Healthcare IT Startups: How to Assess a Maturing Market

nazar /  Jan. 08, 2018


The provision of quality cost effective healthcare is one of the most significant challenges facing the U.S. today. Healthcare now accounts for more than one-sixth of the U.S. gross domestic product. According to a report by the Centers for Medicare and Medicaid Services, U.S. healthcare spending reached $3.2 trillion, or $9,990 per person, and hospital care accounted for a third of the overall health spending.

Founders of a new cohort of healthcare IT startups have been motivated to address this challenge using data analytics, AI, and scalable IT infrastructure solutions. Their challenge is to convince providers and payers to adopt their solutions by making the business case for data-driven methods that can have real impact on cost and quality of care.

From an investor’s perspective, the healthcare IT sector is a challenge to assess because it is relatively new, and HIT startups are competing in a broad marketplace to improve healthcare data, delivery, and outcomes while the nation’s healthcare delivery system is transitioning from volume-based to value-based care. At OUP, we’ve been active in the space for the last several years, having made a few HIT investments, as well as scouted within the health systems of our partner institutions looking for interesting technology that could become a future startup. Since 2014, a substantial amount of VC funding has poured into this sector, so we held a webinar on the topic to delve into what is happening in this space.

Our panelists for this discussion were with Samir Manjure, CEO and Co-founder of KenSci, Sunny Neogi, Head of Growth for KenSci, and Tom Hawes, Managing Director in Healthcare of Sandbox Industries.

From left to right: Tom Hawes, Sunny Neogi, and Samir Manjure.


It is worth noting that healthcare IT can be difficult to define. Sometimes it’s defined as anything digital relating to health. Using a broad definition can include consumer health companies, such as wearables or fitness startups, and also medical diagnostic companies. Our discussion in this webinar focused on the information technology side of HIT, in particular software and data driven healthcare IT opportunities.

Overall Takeaways

Gradual increase in healthcare IT VC activity corresponds closely to trends in Pharma/Biotech. These data exclude consumer health companies and medical diagnostic companies.


  • There appears to be a gradual increase in funding levels in healthcare IT startups over the past 5 years.
  • VC-backed HIT companies generally have institutional and commercial partners which have helped provide data and develop the value proposition early in the company’s development.
  • Having a commercially-minded focus very early as you’re starting the company and getting to revenues quickly is imperative to get VC funding. Often HIT companies have one contract with one customer, and it’s difficult to branch out of that environment to get to the second customer. Company founders need to go beyond the initial University IP source and customer and get to unrelated customers and validate value proposition elsewhere.
The Healthcare IT space is likely to see a large allocation of capital in the future as an AI approach to healthcare gains traction and more operators are adopting these services.


HIT Hottest Funding Categories (2016 and 2017)

Source: Startup Health Insights
  • The number one funding category as of Q3 2017 is Big Data / Analytics. Last year when Startup Health released the same report, big data ranked at #6.
  • Other areas where adoption is rapidly increasing is within decision support tools and data integration — generally how to better utilize data and use of data from different silos.

Data Utilization

  • KenSci’s value proposition comes from understanding how providers use and manage their data. “The real value of playing around with data came not with the data itself but understanding the challenge of managing that data. There is enough data in health systems today. It’s hard to make sense out of it. We came across the same set of problems our customers face today — converting lots of data into something a nurse or doctor can use.” — Sunny
  • Other tactical learning came from understanding the general structure of the data. “Most data sets follow a similar rhythm — similarities in how people fall sick. When we noticed these patterns, it was difficult for us to make sense of them. So we collaborated with UW medicine and got doctors involved to give us a sense of what lab test results we should track better. This led us to hire doctors to work alongside data scientists to bridge the gap between raw data files to machine learnable data to get data a doctor really cares for.”

What Investors Look for in HIT Startups

  • “We’ve seen success when there is some element of cross-collaboration across departments. Early on, typically at the university research stage, there was an outside party that helped ask some of the basic questions of the lead investigator: What problem does this solve, what value does it create, and how do you quantify that value? Having outside parties involved early to ask about business model and value opportunity, and having someone that can understand the nuances of a particular sector helps tremendously.” — Tom

Management Teams

  • “It’s always best to get the right entrepreneur from the start. Having the wrong entrepreneur, as opposed to no entrepreneur, is the worst thing you can do. Instead, the PI should carry the company forward and message to investors, customers, and new-hires they are looking for the right CEO and will step aside when this person comes along. Alternately, you can also have a ‘baton-carrier’ — but not one who thinks they are the long-term CEO as this will impede progress and financing.” — Marc Singer, Managing Partner of Osage University Partners

VC Diligence in HIT Startups

VCs ask the typical questions they would ask any startup: They ask if the CEO is the right CEO. They ask if the founding team has it in them to last 5–7 years and build this out. Because sales cycles are so long with HIT and software companies, VCs ask more questions around unit economics and modifying deal size based on cash flow. “Coming from a university, you are very focused on the value you want to add. You are not so focused on the value you want to get out of the customer.” — Samir

KenSci in particularly appreciated the diligence VCs performed on company culture and team. “The good VCs differentiated themselves from the bad ones by spending time on due diligence that you cannot present, but you feel it. We hired people based on whether they really wanted to do this — based on their commitment. Not based on where they previously came. The good VCs spent a lot of time understanding our core tenants and why we hire who we hire.” — Sunny

Investors in the Space


Here is the full webinar recording: