Search
Close this search box.

Revolutionizing Healthcare: The Generative AI Prescription

This year, $4.7 Trillion will be spent on healthcare in the US – 18% of the national economy, and it is expected to grow to 20% of our GDP by 2031.

 

Healthcare Expenditure

There are precious few industries so ripe for tech innovation and actual life-saving gains via Generative AI as the healthcare industry. It has been a painfully slow process but we are seeing green shoots as AI is being deployed across many areas of the sector.

But why now? Healthcare has been known for regulation, bureaucracy, and slow tech adoption. If it weren’t for the HITECH Act of 2009, which provided subsidies to encourage hospitals and providers to adopt EHR systems, we could have still been living in a pen and paper health ecosystem today.

For one, Generative AI’s ability to analyze large volumes of unstructured data shows great promise amidst the treasure chest existing in medical records and other healthcare related documents. At the same time, healthcare is in a crisis – cost of care has never been higher, doctor burnout is causing labor shortages, and brick and mortar hospitals are facing unprecedented competition from acquisitive tech-forward players like Amazon, CVS, and Walgreens.

Marrying these trends, we believe AI offers compelling solutions to customers facing existential problems, prompting shorter sales cycles and quicker adoption than typical in the industry.

March’s Areas of Investment Interest

At March Capital, we believe there will be significant value up for grabs from AI innovation in healthcare. According to Statista, the artificial intelligence healthcare market, valued at $11 billion in 2021, is projected to be worth $187 billion in 2030. We are especially excited about innovations in biopharma, healthcare administration and operations, and clinician automation.

Biopharma stands as one of the industries set to undergo the greatest transformation. Drug discovery, development of proteins, and gene writing are examples of how AI/ML are leading to faster medical breakthroughs.  AI is already reshaping this landscape and we are expecting to see a lot more disruption. Read more here: The Intersection of Computational & Biological Sciences: A New Era in Biopharma. Our investments in Generate Biomedicines and Tessera Therapeutics highlight our excitement in this area.

Healthcare administration and operation tools look to simplify the heavy administrative burden health systems face. Hospital back-offices often operate in silos, relying on manual inputs across fragmented systems that hinder data sharing and synthesis. This administrative headache has financial repercussions – in 2022, approximately half of U.S. hospitals finished the year with negative margins. These health systems need a quick ROI solution. We are starting to see some of these emerge with process automation tools (such as revenue cycle management and prior authorization), chatbots, and call center automation.

Clinical automation tools, which free up clinician’s time to focus on the patient, is one of the most exciting and tangible categories in healthcare. Generative AI is a breadth of fresh air for health practitioners who typically spend over 2 hours of paperwork for everyone 1 hour of patient time. Digital assistants like Suki, as well as workflow automation, decisioning, and diagnostics tools, drive clinician efficiency and improved quality of care.

Suki AI – A Game Changing Copilot
Suki is a digital assistant that is the only ambient listening solution on the market, fully integrated with all the major EHRs. This “Siri for Doctors”, helping physicians cut paperwork time and increase revenue by enabling more patient visits and greater billing code accuracy, was started with the mission to lift the administrative burden on doctors so they can focus on what matters most: the patient.

It is estimated that physician burnout contributes to $4.6 billion in costs annually; according to a study conducted by the American Academy of Family Physicians, Suki helps physicians reduce documentation time by 72%.

We first invested in Suki in 2021. Our thesis was that clinical workflows would be the first impacted by AI, and beating incumbents would require an entire suite of solutions at lower cost. Suki is led by Founder & CEO Punit Soni, who previously served as CPO at Flipkart after leading the search and mobile application groups at Google. Punit’s product expertise has been valuable in healthcare, especially in a category selling directly to healthcare groups and EHRs. We see this manifest in Suki’s deep focus on UI and workflow, which has been a meaningful driver of adoption.

Suki’s unique technology picks up doctor/patient interactions ambiently and translates them into narrative via generative AI. Here’s how it works: A clinician asks Suki about her schedule for the day, and who the next patient is. The app pulls up all pertinent details of this next visit, prior actions taken, and starts listening ambiently. During the visit, the app synthesizes existing patient history data from disparate sources and identifies crucial gaps. The clinician focuses solely on providing good care, while AI is listening and taking complete session notes. Afterwards, the notes, synthesized and cleaned, are reviewed by the clinician, approved, and relevant information automatically shared:

  • Appointment details – symptoms, diagnoses, tests, results – added back to the EHR of choice
  • Details shared with other doctors as needed
  • Follow-up medical instructions are created
  • Prescriptions are scripted
  • Billing codes are assigned for insurance processing and reimbursement

All of this is done completely via AI, acting as the clinician copilot where the clinician has full review and edit control. Once reviewed and approved, the app preps the clinician with the details of the next patient. Altogether, this process leads to a 72% reduction in soul-sucking paperwork, happier clinicians, and healthier patients.

Why is Suki differentiated? Suki Assistant can perform clinical documentation through ambient technology, dictation, or command, depending on which mode best suits the circumstance (i.e., in a noisy environment, as is often the case in hospitals, ambient technology struggles to record information effectively).

More importantly, Suki has true bi-directional integration with a hospital’s system of record. This enables a variety of workflows – for example, a clinician can start a note within their EHR, complete it in Suki, and send it back to the EHR at the click of a button. This is not only difficult to build, but also meaningfully more impactful for health professionals, as it drives real time savings compared to semi-accurate and poorly integrated ambient tools in the market.

As we get used to this inevitable future, we wonder how healthcare could have ever been done any differently. The answer is manually, with complex, error prone, and cumbersome processes. The optimism is AI can unlock $1 trillion of unrealized potential in the industry.

Conclusion

Healthcare has the perfect ingredients for AI disruption and the creation of big companies – a huge, inefficient market; abundant unstructured data; disparate manual processes; a growing customer base. Gen AI will re-imagine the industry in ways not possible with previous technologies.

Despite optimism, it is important to recognize that healthcare will continue to move slower than other more tech forward industries. Given sensitivity around healthcare data, there will be more stringent privacy and regulation requirements with healthcare tools, and a greater need for a human in the loop when implementing automation. Nonetheless, we are already starting to see it reshape the industry and we are excited to see the category develop in the years to come.

At March Capital, we are proud to back companies in the frontline of innovation and look forward to meeting new founders building the future of healthcare.