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Health Data Analytics 2016 — Martin’s Insights

29 Nov

I captured this write up by Martin Fowler as it is organized around 6 areas that I see as foundational: collection/persistence; privacy / security; interoperability / sharing; BI / Reporting;  analytics; and, Information strategy. It always seems in one form or another to come back to these topics.


Health Data Analytics 2016

I had the privilege and pleasure to attend HISA’s Health Data Analytics conference in Brisbane on 11 and 12 October 2016. What follows is this particular BI and Analytics consultant’s impressions and insights from the conference in terms of the main themes covered and the messages and impressions I take away, again from my particular…

via Health Data Analytics 2016 — Martin’s Insights


Healthcare’s New Big Idea

14 Oct


Once upon a time in the American healthcare system, big data was an unknown idea. Recognizing that healthcare costs rose unmanageably and healthcare quality varied dramatically without clear explanation, Congress introduced Managed Care with the hope that relying upon a for-profit business model would make the system more competitive, more comprehensive, and more effective. Now, over thirty years later, it appears that new changes in American healthcare will position “big data” as the driver of effectiveness and competitiveness. Here are a few reasons why.

When thinking about the government policy that will make big data essential in the new healthcare system, three main pieces of legislation come to mind – the obvious heavyweight of the group being the Affordable Care Act (ACA). By now, most know that by passing the ACA into law, the federal government shifts America away from a volume-based system of care (in which doctors and hospitals make money based on how many tests they run and treatments they try) to a value-based system in which doctors and hospitals receive rewards according to the value created for patients. However few know that in order to actualize this value-based system, the ACA directly implicates big data at federal and state levels of healthcare. For example, the ACA authorizes the Department of Health and Human Services (HHS) to release decades of stored data and make it usable, searchable, and ultimately analyzable by the health sector as a whole to promote transparency in markets for healthcare and health insurance. Here, the driver of transparency, and thus competitiveness and effectiveness, is clearly big data.

In other examples, the ACA uses language that endorses, if not mandates, big data use throughout the system. The ACA not only explicitly authorizes the Center for Disease Control (CDC) to “provide grants to states and large local health departments” to conduct “evidence-based” interventions, it creates a technical assistance programs to diffuse “evidence-based therapies” throughout the healthcare environment. Note that in the medical community, “evidence-based medicine” means making treatment decisions for individual patients based on data of the best scientific evidence available, rendering the use of this relatively new term an endorsement of big data in healthcare treatment. These pieces of evidence – in the form of direct references to big data at the federal level, state level, and patient level – strongly support the conclusion that the ACA creates a new system reliant upon big data for efficiency and competitiveness.

The remaining pieces of legislation further signal big data as the new lifeblood of the American healthcare environment. In 2009, the Open Government Directive, in combination with the Health Data Initiative implemented by HHS, called for agencies like the Food and Drug Administration (FDA), Center for Medicare & Medicaid Services (CMS), and CDC to liberate decades of data. The Health Information Technology for Economic and Clinical Health Act (HITECH), part of the 2009 American Recovery and Reinvestment Act, authorized over $39 billion in incentive payments for providers to use electronic medical records, with the goal of driving adoption up to 85% by 2019. Finally, to facilitate the exchange of information and accelerate the adoption of data reliance in the new health environment, CMS created the Office of Information Products and Data Analytics to oversee numerous databases and collaborate with the private sector. Among other functions, this office will oversee the over $550 million spent by HHS to create data clearinghouses – run by states – that will consolidate data from providers within the given state. All of this legislation, which essentially produces a giant slot for a big data peg to fill, paves the way for a new healthcare environment reliant upon rapid sharing, analysis, and synthesis of large quantities of community and national health data.

Now at this point, nearly four years after legislation supposedly opened the floodgates of big healthcare data to the private sector, the reader must wonder why more private sector companies haven’t taken advantage of an obvious market opportunity. The answer is: actually, a few first movers have.

Blue Cross / Blue Shield of California, working together with a company called Nant Health, has created an integrated technology system that allows hospitals, HMOs, and doctors to deliver evidence-based care to patients under their jurisdiction. This system catalyzes performance improvement, and thus revenue-generating value creation, across the system. The use of big data has also allowed some first movers to innovate and generate applications reliant upon newly liberated data. A company called Asthmapolis created a GPS-enabled tracker that monitors inhaler usage by asthmatics, directs the data into a central database used to detect macro-level trends, and merges the data with CDC data pertaining to known asthma triggers. These few cases illustrate that private sector engagement in this new market opportunity remains new, and diverse, and far from delimited.

The ACA has moved into its execution phase, and the introduction of the big data idea poses new and interesting challenges to how the American Healthcare system will evolve. Some challenges will bring about positive change, such as identification or clear opportunities for preventive care. Other challenges will bring negative change, such as the adverse effects transparency will likely have on certain patient groups. Regardless, it looks like big data is here to stay.

The Making of an Intelligence-Driven Organization

6 Jun

Interesting presentation – but really liked the Prezi – if you have not seen one of these have a look

The discussions/handout covered many points including:

  • As a discipline, intelligence seeks to remain an independent, objective advisor to the decision maker.
  • The realm of intelligence is that judgment and probability, but not prescription.
  • The Intelligence product does NOT tell the decision maker what to do, but rather, identifies the factors at play, and how various actions may affect outcomes.
  • Intelligence analysts must actively review the accuracy of their mind-sets by applying structured analytic techniques coupled with divergent thinking
  • Critical thinking clarifies goals, examines assumptions, discerns hidden values, evaluates evidence, accomplishes actions, and assesses inferences/conclusions
  • Networking, coordinating, cooperating, collaboration, and multi-sector collaboration accomplish different goals and require different levels of human resources, trust, skills, time, and financial resources – but worth it to ensure coverage of issues.
  • Counterintelligence and Security to protect your own position
  • and more….

I liked the stages of Intelligence Driven Organizations in the Prezi.

Good Perspective on Analytics

11 Feb

Interesting post on healthcare fraud – a couple of good points – traditional view of predictive analytics assumes you know what you are predicting – Fraud is adaptive – it changes. As a result being predictive requires a more diverse approach that involves a range of analytical approaches.

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