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Cota Healthcare: Cataloging Disease Attributes
John Hervey, CEO, Cota Healthcare
The American Healthcare system wastes as much as $1 trillion each year, according to several sources. Some of this unnecessary spending is caused by patients receiving too much, too little or the wrong care because physicians cannot see how patients “just like” the ones they are treating have fared historically. This is especially true for patients with very complex diseases such as cancer. The problem is exacerbated by poor data quality held in most electronic health records platforms. Taking stock of this predicament, Cota Healthcare was founded with the right mix of doctors, engineers and data scientists to counter the problem by creating a patented system that precisely defines patient groups. With its Cota Nodal Address (CNA), the company creates clinical grade Real World Data (RWD) sets that allow doctors and researchers to compare how clinically identical patients performed on different treatments and circumstances to enable optimal care decisions. This data can be wedded to cost and claims data to enable care providers to offer the best solutions while eliminating waste.
Cota initially targeted cancer, however, CNAs are effective tools for any complex disease such as mental health, cardiology and rheumatology. “Unlike ‘big data’ plays in healthcare that look for patterns in large data sets, Cota starts with established patterns – and finds value,” said John Hervey, CEO of Cota Healthcare. Each digitized patient record is encapsulated in a numeric code that expresses all relevant elements in a patient’s record and treatment journey. This code can be used by hospitals and insurance companies to optimize care and simplify claims adjudications. The CNA includes a wide array of phenotypic patient data like tumor type, histology, comorbidities and patient-specific genomics that is not included in the current standards such as the ICD codes.
CNA is a very flexible way of looking at data sets from a multi-dimensional perspective
Cota extracts historical patient data from a hospital’s EHR, corrects and enriches it, assigns CNAs to all patients, then performs comparative analysis that will be used by care givers to guide future optimal care. With CNA Guided Care, hospitals can engage in value based reimbursement programs for complex diseases including cancer. Moreover, CNAs are powerful research tools in the hands of academic institutions and life science companies. Clients can compare identical patient groups by treatments, costs or even socio-economic indicators such as zip codes. “The Cota platform with CNAs and its SaaS visualization products are powerful and flexible ways of looking at patient outcomes from multi-dimensional perspectives,” says Hervey. He further adds that Cota has effectively mapped all 163 subtypes of cancer which represent more than half a million unique CNAs. The company has already begun defining CNAs for mental health and is evaluating and prioritizing other diseases as well.
When Hackensack Meridian Health (HMH)—a NJ-based not-for-profit health care organization—set out to establish a value-based bundles program for its cancer center, they sought Cota’s assistance. Using its CNA Guided Care platform, Cota has worked closely with HMH to identify the best treatments for its patients then to use these results to optimize the cost efficiencies of its care. Cota has partnered with IBM Watson for Oncology to deliver its care solutions directly to physicians, nurses and other medical professionals at the point of patient care. This partnership combines the RWD and CNAs from Cota with the incomparable information suite and artificial intelligence platform of IBM Watson.
Cota already has a national footprint with its hospital partnerships and is working with seven of the top ten pharmaceutical companies. Hervey expects the demand for value based care solutions to rise significantly in the future and believes Cota has one of the only viable solutions for very complex diseases that optimizes outcomes rather than rationing care.
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