By Matt Gross

If a ride-sharing app can detect when a passenger is having a heart attack, should that app be allowed to notify clinical staff?  That scenario was among the challenging digital health topics tackled at a recent HTB Boston event by experts from Boston Scientific, Medtronic, Analytics 4 Life, and Outcome Capital.

While digital technologies are starting to make a significant impact in many sectors of healthcare, market data indicates that we’re still in the earliest days with a steep growth curve ahead (source: Outcome Capital).

That growth will occur across a variety of healthcare sectors.

From the viewpoint of David Feygin of Boston Scientific, digitization will come first to areas with significant data flows or where there are frictions that need to be addressed.  Examples include the digitized capture of medical imaging with AI, telehealth, clinical trials, and population health.

For Geoff Dacosta of Medtronic, the surgical division is his area of focus for digital change.  Many companies are starting to digitize surgery from robotics to machine learning. One of the fundamental challenges is distilling actual surgery into bytes and voxels and compressing actions into a format that’s accessible to machines for the development of surgical algorithms.  Once digitized, surgery data can be supplemented by biologic and genetic data. Another area of surgical practice with great potential to benefit from digital technologies is post-operative recovery. New post-operative algorithms for regimen and prescriptions can be personalized to target treatment to an individual patient’s specific surgery.

Regulatory implications

Kristine Canavan of Analytics 4 Life noted that digital companies still face the same constraints as traditional medical device manufacturers.  It’s crucial early on to define the requirements for the commercial process including regulatory documentation and clinical trials. Extensive background work is required of companies for regulatory submissions, regardless of whether that company is a small startup or deep pocketed medical device companies.  Throughout this process, it’s important to understand the cybersecurity requirements for protecting the systems and patient data.

The regulatory bodies are trying to keep up with how to adapt their systems for software that can be made in weeks instead of the months or years traditionally required for medical devices and pharmaceuticals.  Companies like Boston Scientific are going full agile with lean startup principles; their goal is to prove or disprove a hypothesis as quickly as possible. The FDA has demonstrated their understanding of the need for a new model.  The FDA PreCert program is a good start and within 1-2 years there may be a pathway to release a device in an iterative way while still keeping safety foremost.

Meanwhile, for approved devices there are systems of reimbursement that are being reexamined.  Kristine Canavan of Analytics 4 Life observed that one impact of AI may be lower physician reimbursement rates.  Even if the physician is still involved, they may be able to work more efficiently, leading to a shorter procedure and thus lower reimbursement amount.

Segments where digital is happening now

David Feygin described how implantable pacemakers and defibrillators are a good example where medical devices are collecting data and also providing a better user experience.  In this case, there is a multi sensor right next to the heart that makes digital diagnostics possible to predict heart failure several weeks out. That information can be shared with the physician, payer, and pharmacy.

Geoff Dacosta has been observing how Amazon is working backwards to the medical industry by starting with the consumer.  With Amazon Alexa’s recently announced clinical partnerships, they may be on the path to becoming your personal doctor in the home who can prescribe drugs through PillPack.  

Perhaps more dramatically, telesurgery is starting to happen.  A surgeon in one place can operate on a patient in a different state in the US or a different country.  However, this is occurring only in a limited way due to a patchwork of local governmental regulations.

Additionally there are areas of consumer health where clinical practitioners don’t fill all the gaps.  One example is sexual health and sexual dysfunction where many patients are reluctant to talk to medical staff.  In this niche, consumer health apps or services may feel more accessible to patients whether that’s communication with a bot or non-professional.  The concern is when such non-medical apps cross over into diagnosis.


The quantity of all the new data generated by digitalization is tremendous.  At this stage, it’s still not clear who should be the controller of the data and how to manage the volume so that it doesn’t overwhelm clinical staff.  

It’s likely that it will be the data companies because they understand and have the capability to manage the data.  Doctors and hospitals will likely lack the expertise and resources. And physicians do not want more data, they want tools that give them useful insights instead of endless alerts.  Another factor is that analyzing data can be very expensive. Even if a patient has access to all of their data, they may have no way to make use of it. During the Apple Watch study, many provider sites that participated in the study found the process painful.

With too much data and no central control, we may have to wait for algorithms of the future to catch up and manage it for us.

International implications

In different markets internationally, digital health is progressing in different ways based on local needs.  In the US, much of digitization is focused on efficiency and optimization. In less developed regions of Asia and LatAm, the emphasis is on very basic healthcare access.  Especially in rural areas where the clinical workforce is stretched thin, technologies like telehealth can make a big impact. In China, there might be a unique need for technology to facilitate care delivery at scale in a 10,000 bed hospital.  These are other challenges may make it difficult for digital health companies to deliver the same products and services to markets across the globe.