Medicine Storm Clouds

Trying to connect the dots in healthcare delivery can be a lot like stringing beads in a windstorm: the time spent getting even a few in place often comes at the expense of losing track of many others. Over the past few days I came across three articles that feel like they should be strung together because they share an unintentional common theme: what will the practice of medicine look like in a decade from now as more and more medical knowledge is captured and made available in the cloud: the Medicine Cloud.

The cloud I refer to of course is a metaphorical description of electronic computing resources (i.e., data storage, hardware and software) that are accessed by users through web browsers and light-weight desktop and/or mobile applications. There are significant advantages to healthcare providers leveraging cloud-based computing, notably a significant reduction in upfront investment – both in terms of time and capital. Lower maintenance costs, improved reliability and the facilitation of greater data sharing that can enable more efficient integrated care delivery and provider interoperability are also big advantages.

The three articles I reference above include:

    Through a Scanner Darkly: Three Health Care Trends
    for 2013
written by Dr. David Shaywitz in the
    Healthcare Blog;

      Brain Awareness, by Dr. Thomas Insel, Director of the
     National Institute of Mental Health; and

      the third was an article shared by Dr. William Palmer
      in our HCPolicy online discussion group:
     learning: Campus 2.0
 by M. Mitchell Waldrop in
     the March 13th edition of Nature Magazine.

From different perspectives each of these articles represent key trends and drivers likely to impact how Medicine is practiced in the future – and in particular, the impact information technology will have. And while there are reasons for optimism in how advancements in technology can lead to improved access, efficiency and productivity – information technology has so far not proven to be the panacea many practitioners had hoped for.

Sourcing, capturing and aggregating medical-based knowledge – and then making that knowledge readily available to clinicians (e.g., including physician extenders) can be incredibly enabling and empowering for both the clinician and the patient, particularly when it is made available in real time. But there are hugely challenging concerns and substantial public policy issues that I think we should be discussing.

For example, one major challenge – as shared by Dr. Shaywitz in his blog post – is finding balance between the current push toward practice standardization that information technology naturally enables and maintaining the valuable non-standardized realities of practitioner experience. Dr. Insel’s article succinctly explains just how far we are from understanding how the human brain functions. To the extent we come to view an electronic knowledgebase as replacing a trained and experienced clinical practitioner’s brain, I think we do so at great peril.

On the other hand, making more medical-based knowledge available at a lower cost (i.e., as shared in the Nature Magazine article) has the potential to address the looming challenge of primary care physician access. Indeed, knowledge is power, and we should never be afraid to pursue any opportunity that empowers more people with knowledge.

Of course, online courses cannot replace medical practicums, and we must not be led to believe that the accumulation of didactic knowledge can replace practice and experience. There are two ways to view this: as an obstacle that inhibits expansion of provider availability – especially the expansion of physician extenders – or as a reality that requires proactive planning to try and ensure practical alignment between provider capabilities and patient needs. And then we have to assess whether this is a phenomenon that should be addressed through public policy, and if so how.

Now throw into this mix the markedly different attitudes and perceptions of younger clinicians on the role information technology can (and should, in many of their minds) play in the future practice of medicine – and you have the makings of a public policy maelstrom. Even in the face of the recent recession, Gen Xers and Millennials still are looking at work-life balance as one of their primary concerns. While there is a lot to be said for the benefits to society in taking more time for the family and less for the fortune, I do fear the potential implications this can have if it precipitates an overreliance on the Medicine Cloud as a replacement for the Medicine Man/Woman.


Can Big Data Rescue Long-Term Care Providers?

Big Challenge
Yesterday, the
Alliance for Quality Nursing Home Care announced the release of a new study from Avalere Health, which projects a $65 billion cumulative reduction in Medicare funding of skilled nursing facility reimbursement over the next ten years. The cuts are projected to result from implementation of the Affordable Care Act’s productivity adjustment ($35.3 billion); the regulatory case-mix adjustment enacted in FY 2010 ($17.3 billion); a CMS forecast error adjustment in FY 2011 ($3.2 billion); and the sequestration provision of the Budget Control Act ($9.8 billion).

Several news sources have picked up the Alliance’s press release and noted those states with the highest levels of projected annual cuts, e.g., Florida ($370 million), California ($350 million), Texas ($240 million), Illinois ($240 million), New York ($220 million), Pennsylvania ($200 million) and Ohio ($200 million).  I don’t think the aggregate comparisons are necessarily very useful because there are a host of other considerations that should be included to truly understand the relative impact of these reductions on individual SNF providers in each of these states.  What is quite meaningful, however, is the stark reality the industry is facing: the decade ahead will see tremendous operational and economic challenges as providers try to accommodate the demographic realities of increasing demand at the very same time less resources are available to cover costs.

Big Data to the Rescue?
In the July 2012 issue of HealthLeaders Magazine Philip Betbeze writes about
Healthcare’s Big Data Problem.  Well, it’s a problem in so much as substantial obstacles still stand in the way of being able to use healthcare data more effectively – and more pointedly, to the real time benefit of operational, financial and clinical decision making.

If I could sum up that challenge it would be this: how do you take an unparalleled amount of disparate  data (e.g., demographic, operational, financial, clinical) and meld it together into a warehouse of information, such that the various elements of that information can be combined, compared and contrasted in ways that reflect and then empower the distinctive thought processes of clinicians, managers and executive leadership of healthcare organizations?

As the article points out, some very encouraging progress is being made to overcome this challenge, including something called, “natural language processing technology,” which integrates clinician notes from the patient’s EMR into the aforementioned information warehouse.  This could be a huge step forward because it has the potential to address a major obstacle sited by many clinicians: i.e., the ability to effectively capture and later be able to quickly recall and share ad hoc note taking that is such a critical component of a patient’s record.

When looking at the path from data to actionable knowledge it is important to remember that data becomes information only after it has been collected, aggregated and organized.  Information becomes knowledge through analysis.  Knowledge becomes wisdom through synthesis.  Wisdom is the foundation of economically beneficial decision making.  Unfortunately, effectively navigating the winding path from raw data to informed decision making has a lot more to do with human nature and individual personalities than it does with the ability to store and manipulate binary data bits.

The Big Idea
So what does this have to do with post-acute and long-term care? As many providers are beginning to realize – and some I dare say, even accept – the economic future of healthcare delivery is going be built upon value-based incentives and risks.  Ultimately, the distinctive difference between financial sustainability and going out of business will depend on the ability of direct service and care workers – whether that is the medical director or the food service aide – to make real-time decisions that allocate the organization’s resources in ways that add value and minimize risk.

Empowering those individuals with the requisite knowledge (see above) to make those decisions more quickly, more confidently and more in alignment with the organization’s value-based mission will create competitive advantages that lead to comparatively stronger financial performance under value-based contracting and integrated care delivery models.  This is a critically important consideration to have in mind when beginning to explore potential relationships with other healthcare providers in your market. 

It is likely that many if not most post-acute/long-term care providers will have to link into and utilize the Big Data solutions of more formidable acute care organizations.  In doing so, PA/LTC organizations must be in a well-informed position so that they can clearly articulate how such solutions must serve them and their direct service and care workers as a prerequisite to their adding value to an integrated delivery network.  It fundamentally has to be a core element of the negotiating process.

So my advice to the leadership of PA/LTC organizations is straight forward: if you don’t yet realize and understand the impact that emerging Big Data solutions will have on how well you are strategically positioned to compete in a value-driven world of healthcare delivery and integrated models of care – learn quickly.  Or, as an alternative, find someone you trust who does – and listen to them.

That’s what I think, anyway.  Would love to hear what you think!

  ~ Sparky

Don’t Let Data Get in the Way of Good Judgment

There was an interesting article in the April 2012 issue of Harvard Business Review (Good Data Won’t Guarantee Good Decisions, by Shvetank Shah, Andrew Horne, and Jaime Capellá) that I think has relevancy to post-acute/long-term care providers.  Specifically, insights there can be useful in better understanding the significant clinical and operational challenges associated with developing the type of IT infrastructure that will help those organizations demonstrate real value as participants in integrated care delivery models.

About the Article
The authors are part of the leadership team at the
Corporate Executive Board
and they share some of what was learned through development of a proprietary tool used to assess the ability of employees to, “find and analyze relevant information.”  They call this the, Insight IQ, and through researching 5,000 employees at 22 global companies they stratified those employees into three types:
     Unquestioning Empiricists: Trust analysis over judgment
     Visceral Decision Makers: Go exclusively with their gut
     Informed Skeptics: Balance judgment and analysis

They argue that the Informed Skeptics are, “best equipped to make good decisions,”  but that only 38% of employees – and 50% of senior managers – fell into this group. Their research also uncovered four problem areas that represent obstacles to achieving better ROI on IT expenditures to develop data analysis:
     Analytical skills are concentrated in too few employees
     IT needs to spend more time on the “I” and less
on the“T”
     Reliable information exists, but it’s hard to locate
     Business executives don’t manage information as well
they manage talent, capital and brand.

Implications for PA/LTC Providers
As I have written in this space previously (and in other publications), PA/LTC providers face a challenging Catch-22 with respect to Information Technology: how to make prudent investments that position them to be competitive in a world of integrated care delivery without subverting scarce resources during a period of tremendous financial pressure.  In making such investments it is critically important to fully understand and anticipate how future IT functionality will enhance clinical and operational capabilities.

To really create demonstrable value as part of an integrated care delivery network it will not be sufficient to collect, assess, analyze and report data collected through an EHR/EMR system.  Those providers seeking to gain a distinct competitive advantage through IT capabilities will also need to demonstrate how their IT infrastructure supports tangible achievements, e.g., greater patient activation, operational efficiencies and improved productivity, higher stakeholder and constituency satisfaction scores and lower rates of hospital readmissions.

As I wrote in my recently published white paper: Strategic Planning and Positioning for Healthcare Reform,
     Data becomes Information when it is organized
     Information becomes Knowledge when it is analyzed, and
     Knowledge becomes Wisdom when it is synthesized.

The stakes are very high for PA/LTC providers entering the new world of integrated care delivery.  IT investment is a foregone certainty of participation – and with that comes the tremendous risk of not achieving the necessary ROI.  As the article points out, “investments in analytics can be useless, even harmful, unless employees can incorporate [those analytics] into complex decision making.”

And there are few industries where the complex decision making of employees carries as much importance (and risk) as in healthcare.  When developing your organization’s IT Strategy, therefore, it is very important to do so in a way that sufficiently recognizes and incorporates operational and clinical understanding.

Policy Implications
There is a lesson here, too, for public policy initiatives seeking to drive wider adoption of Evidence-Based Healthcare (EBH) and Evidence-Based Medicine (EBM). Direct caregivers – and in particular physicians – are being pressured to make greater use of EBH/EBM.  We see this in the regulatory platform of the Shared Savings Program (i.e., Medicare ACOs).  We see it in how the Insurance Exchanges are being built.  And we see it in how Minimum Essential Benefits have been defined.

I believe most physicians rightly view themselves as Informed Skeptics: balancing available data with their practice experience.  I think where very often a policy disconnect occurs is when physicians try to paint policymakers with the broad brush of being Unquestioning Empiricists: seeking to supplant physician judgment with mandated decision trees.  In response (retaliation) then, policymakers will often argue that physicians’ Visceral Decision-Making is used as a cover for the economic benefits of fee-for-service based medicine.

Of course, reality as usual, lies somewhere in the middle – beyond the interests of political campaigning.  I have always argued against mandated third-party protocols (i.e., those not created and implemented by healthcare providers) because I believe the Visceral Decision Maker brings more to the table than the authors’ research necessarily implies.  I am mindful of Malcolm Gladwell’s book, Blink, in which he explains the importance of rapid cognition and intuition – and how these capabilities are based on a lifetime of experience that exists in our subconscious.

But the key takeaway here, from a policy perspective, is the importance of going beyond the “data,” which constitutes the evidence in EBH/EBM, and understanding how data will (can) be used in provider decision-making.  The same caution that applies to organizations of being at risk of data getting in the way of good decision making thus applies equally to the development of effective public policy.

What do you think?

  ~ Sparky



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