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.

Cheers,
  Sparky

Clinical Technology and Social ROI

Welcome to another in an emerging series of Difficult Challenges in Healthcare brought to you today by demographic and economic realities – and the political nature of the US Healthcare Delivery System.  According to an annual industry survey conducted by HealthLeaders Magazine, roughly 21% of hospital CEOs surveyed indicated, “their organizations are cutting back on high-level, high-price technology for at least some service lines.”

This from the article, Scrutiny for Clinical Technology, wherein segments from interviews with those CEOs tells a story within a story: not just about the planned reduction in investment – but the means and methods being employed to determine such reductions.  As you might expect, capital investment decisions are being significantly impacted by exogenous considerations, such as the cost of capital (i.e., financing costs), uncertainty regarding future revenue streams and competing investment priorities driven by growing demand.

Free market advocates who believe the healthcare industry would produce greater access, quality and affordability if most of the current regulations could be taken away no doubt cringe at the prospect of investment decisions being made in reaction to conditions directly, or indirectly, caused by such regulations.  Conversely, advocates of a universal/single payer system will object to the prospect of speculative investments with unproven clinical value being made on the collateral of the revenue base they provide the industry through taxation.

Where does the balance lie between investing in new technologies that has the proven potential to save lives, or at least make those lives more productive and less painful – and investing in the infrastructure required to increase delivery capacity in anticipation of higher demand?  Demand that will be driven both by an aging population (natural), as well as implementation of the Affordable Care Act (through regulation).

Who should be making those decisions – and what are the criteria that should be used in weighing investment alternatives? Demand is going to grow substantially, so there must be investment in existing infrastructure.  At the same time, free cash flow is going to be strained to subsidize increased operating deficits caused by continued downward pressure on care reimbursement.  Caught there right in the middle will be thinner balance sheets forcing difficult tradeoffs for capital deployment.

According to the American Hospital Association, in 2010 approximately 56% of all care provided by hospitals was funded by Medicare and Medicaid.  In the post-acute/long-term care world the proportion of Medicare/Medicaid’s share is significantly more because of the higher prevalence of retirement age patients.  But the key takeaway is that a substantial amount of funding for healthcare delivery in the United States comes from public sources (i.e., society).

So shouldn’t society have a greater say in clinical technology investment decision making? If so, what would that look like? What do you think?

Cheers,
  Sparky