Transforming Healthcare With Data Physics


I just completed an in-depth paper on how our work and system can help life science and healthcare companies overcome the great challenges they face, so I wanted to share some thoughts while still fresh. The paper is part of our long-term commitment to healthcare and life sciences, requiring a deep dive over the past several weeks to update myself on the latest research in behavioral psychology, machine learning, deep learning, genetics, chemicals, diagnostics, economics, and particle physics, among others. The review included several hundred papers as well as a few dozen reports.

Kyield Distributed OS - Life Science and Healthcare

The good news is that the science is improving rapidly. An important catalyst to accelerated learning over the past 20 years has been embracing the multi-disciplinary approach, which academia resisted for many years despite the obvious benefits, but is now finally mainstream with positive impact everywhere one looks.

The bad news is that the economics of U.S. healthcare has not noticeably improved. For a considerable portion of the population it has deteriorated. The economic trajectory for the country is frankly grim unless we transform the entire healthcare ecosystem.

A common obstacle to vast improvement in healthcare outcomes that transcends all disciplines with enormous economic consequences is data management and analytics, or perhaps more accurately; the lack thereof. There is no doubt that unified networks must play a lead role in the transformation of healthcare. A few clips from the paper:

“By structural we mean the physics of data, including latency, entropy, compression, and security methodology. The Kyield system is intended to define structural integrity in NNs, continually exploring and working to improve upon state-of-the-art techniques.”

“While significant progress has been made with independent standards towards a more sustainable network economy, functionality varies considerably by technology, industry, and geography, with variety of data types and models remaining among the greatest obstacles to discovery, cost efficiency, performance, security, and personalization.”

Life science and healthcare are particularly impacted by heterogeneous data, which is one reason why networked healthcare is primitive, expensive, slow, and alarmingly prone to error.

“Biodiversity presents a unique challenge for data analytics due to its ambiguity, diversity, and specialized language, which then must be integrated with healthcare and data standards as well as a variety of proprietary vendor technology in database management systems, logistics, networking, productivity, and analytics programs.”

“Due to the complexity across LS and healthcare in data types, standards, scale, and regulatory requirements, a functional unified network OS requires specific combinations of the most advanced technology and methods available.”

Among the most difficult challenges facing management in mature life science companies are cultures that have been substantially insulated from economic reality for decades, only recently feeling the brunt of unsustainable economic modeling throughout the ecosystem, typically in the form of restructures, layoffs, and in some cases closure. This uncertainty particularly impacts individuals who are accustomed to career security and relatively high levels of compensation. I observed this often during a decade of consulting. The pain caused by a dysfunctional economic system is similar to the diseases professionals spend their careers fighting; often unjustly targeting individuals in a seemingly random manner, which of course has consequences.

“Among many changes for knowledge workers associated with the digital revolution and macro economics are less security, more free agency, more frequent job changes, much higher levels of global venture funding, less loyalty to corporate brands and mature industry models, and considerably increased motivation and activism towards personal passionate causes.”

Healthcare is a topic where I have personal passion as it cuts to the core of the most important issues to me, including family, friends, colleagues, and economics, which unfortunately in U.S. healthcare represents a highly self-destructive model. My brother was diagnosed with Lou Gehrig’s disease (amyotrophic lateral sclerosis/ALS) in 1997 not long after his only child was born. I’ll never forget that phone call with him or what he and his family endured over the next three years even though his case was a fine example of dedicated people and community. My father passed a decade later after a brutal battle with type 2 diabetes; we had an old friend pass from MS recently, and multiple cancers as well as epilepsy are ongoing within our small group of family and friends. So it would be foolhardy to deny the personal impact and interest. Healthcare affects us all whether we realize it or not, and increasingly, future generations are paying for the current generation’s unwillingness to achieve a sustainable trajectory. Unacceptable doesn’t quite capture the severity of this systemic failure we all own a part of.

The challenge as I see it is to channel our energy in a positive manner to transform the healthcare system with a laser focus on improved health and economic outcomes. This of course requires a focus on prevention, reduced complexity throughout the ecosystem, accelerated science, much improved technology, and last but not least; rational economic modeling to included increased competition. The latter will obviously require entirely new distribution systems and business models more aligned with current science and economic environment. Any significant progress must include highly evolved legislation reflecting far more empowerment of patients and dramatic improvement in fiscal discipline for the ultimate payer we call America while there is still time to manage the disease. If we continue to treat only the symptoms of healthcare in America it may well destroy the quality of life for the patient, if indeed the patient as we know it survives at all. This essentially represents my diagnosis.

A few of the 80 references I cited in the paper linked below are good sources to learn more:

Beyond borders: unlocking value. Biotechnology Industry Report 2014, EY
http://www.ey.com/GL/en/Industries/Life-Sciences/EY-beyond-borders-unlocking-value

Dixon-Fyle, S., Ghandi, S., Pellathy, T., Spatharou, A., Changing patient behavior: the new frontier in healthcare value (2012). Health International, McKinsey & Company.
http://healthcare.mckinsey.com/sites/default/files/791750_Changing_Patient_Behavior_the_Next_Frontier_in_Healthcare_Value.pdf

Thessen A., Cui H., Mozzherin D. Applications of Natural Language Processing in Biodiversity Science Adv Bioinformatics.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364545/

Top 10 Clinical Trial Failures of 2013. Genetic Engineering & Biotechnology News.
http://www.genengnews.com/insight-and-intelligence/top-10-clinical-trial-failures-of-2013/77900029/

Begley, C.G., Ellis, L.M. (2012) Drug development: raise standards for preclinical cancer research. Nature 483 http://www.nature.com/nature/journal/v483/n7391/pdf/483531a.pdf

Cambria, E., and White, B. Jumping NLP curves: A review of natural language processing research. IEEE Computational Intelligence Magazine, 9:1–28, 2014.
http://www.krchowdhary.com/ai/lects/nlp-research-com-intlg-ieee.pdf

Montgomery, M. Diabetes and the American Healthcare System. Kyield, Published online May 2010
http://www.kyield.com/images/Kyield_Diabetes_Use_Case_Scenario.pdf

All quotes above are mine from Kyield’s paper of 8-15-2014:

Unified Network Operating System
With Adaptive Data Management Tailored to Each Entity
Biotech, Pharmaceuticals, Healthcare, and Life Sciences

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New Report: Adaptive Unification for Life Science Ecosystems


First, I want to apologize for not being able to keep up with my blog as much as I would like, or to share as much in public as I would prefer. The reasons are twofold. We’ve been very busy at Kyield, and testing has increasingly confirmed that while competitors in our industry invest heavily in web information (CI), most customers do not; at least for enterprise-wide systems like Kyield.  So I have regrettably pulled back on detailed public writing, or rather– have replaced with more formal papers and presentations with customers.

A good example of our efforts is the new report below, which is a hybrid of an academic paper with citations supporting our claims and a detailed brochure for senior managers in pharmaceuticals, biotech, and healthcare–particularly those pursuing personalized medicine and significant improvement in operational efficiency:

Adaptive Unification  for  Life Science  Ecosystems 

Kyield report: Adaptive Unification for Life Science Ecosystems

The paper highlights the challenges facing the industry with considerable detail on how Kyield is unique in the world with respect to ability to overcome these challenges. Essentially, in order to overcome systemic challenges it requires a systemic solution, and in terms of distributed organizations it requires a very particular type of systemic solution that can address each of the challenges. Due to the high values involved, the result is that Kyield may well be the best investment option in the world today for life science executives.

For those who would prefer more frequent updates, the best methods to track either Kyield or my activity are as follows:

Connect with me on LinkedIn:      http://www.linkedin.com/in/markamontgomery/

Follow Kyield on LinkedIn:              

Follow @kyield on Twitter:             https://twitter.com/kyield

And of course visit our web site regularly at www.kyield.com

Kind regards,

Mark Montgomery