Mar 312017
 

CognitiveThere are approximately 22,000 new cases of lung cancer each year with an overall 5-year survival rate of only ~18 percent (American Cancer Society). The economic burden of lung cancer just based on per patient cost is estimated $46,000/patient (lung cancer journal). Treatment efforts using drugs and chemotherapy are effective for some, however more effective treatment has been hampered by the inability of clinicians to better target treatments to patients. It has been determined that Big Data holds the key for providing clinicians with the ability to develop more effective patient centered cancer treatments.

Analysis of Big Data may also improve drug development by allowing researchers to better target novel treatments to patient populations. Providing the ability for clinicians to harness Big Data repositories to develop better targeted lung cancer treatments and to enhance the decision-making process to improve patient care can only be accomplished through the use of cognitive computing. However, having a source or sources of data available to “mine” for answers to improve lung cancer treatments is a challenge!

There is also a lack of available applications that can take advantage of Big Data repositories to recognize patterns of knowledge and extract that knowledge in any meaningful way. The extraction of knowledge must be presented in a way that researchers can use to improve patient centric diagnosis and the development of patient centric treatments. Having the ability to use cognitive computing and KM methods to uncover knowledge from large cancer repositories will provide researchers in hospitals, universities, and pharmaceutical companies with the ability to use Big Data to identify anomalies, discover new treatment combinations and enhance diagnostic decision making.

Content Curation

An important aspect to cognitive computing and Big Data is the ability to perform a measure of content curation. The lung cancer Big Data environment that will be analyzed should include both structured and unstructured data (unstructured being documents, spreadsheets, images, video, etc.). In order to ingest the data from the Big Data resource the data will need to be prepared. This data preparation includes applying Information Architecture (IA) to the unstructured data within the repository. Understanding the organization and classification schemes relating to the data both structured and unstructured is essential to unifying the data into one consistent ontology.

Are We Up for the Challenge!

Even if a Big Data source was available and content curation was successful, the vast amounts of patient data is governed by HIPAA laws which makes it difficult for researchers to gain access to clinical and genomic data shared across multiple institutions or firms including research institutions and hospitals. According to Dr. Tom Coburn in his January 14th article in the Wall Street Journal ‘A Cancer ‘Moonshot’ Needs Big Data; gaining access to a big data repository all inclusive of patient specific data is essential to offering patient centered cancer treatments. Besides the technology challenges, there are data and regulation challenges. I’m sure that many of these challenges are being addressed. Thus, far there have been no solutions. Are we up for the challenge? Big Data analysis could help tell us which cancer patients are most likely to be cured with standard approaches, and which need more aggressive treatment and monitoring. It is time we solve these challenges to make a moonshot a certain reality!

Feb 292016
 

Cancer MoonshotOn January 12, 2016 in his State of the Union address, President Obama called for America to become “the country that cures cancer once and for all” As he introduced the “Moonshot” initiative that will be guided by Vice President Joe Biden.

Dr. Tom Coburn, former Republican Senator from the state of Oklahoma and three time cancer survivor, in his January 14th article in the Wall Street Journal ‘A Cancer ‘Moonshot’ Needs Big Data ; indicates that “harnessing that information (“big data”) would allow us to personalize prevention and treatment based on the genetic characteristics of a patient’s tumor, family history and personal preferences, while minimizing unwanted side effects.”

On February 5, 2016 on CNN’s Global Public Square show: Big data could be a health care game-changer author and doctor, David Agus tells Fareed Zakaria how using big data and examining thousands of cases might increase how long we live and our quality of life.

At this time in our history, with the continuing electronic capture of patient information from intake to discharge, the opportunity could not be brighter to cure cancer. The Obama administration’s 2010 initiative to capture electronic health records has enabled the opportunity to improve patient care, increase patient participation, improve diagnostics and patient outcomes, improve care coordination, as well as create practice efficiencies and cost savings.

The electronic capture of patient information has created medical big data repositories. One such repository is the American College of Surgeons/American Cancer Society’s National Cancer Database – NCDB. Resources such as these will benefit by utilizing knowledge management and information architecture techniques to identify and unlock knowledge patterns contained within these big data sources. In several of my blog post dating back to January 2013, I wrote about the advantages of applying KM to big data. From understanding Contextual Intelligence KM and Big Data ; to devoting a chapter on KM and Big Data in my upcoming book KM in Practice; I believe when executed the right way KM, powered by information architecture will provide the essential ingredient when applied to big data. This will enable researchers to discover better treatments and possible cures for many diseases including cancer and we will realize the dream presented by the Moonshot initiative!

Sep 192015
 

contextual%20intelligence-technologyThis all started during a conversation I had with a colleague (Baron Murdock of GreenBox Ventures, LLC) and he mentioned the term Contextual Intelligence. Due to the fact that we were talking about knowledge management and big data I believe that I understood what he was talking about. However, I had never heard of the term. Not long after our meeting I began to do a little research on the concept of contextual intelligence.

What is Contextual Intelligence?

It is during my initial research (consisting of a series of internet search queries) where I began to understand that the term Contextual Intelligence is not new. As a matter of fact it’s a term that has been used in graduate business schools since the 80’s.

Contextual Intelligence is, according to Matthew Kutz “a leadership competency based on empirical research that integrates concepts of diagnosing context and exercising knowledge”; Tarun Khanna states that ”understanding the limits of our knowledge is at the heart of contextual intelligence” and Dr. Charles Brown states that “Contextual intelligence is the practical application of knowledge and information to real-world situations. This is an external, interactive process that involves both adapting to and modifying an environment to accomplish a desired goal; as well as recognizing when adaptation is not a viable option. This is the ability that is most closely associated with wisdom and practical knowledge”

While there are several positions on what contextual intelligence is. I align more to Dr. Brown’s assertion of Contextual Intelligence. When it comes to knowledge management (KM) and contextual intelligence, context matters! Understanding that contextual intelligence is link to our tacit knowledge, I immediately thought of what is the connection between KM and Contextual Intelligence. Knowledge management among other aspects is concerned with the ability to understand knowledge and adapt that knowledge across a variety of environments (cultures) different from the origin of that knowledge.

To enable the flow of knowledge to the right person in the right time and in the right context, it is essential to understand the context of that knowledge. Information Architecture (IA) is the backbone of delivering knowledge in the right context to users of Knowledge Management Systems (KMS). IA focuses on organizing, structuring, and labeling content (information and knowledge). IA enables users to find relevant content in the right context, understand how content fits together, connects questions to answers and people to experts. It is the incorporation of IA that contributes to giving knowledge its context.

Understanding the context of knowledge consists of:

  • Understanding the intent of the knowledge
  • Understanding the cultural and environmental influences on the knowledge
  • Understanding the role (or who) the knowledge is intended to be used by
  • Understanding the relevancy of the knowledge (The knowledge could only be valid for a specific period of time)
  • Understanding the origin (lineage) of the knowledge

Big Data

Without context data is meaningless, this includes structured and unstructured data. Big Data resources contain a proliferation of structured and unstructured data. Knowledge management techniques applied to big data resources to extract knowledge will need to understand the context of the data in order to deliver pertinent knowledge to its users. Knowledge Management has the ability to integrate and leverage information from multiple perspectives. Big Data is uniquely positioned to take advantage of KM processes and procedures. These processes and procedures enables KM to provide a rich structure to enable decisions to be made on a multitude and variety of data.

We know that context matters. Especially when it comes to what we know (our knowledge). Being able to adapt our knowledge with others is at the heart of successfully communicating, sharing what we know and to fuel innovation.

Obtaining contextual intelligence for your organization consists of leveraging or hiring people who are fluent in more than one culture, partnering with local companies, developing localized talent and enabling your employees to do more field work to immerse themselves in other cultures (tuning in to cultural and environmental differences).

A couple of great resources to read on Contextual Intelligence are “Contextual Intelligence” by Tarun Khanna from the September 2014 issue of Harvard Business Review and “Understanding Contextual Intelligence: a critical competency for today’s leaders” by Matthew R Kutz and Anita Bamford-Wade from the July 2013 Emergent Publications, Vol. 15 No. 3.

Jan 302013
 

Knowledge Management TrendsNow that we are firmly into 2013 lets take a look at what is trending in Knowledge Management (KM) this year.

With the proliferation of mobile devices (iPhone, Chromebook, iPad, Android devices) Personal KM is moving front and center. In the enterprise, as more and more content and knowledge gets created and the need to access and use that knowledge and content to address day-to-day knowledge needs of workers and customers (see Big Data), providing knowledge quickly to address internal and external users, as well as search and findability, are getting much attention within organizations implementing KM.

Let’s take a look at what some others are indicating the trends will be for KM in 2013:

  • Matthew Whalley – ClientKnowledge Manager (Legal Services), talks about “helping clients to realize efficiencies and knowledge gains, the growing realization that KM delivers more than “documents” providing  “operational” efficiency, transaction delivery, knowledge re-use and transformation, and technology – social and mobile channels”.
  • SAP indicates that “defining a knowledge management strategy, structuring content and measuring business impact as well as reaching external leadership are becoming more and more important”.
  • KMWorld indicates that the focus is on sharing collective knowledge and on KM strategy more so than the technology.

These are some thoughts on what to expect regarding KM for 2013. So, what do you think? I look forward to hearing more about what other organizations and individuals are doing with KM in 2013!