Three years ago, Cota, a New York-based digital health company had three employees. Now, the company is using the minds of nearly 100 employees to solve one of the most difficult problems in healthcare — finding a way to provide a universal data model for healthcare to help physicians improve the standards of care. Ultimately, the company seeks to make changes not just to fundamentally change how clinicians use data and make decisions in healthcare, but to accelerate the pace of research in academic networks, and provide real-world evidence to pharmaceutical companies developing cancer-fighting treatments. As the company works to solve this challenge, it is producing a significant amount of research in the field and has been published in 15 peer-reviewed journals and delivered presentations at multiple industry conferences.
Two members of Cota’s founding team, oncologists Andrew Pecora, MD, and Stuart Goldberg, MD, have been practicing medicine for more than two decades. Both work at the John Theurer Cancer Center in Hackensack, NJ. Ten to fifteen years ago, the two doctors saw a need that they first set out to solve for themselves in their cancer treatment work, later realizing a business could be formed to improve the lives of cancer patients everywhere by using data and technology.
One of the challenges with cancer treatment is its complexity of diseases and types of treatments, complicated by no two people being alike. In oncology, a doctor must consider a patient’s genetic mutations, hormone responses, as well as comorbidities before recommending medical treatment. When multiple factors like this come into play, treatment of, say, a 25-year-old female with breast cancer can vary widely. However, Pecora and Goldberg considered how treatment decisions could fundamentally change by taking all the available clinical factors that have prognostic and then classify patients to build a universal model for a new way of thinking about cancer treatments.
They started by building a simple database to isolate and track key clinical factors that weren’t all in place or easy to find in either paper charts or electronic health record systems. From that concept, the two doctors eventually formed the company Cota in 2011 four to five years ago. Over time, Cota grew into a robust value-based care measurement and decision support tool for providers, a research platform for academics, and a real-world evidence platform for pharmaceutical companies. “The doctors realized that this could be more than just a database or a classification methodology, but rather the beginning of an entire new way to think about classifying patient data and using it that for decision making,” says Cota VP of Marketing Matthew Levin. “In addition to it working for individual physicians, it could also work throughout the entire spectrum of healthcare, including the provider organization as a whole.”
Precise timing for precision medicine
Considering the economic impact of cancer treatment, Cota’s introduction to the market could not have come at a more opportune time. According to the American Cancer Society, about 600,920 people are expected to die of cancer in 2017 while the Agency for Healthcare Research and Quality is indicating that the per-person costs of cancer are exceeding those of the #1 killer — heart disease. “We are talking about a healthcare system where costs are rising in an unsustainable way,” says Levin.
Healthcare is moving from fee-for-service care delivery to one based on value, but according to Levin, no way exists to quantify that value. “That’s because there’s no way to determine if you are giving the right care to the right patient; at present, there’s no method of looking at patients on an apple to apple basis,” Levin says. As the medical costs increase, determining the right care will be crucial. Cost expenditures rise when an aging population is combined with the complexity of all the new therapies that are coming to market. “That is an information problem we are trying to solve,” he says.
Healthcare is hard but solvable
When evaluating how to turn patient data into useable insight at scale, one quickly realizes the complexity of such a challenge. Levin says it’s one part technology, one part medical/clinical IQ, one part biology, and one part data science and analysis with a certain strong human component added to that. “You just can’t press a button and have a computer calculate this automatically; it takes a system to do this with an incredible amount of engineering and manpower to accomplish the feat. This is not something that two guys in a dorm room can hammer out,” Levin explains.
Healthcare, as well as this multi-faceted challenge for treating diseases with such complexity, remains a giant problem. Only a couple of companies have tried to tackle it. “IBM Watson is a great example. We are very friendly with them, but they are attempting to solve the problem by taking a different approach. They’ve applied the most powerful artificial intelligence (AI) engines in a different way on the data,” explains Levin. “That’s the magnitude of of the problem we are trying to solve.”
Oncology and beyond
In the beginning, the company co-founders used the full name of its database tool — Cancer Outcomes Tracking and Analysis, but later began using the acronym (Cota) when they saw that the Cota methodology could be applied to more than just cancer outcomes. The company has started with oncology, but it definitely has expansion plans. Not all medical areas make sense for the Cota methodology. Orthopedics being one example of where many of these problems have been solved with bundled payments, but Levin says, “many other areas like cardiology, behavioral health and other specialties where a certain level of complexity exists do make sense.”