rheumatoid arthritis study, called PARADE, and an iPhone app using Apple’s ResearchKit, demonstrating the first time a drug maker has used the open source software framework to conduct clinical research.
Wearables are being put to use wherever we look, including in the NHS, which has endorsed wearable use in its own trials. In partnership with Diabetes UK and Hewlett Packard it is deploying mobile health self-management tools (wearable sensors and software) for people with Type 1 and Type 2 diabetes to self-manage their condition. The devices feed data back via the internet to allow more timely intervention from peers, healthcare professionals, carers and social networks, should their help be required.
Evidence to date suggests that wearable technology is plugging a gap in our knowledge by way of collecting real-world data directly from patients. Hospitals are deploying wireless monitoring so that patient’s vital signs are automatically and continuously fed back to clinicians. Furthermore, sensors are now available that automatically measure and store glucose readings removing the need for finger pricking. But can it really help us as market researchers to better understand the patient journey- is the question.
Results from a recent survey of HCPs and pharma professionals, which was presented at the BHBIA Conference (May 2016), shows that an already quite apparent use of wearable devices especially amongst HCPs. Two thirds currently make use of biometric data for personal reasons outside of work, which is found to be surprisingly high. But when the use of standard health applications on mobile devices is factored in, this may help to explain things. Over 40% of HCPs use biometric data for work-related purposes, but this is much lower for pharma. Again this seems high, but perhaps this supports increasing examples of patients bringing in their data on their devices to help inform consultations.
The question is how pharma can generate evidence from wearables? Biometrics collected from wearables could potentially offer an exciting future for qualitative research – to determine what is actually happening instead of what patients tell us is happening. For example, while carrying out a qualitative interview with a patient and discussing mobility, data from their wearable device could help verify whether the patient has been as mobile as they say they have been. From a quantitative perspective, biometric data from wearables could feed into online segmentation studies. For example, does segment A exhibit a higher heart rate and greater sleep disturbance? In this instance biometric data could be collected to help facilitate the analysis process and test additional hypothesis that at present are very difficult to test. And of course, there is the potential for biometric data to be collected alongside our on-going tracking studies – to monitor how important metrics are changing over time and to identify periods in the day/ week/ month where patients exhibit peaks and troughs.
It seems the application for data derived from wearables has increasingly more value in the healthcare research process as the technology improves and becomes more reliable. Their potential lies in their inconspicuousness – we forget we’re wearing them, and they provide access to an un-simulated world of responses to everyday events to either back up or refute what we think we know already.
There could be a very bright future for wearables at the centre of healthcare research, but there are many issues to address first. The accuracy of the data from wearables must be assessed. Not to mention the issues surrounding use; at the very least does the patient own a device and have they worn it at all times without tampering or hindrance? There are ethical issues around the data, gaining approval and ownership of the information generated. And of course, if there’s a problem in the data, should it be reported or not? There are still many unanswered questions.
Wearables are unlikely to ever entirely supersede traditional market research, but it’s clear their use for wider healthcare research purposes is on the increase. They currently provide a valuable tool to use in conjunction with more traditional methods of research by offering context, putting clinical data into a more relevant light and further personalizing the patient journey. Could the collection of biometric data provide researchers with a new, previously inaccessible, form of insight that may help in further understanding the patient experience? Only time will tell.
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