Does Measuring Quality Drive Value?

businesswoman drawing diagrams on wallThe Centers for Medicare and Medicaid Services today announced release of the 2015 Impact Assessment of Quality Measures Report. Designed to relate the performance on quality measures over time, it includes research on 25 quality programs and hundreds of quality measures from 2006 to 2013.

Key findings of the report include:

Overall quality measurement results demonstrate significant improvement over time.

Race and ethnicity disparities present in 2006 were less evident in 2012.

Provider performance on CMS measures related to heart and surgical care saved lives and averted infections.

CMS quality measures impact patients beyond the Medicare population.

CMS quality measures support the aims of the National Quality Strategy (NQS) and CMS Quality Strategy.

There is an old management adage that goes, “what cannot be measured cannot be managed.” It is from this vantage that CMS advocates for the role quality measurement plays in achieving the desired goals of improved access, better outcomes and lower cost (the infamous Triple Aim liberally interpreted by me). While the data may support improvement in performance indicators, that does not necessarily translate into value.

And value is (or ought to be) the universal currency of the Triple Aim

Recall, I have shared here often that value in healthcare is defined as outcomes divided by cost – and that measuring outcomes is a bit like trying to nail Jell-O to the wall. Measuring and reporting on quality in other industries has proven to be a useful endeavor that underpins market efficiencies. It’s not the availability and use of information derived from such endeavors that I wonder about – but who uses it and how.

Consumers that are armed with information on product and service quality from organizations like Consumer Reports are better able to navigate the value paradigm and reconcile their wants and needs against affordability. But in healthcare, consumers (patients) largely still don’t get to do that regardless of how much Big Data is collected, analyzed and reported on by CMS.

Will future efforts to capture all of the nuances that influence how individuals determine the value of an outcome ever be adequately captured by Big Data analytics in a fashion that such knowledge can supplant the simple effectiveness of personal decision making in a free market? CMS is banking on it.

What say you?

  ~ Sparky

Big Data Meets the Value Paradigm

VDO-Option3FlatA little over a year ago I shared a post on healthcare pricing: Pick A Price, Any Price. I wrote about the challenges, difficulties and consequences associated with the frustrating disconnect between hospital charges and the actual costs of proving care in those hospitals. At the time I also referenced the work of Michael Porter and Robert Kaplan that was published in the Harvard Business Review article, How to Solve the Cost Crisis in Healthcare.

I am excited to share with you research inspired by that article that was recently completed at the University of Utah, spearheaded by Dr. Vivian Lee, the senior vice president for health sciences and Dean of the University of Utah School of Medicine. Highlights of the research were published in the article, Hospitals Are In the Hot Seat, on the University of Health Sciences’ Algorithms for Innovation web site.

In a nutshell, colleagues representing several industry disciplines worked together to explore how harnessing Big Data and applied research might help empower patients and healthcare providers with more timely, more reliable – and most importantly, most understandable cost information and how costs compare to care received and outcomes achieved.

We’re all familiar with Peter Drucker’s challenge that, “if you can’t measure it, you can’t manage it.” Though less famous but probably more meaningful – or at least pragmatic – was Drucker’s quote that, “what’s measured improves.” Historically for healthcare trying to measure, apportion and determine meaningful costs at a granular enough level where that information has timely and impactful use has been elusive.

Here’s hoping this work is another step in the right direction.


Paging Dr. Watson . . .

Watson, the IBM supercomputer, generated world interest in 2011 when it competed on Jeopardy against former champions of the famous TV game show and won the first prize reward of $1 million.  With access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage, Watson performed without having access to the Internet.  Ever since IBM’s Big Blue beat Gary Kasparov in 1997 IBM has doubled down on its passion for developing technology that seeks to mirror the capabilities of the human mind.

Now that passion is taking Watson into the hospital and physician office. A February 11, 2013 article in Wired Magazine UK, IBM’s Watson is better at diagnosing cancer than human doctors, describes how IBM is partnering with Memorial Sloan Kettering Cancer Center in New York and Wellpoint to make Watson available (i.e., for a fee) to any hospital or clinic seeking its input on oncology cases, including proposed treatment protocols that seek to minimize cost.

The big advantage Watson has over human doctors is its ability to absorb and analyze enormous quantities of data – and then make that knowledgebase more accessible and more affordable.  As example, according to Sloan-Kettering, only 20% of the knowledge doctors use in diagnosing patients relies on trial-based evidence.  But it would take at least 160 hours of reading a week to keep pace with all of the medical knowledge being published – and that doesn’t include the time it takes to determine how to apply that knowledge in practice. Watson’s successful diagnosis rate for lung cancer is 90 percent, compared to 50 percent for human doctors.

This subject-matter reminds me of Malcolm Gladwell’s book, Blink, in which he tackles the subject of rapid cognition: how the human mind processes environmental stimuli and compares, contrasts and analyzes that stimuli against the billions of elements of data that comprise individual experiences comprising our conscious and unconscious memories.  Watson’s ability to replicate that capability is still a long way off.  But the progress already made is fascinating.

While fascinating, practical application of technological advancements in healthcare are often challenged by skepticism. How much of that challenge is created by the natural human resistance to change, how much results from not understanding the new technology – and how much is based upon previous experiences that demonstrate the risks of adopting technology before it is fully proven – is hard to know.

A lot of faith is being put into technology as the silver bullet to address the healthcare cost crisis. When you read something like what IBM is accomplishing with Watson you want to jump on that bandwagon.  When you spend an afternoon with clinicians that share real life stories of how their ability to deliver care is being impeded by technology that was supposed to make them more efficient and productive – well, not so much.


Big Data Assimilation

In early October, I wrote a post entitled, Big Data and Brand Management.  In observing the Pub’s recent visit tracking activity that post has been getting some attention – particularly from the Netherlands.  I wish I had the time to investigate further to possibly understand why.

I do know that the subject of Big Data and Healthcare is quickly becoming one of the most intriguing – if not controversial, and to many, threatening – side shows of the big show that is Healthcare Reform and the impending implementation of the Affordable Care Act.

In the IT world this growing attention is seen as an anticipated awareness among the less informed masses to a level of consciousness they achieved over a decade ago.  But for all that foresight, there has been precious little headway made in addressing some very critical issues of access and security.  And that is because those issues are not clearly defined, have dramatic implications regarding personal privacy and must be framed within a context of assumptions about the future that are widely debatable and lacking entirely for empirical support.

There is a lot at stake here:  a huge potential for solving some very challenging social problems – yet just as great potential for infringing upon personal liberty.  While I share the justifiable concern over protecting the privacy of individual patient data and information, I believe that concern is clouding an even greater story here; and that is the alluring diagnostic trajectory that Big Data has launched us upon.

In combining Big Data (large static storage requirements) with highly complex  analytical algorithms (large dynamic memory capacity) requiring tremendous computing capacity (processing speed) what we are essentially doing is seeking to replicate and accelerate the thinking ability of the human brain.  The historically great equalizer of human intelligence has been a life’s experience.  To be sure, there are ways to broaden exposure to circumstances and events that contribute to such experience, but there is no way to accelerate the natural course of observable events, which ultimately comprise the sum total of that experience – nor the wisdom of maturity to make good use of it.

In the book, Blink, by Malcolm Gladwell, he explains the concept of rapid cognition: a fascinating treatise on how our minds instantaneously sort through and combine billions of observational data elements from our life’s experience, analyze the meaning of that data and then form a reasoned judgment about what we have just observed through our senses in a matter of a few seconds.  This is often also referred to as intuition, or a gut feel.  It’s something that has saved many lives owing to physicians’ diagnostic capabilities.

What many clinicians fear in a world of Big Data is an unproven overreliance on information technology to supplant or replace that diagnostic capability (or intuition, if you will).  While, in the aggregate, some of that concern may understandably be driven by a fear of professional obsolescence, I think the much more prevalent concern is challenging whether and when a machine will (ever) be able to truly replace the intuitive capability of the human mind.

And that really is at the heart of the longer-term Big Data dilemma, even if the focus right now is on privacy and protection.  I don’t mean to diminish such concerns, but I do believe we will ultimately be able to address those relevant concerns satisfactorily.

A much more difficult challenge, however, is assessing and understanding whether machines will eventually be able to capture the collective human knowledge and experience that clinicians currently rely upon and be able to analyze and apply that information in a way that achieves better overall patient outcomes than application of human assessment, analysis and reasoning.  And, if so, will patients be able to have access to that computing capability without needing human interface?

Then, what is the role of doctors in the future? Will there be a need for them? Will those who would have otherwise employed their talents in becoming physicians be the future engineers and programmers that work to develop, upgrade and enhance the computing capability of the new electronic caregivers?

A lot to think about.  Big Data offers a lot bigger challenges than just worrying about who owns the data.  The real concern is who is going to control the owner of the data – and how? Star Trek fans, think Borg.  Is that where we’re headed?

What do you think?


Big Data and Brand Management

Big Data: big opportunities or big problems?  While most of what I have read seeks to position this question in the context of anticipated investments in human resources and IT infrastructure, I have a different take.  I think the most critical and salient difference in determining whether Big Data has positive or negative implications for healthcare providers will depend primarily on whether and how effectively it is utilized and managed in organizational branding.

Part I ~ Implications of Big Data
In explaining this, let’s start with a look at just a few examples of where and how Big Data will impact healthcare organizations. 

Clinical and Epidemiological Research
Healthcare providers have long been cognizant of the important role that cutting edge clinical and epidemiological research plays in helping educate and prepare them to provide evidence-based care.  They are also aware of the tremendous burden that misguided and/or shoddy research creates on both their time and talents.

At a clinical level, Big Data means being able to utilize previously prohibitive quantities of biomolecular data to test relational hypotheses much faster, while at the epidemiological level it means being aware of social cause and effect relationships much sooner.  In either instance, the impact and expectations of what to do with more information at an accelerated rate will have a significant impact on healthcare providers, as well as patient-consumers.

Consumer Empowerment
There are already literally thousands of smart phone/tablet app’s available to help individuals manage there own care.  A quite natural focus among these has been to design applications targeting chronic disease management.  As the Boomer age wave grows, so too will that portion of the patient population that is not only adept but very conversant in using electronic data and information to be highly informed and highly motivated self-care advocates.

Though Big Data is by far not the only force driving greater transparency of financial and operational performance metrics from healthcare providers, it will be the catalyst that transforms those metrics from merely data to usable information – and unfortunately, probably a good deal of misinformation as well.  Providers will have to be both cognizant and vigilant in assessing how this emerging trend will impact their market positioning.

The common thread of these three examples is what I call the Acceleration of Digital Chaos©.  More data is always beneficial to the extent that it creates greater awareness, enhances education, expands knowledge – and most importantly, creates wisdom.  But as we know, more data does not always lead to such hopeful results.  It also often leads to more confusion, more frustration – and worst, more risk of making critical decisions based upon faulty analysis.

Part II ~ The Importance of Brand Management
Wherever there is chaos and confusion that grows out of attempts to address a basic human need like healthcare, so too exists the double-edged sword of opportunity and risk: the opportunity to bring clarity amidst the chaos in the form of high-value solutions, as well as the ever present risk of making things worse.  And there too lies the associated challenge of branding: opportunities to leverage Big Data in ways that can greatly enhance the value of your brand – or facilitate its disintegration into a pile ashes.

To make sure Big Data serves your brand rather than destroys it will require an active awareness and understanding of where and how Big Data will intersect with Brand Management.  Several examples of these intersections are offered for your consideration.

Social Media
Social Media continues to grow in importance and relevancy to the healthcare industry.  Enter Big Data and now you have a tremendously powerful vehicle for gaining valuable information and insights on patterns and behaviors – of both consumers and competitors.  

To the extent a knowledge advantage can be gained through use of Big Data, that information can be used to help position your organizational brand in concert with consumer demands and expectations – and before competitors achieve that positioning.  I cannot think of a more important market-oriented investment that healthcare providers can make at this time than exploring and understanding how Big Data will transform the way data collected through Social Media can be used to competitive advantage.

Quality and Integrity
Examples in Part I above highlight the likely potential where Big Data will generate tremendous personal anxiety, confusion and frustration.  Take the average consumer-patient looking at knee-replacement surgery in the year 2015.  Armed with 30 published research papers on the advantages and disadvantages of different techniques; over 50 web site addresses stored in the web browser with pages and pages of performance data on surgeons;  15 different self-help iPad applications downloaded to determine the most effective means of post-survey rehabilitation.  You get the idea.

So the ability of healthcare providers to be perceptually positioned as a trusted resource to cut through all of the confusion and frustration will create substantial market advantages.  But, importantly, those healthcare providers that are able to achieve a sustainable advantage will not only facilitate a more efficient and helpful pathway through the confusion – but they will do so while backing it up with consistently higher quality care than competitors.  The two must go hand in hand.

Data Security and Corporate Compliance
I saved the most important for last.  This is a hugely tremendous risk to brand value that will be attendant to using Big Data.  We read of examples every day where patient data has landed in the wrong hands.  The consequences of being at fault – whether real or perceived – for a breach of data privacy and protection could erase years of investment in building your brand overnight.

Yet it is reasonable and plausible that a breach could happen despite the most advanced and diligent efforts of prevention.  In such instance, the organizational fallback position must be a strict adherence to corporate compliance policies that clearly make the protection of personal data the highest priority – not only in theory but in practice.

Please note this post is not by a stretch intended to be an exhaustive survey and consideration of either the ways in which Big Data will impact healthcare, nor the numerous ways in which it has the potential to impact healthcare providers’ brands.  It is intended primarily to help leadership teams of such organizations begin to perform their own assessment of how and where Big Data can have a Big Impact on their future branding efforts.


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