Wednesday, October 04, 2017
The NEJM Hits A Six With A Great Article On Medicine And AI. Deeply Important Stuff To Me!
This appeared last week:
N Engl J Med 2017; 377:1209-1211 September 28, 2017
In the good old days, clinicians thought in groups; “rounding,” whether on the wards or in the radiology reading room, was a chance for colleagues to work together on problems too difficult for any single mind to solve.
Today, thinking looks very different: we do it alone, bathed in the blue light of computer screens.
Our knee-jerk reaction is to blame the computer, but the roots of this shift run far deeper. Medical thinking has become vastly more complex, mirroring changes in our patients, our health care system, and medical science. The complexity of medicine now exceeds the capacity of the human mind.
Computers, far from being the problem, are the solution. But using them to manage the complexity of 21st-century medicine will require fundamental changes in the way we think about thinking and in the structure of medical education and research.
It’s ironic that just when clinicians feel that there’s no time in their daily routines for thinking, the need for deep thinking is more urgent than ever. Medical knowledge is expanding rapidly, with a widening array of therapies and diagnostics fueled by advances in immunology, genetics, and systems biology. Patients are older, with more coexisting illnesses and more medications. They see more specialists and undergo more diagnostic testing, which leads to exponential accumulation of electronic health record (EHR) data. Every patient is now a “big data” challenge, with vast amounts of information on past trajectories and current states.
All this information strains our collective ability to think. Medical decision making has become maddeningly complex. Patients and clinicians want simple answers, but we know little about whom to refer for BRCA testing or whom to treat with PCSK9 inhibitors. Common processes that were once straightforward — ruling out pulmonary embolism or managing new atrial fibrillation — now require numerous decisions.
So, it’s not surprising that we get many of these decisions wrong. Most tests come back negative, yet misdiagnosis remains common.1 Patients seeking emergency care are often admitted to the hospital unnecessarily, yet many also die suddenly soon after being sent home.2 Overall, we provide far less benefit to our patients than we hope. These failures contribute to deep dissatisfaction and burnout among doctors and threaten the health care system’s financial sustainability.
If a root cause of our challenges is complexity, the solutions are unlikely to be simple. Asking doctors to work harder or get smarter won’t help. Calls to reduce “unnecessary” care fall flat: we all know how difficult it’s become to identify what care is necessary. Changing incentives is an appealing lever for policymakers, but that alone will not make decisions any easier: we can reward physicians for delivering less care, but the end result may simply be less care, not better care.
The first step toward a solution is acknowledging the profound mismatch between the human mind’s abilities and medicine’s complexity. Long ago, we realized that our inborn sensorium was inadequate for scrutinizing the body’s inner workings — hence, we developed microscopes, stethoscopes, electrocardiograms, and radiographs. Will our inborn cognition alone solve the mysteries of health and disease in a new century? The state of our health care system offers little reason for optimism.
But there is hope. The same computers that today torment us with never-ending checkboxes and forms will tomorrow be able to process and synthesize medical data in ways we could never do ourselves. Already, there are indications that data science can help us with critical problems.
Lots more here – and freely available at present:
To me this article makes some great points about how we will see medicine evolve to address increasing complexity and allow practitioners to continue both to function well and be invaluable to the care process. Implementation is all and in this case it will be very difficult to bring off well I believe.
Wishful thinking? I hope not. A must read.
Posted by Dr David G More MB PhD at Wednesday, October 04, 2017