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Using AI to Help America “Buy Right” in Health Care

Posted on Thursday, March 26, 2026
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by Outside Contributor
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When I arrived in Washington in the summer of 1979, the hottest policy issue was the soaring cost of hospital care and the Carter administration’s drive to contain it. Nearly half a century later, remarkably little has changed. Health care spending still dominates fiscal debates, straining taxpayers, employers, and families alike.

Back then, national health expenditures equaled 8.4 percent of GDP. Today, they approach 18 percent and keep climbing. The structural weight of that spending on families, employers, and federal and state budgets has become too great to ignore.

The day of reckoning is coming. The only question is how hard the stop will be. Before the fiscal hammer falls, policymakers must do everything possible to ensure that we are buying right—paying for the right care, at the right price, with the right results—so that when tough choices come, less harm is done.

Four Decades of Chasing “Value”

Washington has spent decades trying to “buy right.” We’ve cycled through cost‑control strategies—HMOs, managed care, accountable care organizations, and value‑based purchasing. Each aimed to reward efficiency and outcomes. Each made progress, but none fully aligned clinical accountability with fiscal responsibility.

Studies show that low‑value care and preventable harm still waste tens of billions of dollars annually. Despite vast reporting systems, the health sector measures more than ever but still struggles to measure what truly matters: beneficial outcomes for patients.

Over my years on Capitol Hill and later with the hospital industry, I’ve spent much of my career focused on improving the quality and safety of care. Yet looking back, I fear there’s not as much to show for that effort as one would like. We had the right intentions and often the right ideas, but not the right tools.

The modern quality movement began in the late 1980s and 1990s, as hospitals began tracking performance more systematically. The Institute of Medicine’s 1999 To Err Is Human report estimated up to 98,000 preventable hospital deaths each year. Its 2001 sequel, Crossing the Quality Chasm, outlined six goals for high‑quality care: safe, effective, patient‑centered, timely, efficient, and equitable.

Since then, Medicare and private payers have expanded reporting and pay‑for‑performance models. Yet much of what’s measured still tracks compliance and processes, not true outcomes. Even when data on hospital performance is available to the public, it often arrives more than a year after the fact — far too late to influence purchasing or patient decisions.

Where AI Can Finally Help

Artificial intelligence offers a path to make “buy right” more than a slogan. Properly used, AI can turn quality reporting from bureaucracy into real‑time accountability.

AI can sift through vast clinical data, identify wasteful or risky patterns, and flag safety threats before harm occurs. It can shorten feedback loops, make transparency actionable, and clarify which interventions really improve outcomes. For policymakers, this technology provides a chance to pinpoint inefficiency — protecting necessary care while reducing what doesn’t work.

Equally important, AI can help payers and providers distinguish high‑value care from low‑value care across the entire system. That capability will be crucial when fiscal pressure forces decisions about where and how to restrain spending. Smarter, data‑driven accountability can mean the difference between measured reform and blunt austerity.

Not Too Late to Act?

If we fail to link payment to outcomes now, the inevitable correction will be imposed for us—and it will be far less forgiving. Policymakers should focus on three priorities: improving how we measure outcomes, holding providers accountable for low performance, and making cost and quality data fully transparent. Most importantly, they should leverage AI and analytics to drive care improvement while making accountability practical and transparency actionable.

AI will not solve every problem in health care, but it may be our best hope to finally buy right and subsequently ensure each health care dollar delivers value for patients and the nation alike.

The ever-upward spiral of health care spending hurts everyone. The late AEI economist Herb Stein’s warning remains as true now as ever: “If something cannot go on forever, it will stop.” The task before us is to make sure that when it does, we have shaped the stop—and not simply suffered from it.

Reprinted with permission from AEI.

The opinions expressed by columnists are their own and do not necessarily represent the views of AMAC or AMAC Action.

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Carol
Carol
2 months ago

Government is the health care problem! All these politicians aren’t going to give up their power to control us! As long as government has a last say in who lives and dies, nothing will get better!

Deborah Wood
Deborah Wood
2 months ago

Get the lawyers out of the picture!
Require advertising of price!
Allow insurance companies to sell across state lines!

Kaiju
Kaiju
2 months ago

The third party payor system (insurance industry), along with government and corporatized (profit-motivated) medical establishments have all made healthcare less and less affordable. After 42 years in healthcare, I can also say that patients have done less and less to PREVENT disease, with poor food choices, dangerous hobbies, sedentary lifestyles, too much trust in government health and food recommendations, and belief in all things promulgated through the internet. There’s plenty of blame to go around. It’s too hard to tell which of these factors has had the greatest impact.

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