AI integration strategies require patient focus, partnerships

At the HIMSS AI in Healthcare Forum in San Diego on Dec. 14, a group of panelists outlined tactical pathways to artificial intelligence adoption and investment, including how to maximize impact and decisions around adopting existing tools or building new AI infrastructure.

Anne Snowdon, CEO of Scan Health and chief research officer at HIMSS, said that determining strategic priorities and setting goals for what AI investment and implementation would achieve are indispensable first steps for any healthcare organization.

“You’ve got to look at the whole picture and what are your strategic priorities for the workforce and for the patients,” she said. “It’s also important to determine what success looks like and have the tools to measure it because, otherwise, what are you investing in, and how will you know if you achieved it?”

Albert Marinez, chief analytics officer at Cleveland Clinic, explained that a significant part of Cleveland Clinic’s strategy for deploying AI focuses on provider productivity and supporting healthcare providers’ quality of life.

“We’re thinking a lot about ambient intelligence and the clinical documentation that’s happening in real time with clinicians,” he said. “We think about the messaging, as it’s a lot of work to respond to patients who are reaching out.”

Marinez pointed out the opportunities for leveraging AI in back-end office work, where clinical coding and revenue cycle are large focus areas for Cleveland Clinic.

“We are all aware of the pressures we’re experiencing from a healthcare industry perspective,” he added. “It’s challenging, it’s expensive, and the pressures are continuing to mount.”

From the viewpoint of Chris Larkin, chief technical officer at Concord Technologies, getting started with small, manageable successes is vital to cut through the noise and hype surrounding AI.

“Very few of us actually just get to play around with technology as a full-time job, so we have to produce results,” Larkin said. “Start small, be successful and be able to show your investors exactly what the results of your work are in a matter of weeks, not months or years.”

He recommended finding projects that will gain clinical and physician sponsorship, as well as operations and financial sponsorship, adding that where an organization starts depends on its key business priorities.

“We will not be able to do this on our own. We need to partner with other organizations and industries, and many times, we don’t need to look very far,” Larkin noted. “We must develop talent internally, as AI is creating new opportunities for roles we haven’t seen before – prompt engineering is a good example.”

Thomas Hallisey, digital health strategy lead at HANYS, noted that as AI becomes more adept at interacting with patient and clinical data and develops the ability to supply healthcare professionals with the correct information at the right time, it will become necessary to design systems that store all this data differently.

“We have an entirely different view in the ER for different types of patients, for example,” Hallisey said.

Snowdon explained that healthcare providers must keep a “razor-sharp focus” on deploying AI to help every person the organization serves achieve their health goals.

“Technology is evolving far more rapidly, and we can integrate, make sense of and seamlessly flow into a clinical setting. You don’t want to nurse all the technology. You’ve got to focus on and nurse that patient, the family.” Snowdon said. “It is absolutely about the people and what those people need to achieve.”

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