MIT Professor says to lower one's expectations
For those healthcare leaders hoping that AI will deliver extraordinary improvements in the notoriously complex and cumbersome operations of hospitals and health systems, do not read the October 2 interview by Bloomberg staff writer Jeran Wittenstein with MIT Professor Daron Acemoglu. Warning: I am going to summarize his key points here. You can also see the article here.
Professor Acemoglu is quick to say he is not hostile to AI; only that he thinks it is overhyped as the solution to all that ails business, industry, government, etc. As Wittenstein writes, according to Acemoglu, "only a small percent of all jobs — a mere 5% — is ripe to be taken over, or at least heavily aided, by AI over the next decade. Good news for workers, true, but very bad for the companies sinking billions into the technology expecting it to drive a surge in productivity.
“A lot of money is going to get wasted,” says Acemoglu. “You’re not going to get an economic revolution out of that 5%.” [emphasis added]
Wittenstein goes on to say that Acemoglu imagines 3 potential scenarios for how the relentless enthusiasm for AI will play out in the coming years.
"The first — and by far most benign — scenario calls for the hype to slowly cool and investments in “modest” uses of the technology to take hold.
In the second scenario, the frenzy builds for another year or so, leading to a tech stock crash that leaves investors, executives and students disillusioned with the technology. “AI spring followed by AI winter,” he calls this one.
The third — and scariest — scenario is that the mania goes unchecked for years, leading companies to cut scores of jobs and pump hundreds of billions of dollars into AI “without understanding what they’re going to do with it,” only to be left scrambling to try to rehire workers when the technology doesn’t pan out. “Now there are widespread negative outcomes for the whole economy.”
The most likely? He figures it’s some combination of the second and third scenarios."
Meanwhile, I have read elsewhere that an estimated 80-90% of hospital leaders say they plan to invest in AI for their organization by 2025. That's a stunning rate of adoption. But before rushing out to purchase the latest hyped AI solutions, healthcare leaders would do well to take into account Professor Acemoglu's admonition.
As previously noted, my colleague, Paul DeChant, MD, MBA and I are not hostile to AI; indeed, we can see its tremendous potential to reduce the "administrivia" burden on clinical staff, create more flexible scheduling options, enhance supply chain management, improve coding and streamline revenue cycle management. Our caveat is two-fold: first, make sure one first identifies, analyzes, and fixes problematic workflows BEFORE a particular AI solution is introduced to that workflow. Second, make sure the end-users -- especially for AI solutions intended to help front-line clinicians -- are deeply involved in the selection and testing processes.
Solutions for Hospitals, Health Systems, and Medical Group Practices: Leadership-Driven Changes
The locus for curing clinician burnout and staffing shortages runs through the C-suite. Here are examples of leadership-driven changes to the workplace that my colleague Paul DeChant, MD, MBA and I often recommend:
>Regard clinicians as knowledge workers who are given significant latitude to make clinical decisions without unnecessary administrative encumbrances or delays
>Consistently apply one or more of the improvement sciences (Lean, Six Sigma, operations research, agile, design thinking) in consultation with front-line staff to improve workflow and reduce delays, waste, inefficiency, and job skill mismatches
>Expect all leaders, but especially senior executives, to do periodic job shadowing of front-line staff (where observing and deep listening are emphasized) in lieu of "rounding" (a largely ineffectual, if widely practiced activity)
>Create and require leader standard work (LSW)
>Develop and deploy a sophisticated, deeply ingrained, and rigorous daily management system (DMS) supported by visual display boards or monitors
>Judiciously invest in AI/ML solutions -- selected, tested, and endorsed by front-line staff -- that eliminate or at least markedly reduce data entry, administrative requirements, and/or repetitive tasks that are non-value add
>Support near-continuous optimization and remediation of the EHR (there's no such thing as "it's all set")
>Get rid of superfluous or outdated policies, procedures, redundant approvals, and other stupid stuff (GROSS)
Ready to transform your hospital or workplace?
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