AiThority Interview with Dr. Trishan Panch, Co-Founder at Wellframe

Hi Dr. Trishan Panch. Please tell us about your role and the team / technology you handle at Wellframe. How did you arrive at Wellframe?

My interest in healthcare has always been getting the right care, to the right people, at the right time, and in the right way. I practiced medicine for 15 years before co-founding Wellframe, and I’m also currently an instructor at the Harvard TH Chan School of Public Health and a lecturer at MIT. My experience has made it crystal clear that the appropriate use of technology is critical to achieving the goal of improving access to care, in the ways people want it. What’s challenging, though, is that the healthcare system itself was not built with patients in mind. I co-founded Wellframe to solve the two biggest systemic issues in American healthcare — the patient experience and rising costs. Wellframe lets users proactively manage their care from home, through an easy-to-use app. It connects people directly with healthcare professionals so they always have access to support. And, crucially, it also gives healthcare professionals the ability to connect more intimately and effectively with the patients who need their help the most.

Tell us more about your role and how it evolved during the pandemic months? What technology / applications did you leverage to boost your remote workplace?

The pandemic accelerated the trajectory for Wellframe, as health insurance plans learned the steep cost of not establishing digital relationships with members, and increased their urgency to leverage technology to better support vulnerable populations. Without digital care, patients come into the hospital more often, but have less effective visits.

Within Wellframe, we used a number of applications to ensure our remote teams stayed aligned, including video conferencing and instant messaging, but the biggest contributor to our success in working remotely was our culture. Collaboration is one of our values, and that was evident every day in how our teams came together to support our customers and their members.

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What Is Wellframe and how does it leverage technology to improve adoption of AI in healthcare?

Partnering directly with health plans, Wellframe creates therapeutic relationships between patients and their clinicians whilst also giving patients powerful tools to manage their own care in between trips to the doctor’s office or hospital. Patients can use the Wellframe app to track their medication, diet, and exercise, to link to medical devices, and to connect with their healthcare professionals for a cohesive, relationship-driven patient experience. This both enables patients to do more themselves and makes help more accessible when they need it. The combination has a powerful effect on clinical outcomes and reduces the total cost of care, especially for patients with the most complex conditions. A recent peer reviewed paper we published details the powerful effects of this approach.

Wellframe’s platform includes AI technologies including natural language processing (NLP) to transcribe and track patient-clinician communication. This data informs prediction models for clinical events within a workflow product used by both patients and clinicians. For example, if a patient consistently uses Wellframe’s chat feature to talk to a clinician about mental health, Wellframe’s NLP can detect those patterns and start recommending other mental health resources to the patient. Wellframe improves the overall adoption of AI in healthcare by embedding technology like NLP into clinical workflows.

Do you think using AI in healthcare could help in stopping the spread of a pandemic, such as SARS, AIDS and Coronavirus?

It is difficult to make predictions in this area due to the many political and social factors involved in stopping a pandemic. However, during the recent Covid-19 pandemic, our NLP algorithms identified a sharp uptick of questions from Wellframe users about Covid-19: symptoms, anxieties concerning the possible extent of the outbreak, and advice regarding travel. This data helped us provide additional support and advocacy to patients during the pandemic. AI tools like NLP can help health systems, plans, and leaders identify the key pain points for patients around a specific health crisis.

Tell us more about the decentralized approach to AI and healthcare policy and predictions for where it’s headed.

My prediction for decentralized AI is that it will be driven by clinicians as opposed to manufacturers of AI algorithms. As clinicians become increasingly specialized in AI, they will be more qualified to understand which specific patients might benefit from which specific algorithms and how those algorithms might exacerbate inequities in local populations.

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Could you explain how healthcare interoperability works and how to enable better information capture in EHRs?

Interoperability is simply the aspiration of making data captured in the different silos of healthcare useful across these silos. Many other industries already have interoperable data due to the clear benefits of adopting this approach from a commercial point of view. As healthcare is more complicated and has necessary regulation, interoperability remains an aspiration. Better information capture in EHRs is only one part of the problem. There need to be aligned incentives between different healthcare organizations who share patient care but often have different organizational goals. We also need better methods of data capture that require less clerical work from clinicians. Over and above there need to be standards for data structure and data sharing. There has been great progress in each of these areas but there is still a long way to go.

How tech in healthcare is enabling better care and making it easier for patients to own their healthcare journey (automating workloads for physicians to focus on higher value work, improving predictive analytics, etc.)

Patients, people like us, actually do most of the work of managing chronic or long term conditions ourselves and this work is invariably done between visits and after discharge. The opportunity for technology is therefore to recognize and intentionally empower patients as producers of their own health.

Introducing digital care management tools helps patients proactively manage their own care whilst building rich virtual relationships with healthcare professionals. Not only does it streamline the burden of managing a chronic condition (or multiple comorbidities), but virtual health programs can help reduce unnecessary hospital and ER visits through proactive, continuous care.

On the health plan and provider side, implementing technology, like automation, cuts down on administrative and backend duties that clinicians are often tasked with, and allows them to prioritize building relationships that have therapeutic value. Where health plans and providers have implemented digital programs, we have found that when patients do come in to meet with their doctor, the appointments are of higher value to both parties.

Your opinion on the idea of reskilling needed for high-growth industries such as healthcare:

We need more involvement of the tech industry in healthcare and more clinician and patient involvement in the tech industry. This will require a lot of skills training in digital health. At Wellframe we offer this to our customers and partners. In my academic role I am also developing courses in this area at Harvard. We recently taught the first course on applied AI in health care  to a global audience of leaders from across healthcare.

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Your prediction on the future of AI’s role in post-COVID world and how it would influence the C-level expectations from AI investments:

We cover this extensively in the course I teach, actually, as many of our students and faculty are senior executives in healthcare and health tech. Healthcare is full of inference tasks — many of which are automatable but presently not automated. As such there are huge opportunities for this generation of machine learning-based inference technologies. However, to realize the value of these technologies, executives will need to be aware of not just the technologies themselves but also the public health dimensions of applying these technologies at scale. They’ll need to understand how to manage change in healthcare organizations, how to address risks of algorithmic bias, and how to create winning business models for AI in healthcare. On that last topic, I recently published a paper in HBR.

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Heather Mattie

Thank you, Dr. Trishan! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]