Can Agile Implementation Take Evidence-Based Care From the Journals to the Front Lines?

Sidney and Lois Eskenazi Hospital in Indianapolis, Indiana. Photo courtesy Wikimedia Commons user Momoneymoproblemz. Photo has been cropped for size.

Malaz Boustani, MD, MPH, could’ve just moved on. In about 2000, he and his colleagues in Indianapolis developed a coordinated care model for dementia patients. They ran a randomized control trial on the program and published a paper in JAMA in 2006. It concluded that “collaborative care for the treatment of Alzheimer’s disease resulted in significant improvement in the quality of care and in behavioral and psychological symptoms of dementia among primary care patients and their caregivers.”

Then Boustani briefly pivoted to another focus. He’d gotten published in a major journal and been promoted for it. Those are pretty much the main goals of academic research, right?

“We are judged on a misaligned incentive of publishing a paper, but not on ensuring that our methodology is being used,” Boustani told Healthcare Analytics News™ in a recent interview. “My dean will reward me if I get a grant and if I publish a paper, he or she doesn’t reward me for how many lives I change and how many people use the solution.”

Because of that misaligned incentive, it takes years—he says, on average, 17—for evidence-based care solutions to make it to the front line of healthcare. He didn’t want a care solution that he believed in to live only in an academic journal.

So he got to work, and now he and his colleagues are back with another report, published in Journal of the American Geriatrics Society. This one, however, is about their methodology for making sure care innovations are scalable, generalizable, and someday get used in actual clinical practice.

They call it “Agile Implementation,” based on the agile software development concept from the IT world. The idea is to align program design very closely with testing to allow for continuous, real-time improvements.

Agile Implementation is an 8-step methodology, according to the new report:

1. Identify opportunities

2. Identify evidence-based healthcare services

3. Develop evaluation and termination plans

4. Assemble a team to develop a minimally viable service

5. Perform implementation sprints

6. Monitor implementation performance

7. Monitor whole system performance

8. Develop a minimally standardized operating procedure.

The authors say it allowed them to implement their collaborative care model in less than 2 years and sustain it for a decade after. Today, the model they wrote about in JAMA 12 years ago is in use at the Healthy Aging Brain Center of Eskenazi Health, a health system that operates in partnership with Indiana University.

Those minimally viable and standardized structures are meant to give end users flexibility to customize their approach while still maintaining a reliance on the core evidence that informs care. For geriatric patients, Boustani says, that’s particularly important. They have countless comorbidities and sensitivities, making it hard to lump them into one population. It was essential to be able to personalize their care.

Boustani, who is the founding director of the Indiana University Center for Health Innovation and Implementation Science and a Regenstrief Institute scientist, wants the new report to serve as a guideline for others who want to implement evidence-based care solutions on an expedited timeline.

“If you look at our healthcare delivery system, I hate to say it, but we have been stuck in mediocrity,” he said. “We had no pressure to provide great value to our patients, so no healthcare delivery systems have actual R&D in their annual operating budget.”

He says that traditionally, academic medicine operates on a limiting budget. Nearly 99% of the resources go towards discovering ways to deliver better care, with only the paltry remainder going towards publicizing and popularizing that solution.

To fight that, he has to be bilingual, speaking both the language of the scientists who are involved in finding solutions and that of health system C-suites who are tasked with implementing them. The biggest disconnect is between the scientist’s quest for certainty, which takes time to fulfill, and the executive’s desire to quickly implement improvements.

“If I had 100 bucks right now, I would spend $5 on modifying the model, $10 on really packaging it very well, $30 on partnering for distribution channels, and the rest, almost 55% of the budget, on creating market demand,” he said. “That’s how I think we have to make the model available to everyone living with dementia across America and the world.”

So far, their dementia care model is in use in Indianapolis and a few other “hot spots.” Right now, he’s exploring how that other “AI”—artificial intelligence—could be used to scale it even further. If an artificial intelligence-powered information system could inform providers 24/7 about the right care choices within their dementia coordination model, it could help popularize it—and add even more agility to the Agile Implementation process.

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