DENVER, CO – It may sound obvious, but innovations are constantly being made in the medical world. What’s not so obvious is that these advances are often slow to be implemented. We all know that new treatments must be thoroughly tested before they are administered to living patients. From a company perspective, there obviously needs to be financial viability for these developments. But even when there is a clear path forward the risk averse nature of medical industry leaders often slows down an already time intensive testing and deployment process.
This dilemma is hurting the industry and this country’s healthcare customers. In the areas of digital technology, medical informatics, predictive analytics, precision based medicine, machine learning and the concept of “artificial intelligence” a fresh business model needs to emerge.
There is no question that the medical field has struggled and is woefully behind other industries in its digitization efforts. It is far behind the energy, retail, telecom, travel and hospitality fields even in the simple concept of records automation. While healthcare providers are now utilizing digital technology processes with respect to patient information, many lack the vision, expertise or resources to implement structural transformations like predictive analytics or useful machine learning capabilities.
It is not for lack of data. For example, there are 1.6 million new cancer cases diagnosed each year in the United States alone, and each cancer type generates terabytes of both structured and unstructured data. Almost every cancer patient undergoes some form of digital imaging at least once, which by itself is a massive source of information. Combining that information with emerging proteomic discoveries enables leading oncologists to employ new intelligence gathering smart systems, that mine disparate data sources in order to fight specific cancer types. The insights obtained from this basic and logical use of available data sources is setting a totally new standard in addressing the needs of suffering patients. The fields of radiology, neurology and psychiatry need to jump on what their peers in the cancer arena are doing. And, they need to start right now.
The human brain is the most complex organ known today. Old, worn out methodologies are ineffective in accurately diagnosing complex brain disorders. Just look at the latest revelations regarding the chronic traumatic encephalopathy (CTE) data published in the recent Journal of American Medical Association.
The analogy of matching power with power is applicable if our mission is to unravel the basis of disorders of the human brain.
I would argue that it will take the best and most cutting-edge computing industry advances to better analyze the human brain. This is an organ with over 400 miles of blood pathways, an estimated 86 billion neurons, each with an average of 40,000 synapses and neuron transmission speeds approaching 268 miles per hour. It is the most sophisticated computer known today. One could argue that in order to analyze the human brain and all of its complexity, you need an equally capable technology tool set. The analogy of matching power with power is applicable if our mission is to unravel the basis of disorders of the human brain. This critical step is essential for precision medicine to become a reality.
Creating a mega data warehouse of human factors far exceeding information available in today’s electronic health records system is an imperative. Without including comprehensive data from other medical specialties, clinical data specialists run the risk of missing correct diagnoses and will certainly diminish the promise of predictive analytics. When pattern matching systems are used with united, wholistic and available patient data organized properly, it can be argued that diagnoses and proper therapeutic protocols should improve results for individual patients. The information obtained from individual patients can then contribute back into the database to add more insights for future patients.
Enabling all brain health related information to be accessible from every profession in pattern matching systems, will be a significant step forward in brain disorder diagnostics. Integrating such a digital system into the medical world not only enable doctors to improve their craft and save time, but should also help improve quality of life for patients. After all, how do you fix a problem if you don’t know what it is?