As a nephrologist, many patient encounters were initiated by “the numbers.” And, like many of my colleagues, I enjoyed figuring out why the numbers were the way they were. These days it seems like the numbers are prominently featured in the news every day. I am going to ignore the political numbers and concentrate instead on the pandemic numbers. Every morning my news sources report a variety of statistics, like 410,000 deaths, 16% positivity rate, and so forth. I understand the intention is to inform the public about the state of the nation in the midst of the pandemic, but are we having the desired effect? Clearly, some news outlets are beginning to worry people are becoming numb. Recently mortality numbers have been compared to the U. S. combat deaths in WWII to give people some sense of proportionality. On the other hand, The PBS Newshour presents five obituaries every Friday to make the numbers more personal, and hopefully more real. Clearly, giving people a sense of the scope of the problem requires more than just reporting the numbers, but I admit to not knowing the most effective strategies.
In 2013, Cukier and Mayer-Schoenberger published an article entitled “The Dictatorship of Data.” The paper was a case study of Robert McNamara, who was a young Harvard Business School Professor who was appointed to Statistical Control team at the Pentagon during WWII. This team not only helped improve acquisition and distribution of materiel, it also trained a generation of people who moved into business after the war.
“McNamara was a numbers guy. Appointed U. S. Secretary of Defense when tensions in Vietnam rose in the early 1960’s, he insisted on getting data on everything he could. Only by applying statistical rigor, he believed, could decision-makers understand a complex situation and make right choices. The world in his view was a mass of unruly information that—if delineated, denoted, demarcated, and quantified—could be tamed by human hand and brought under human will. McNamara sought Truth, and Truth could be found in data. Among the numbers that came back to him was the “body count.””
The authors point out the body count was reported daily and seen as a marker of how the war was going, even by critics. Yet a survey of general officers yielded only 2% who thought the number was a useful way to measure the war’s progress or lack thereof. After considering other situations, they note the modern version of “the numbers” is Artificial Intelligence, yet another attempt to reduce unruly reality to order.
“Big data will be a foundation for improving the drugs we take, the way we learn, and the actions of individuals. However, the risk is that its extraordinary powers may lure us to commit the sin of McNamara: to become so fixated on data, and so obsessed with the power and promise it offers, that we fail to appreciate its inherent ability to mislead.”
Recently, Annalisa Merelli reported on the failure of Haven, the joint venture among Amazon, Berkshire Hathaway, and JP Morgan Chase to form a new healthcare organization designed to disrupt healthcare in the process of caring for their combined 1.2 million people spread around the country. Her conclusions:
“’Haven is yet another cautionary tale to outsiders that hope to disrupt the industry that their ambition is likely unrealistic and that solving key industry problems proves to be far more difficult than most anticipate,’ says Jeff Becker, an analyst at Forrester. By folding, Haven reduces hope in the possibility that private enterprise might fix US healthcare. And it leaves behind a loaded question: if some of the smartest, richest, most knowledgeable, well-connected, and ambitious leaders in the room could not find a way to disrupt American healthcare, who can?”
The reporter’s question may be accurate, but you can make a sure bet that others will try and some will lead with “the numbers.” Yet anyone with clinical experience knows the numbers, while useful in some instances, do not give a complete picture of a messy reality. As an example, I can collect data showing how an individual clinician decides clinical problems on average, but I cannot predict how he/she will decide to act in the next patient seen. I call this the Heisenberg principle of clinical medicine—the act of measuring something distorts the current reality. As another example, the health care needs in rural West Tennessee may be substantially different than in inner city Memphis, not to mention in suburban Nashville’s Williamson County. Certain principles apply, of course, but the details are likely to vary more than “the numbers” would predict.
So, is there any hope? I think the answer is yes, but it requires coming to agreement on certain questions. Do we want to continue to have dual funding—government for old and poor people and private for working people? Do we want to have the system built on a governmental model—regulatory, bureaucratic, but capable of having social equity built in—or a private model—flexible, efficient, and carefully avoiding too many “loss leaders?” Do we want clinicians who are obliged to do their best for individual patients or for “society?” If so, how do we decide and how much variation is tolerable?
None of these questions is simple and none, in my view, have a right or wrong answer. But the implications for how people and their systems behave are significant. These questions are therefore inherently political. As such they can be subject to polarization, demagoguery and exploitation for ends other than healthcare reform. But until we resolve the tension between treating clinical realities and maximizing revenue, we are going to continue to muddle. And maybe that is okay, too.
25 January 2021
 Cukier K, Mayer-Schoenberger V. The Dictatorship of Data. MIT Technology Review. 31 May 2013. Accessed 30 November 2020 at https://www.technologyreview.com/2013/05/31/178263/the-dictatorship-of-the-numbers.
 Merelli A. Why Jeff Bezos, Warren Buffett, and Jamie Dimon Gave Up on Their Venture to Disrupt US Healthcare. Quartz, 6 January 2021. Accessed 7 January 2021 at https://qz.com/1952225/why-amazon-berkshire-hathaway-and-jpmorgans-haven-failed/
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