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The Digital Medicine Society, with support from Google Health and 30 other organizations, has announced a new playbook that aims to help hospitals and health systems craft AI implementation strategies that are grounded in the real needs and capabilities of individual providers.
WHY IT MATTERS
Many healthcare C-suite leaders are responding to "hype and pressure" to develop an AI strategy, DiMe leaders explained. Instead, the group advised: "The most strategic move is to pause and ask, 'What problem are we trying to solve?'"
Bringing AI into clinical care is complex, and gambling on fragmented pilots and poor change management efforts can waste an organization's time and resources while eroding trust or increasing patient risks, according to DiMe.
"Decision-makers must weigh risks and benefits with limited evidence, clinical leaders face the challenge of integrating disparate tools into existing workflows, and technical teams must find ways to scale innovation without compromising accessibility or patient safety," the organization said in its new AI implementation playbook.
To help providers maximize the value of AI for clinicians and deliver better outcomes for patients, the playbook is organized into three sections:
- An assessment with checklists and other tools that aid providers in identifying the operational and clinical pain points and measuring their AI readiness.
- Resources to help evaluate and select AI tools that align with care delivery needs.
- A deployment framework that addresses the elements of successful tool rollout, AI governance, training and monitoring.
Ultimately, DiMe said that the AI implementation playbook can guide health IT strategy leaders, such as chief medical information officers, in balancing clinical priorities, financial sustainability and enterprise alignment when making decisions, and help clinical leaders assess how AI deployments will impact workflows, training and patient safety.
"This playbook offers the guidance health leaders need to move from experimentation to responsible adoption at scale," Pete Clardy, senior staff clinical specialist at Google for Health, said in a statement.
Because technical leaders at healthcare organizations are often asked to add on AI without clear priorities, guardrails or resources, the framework also outlines technical requirements and explores best practices for building data pipelines, monitoring model performance in production and other key development tasks.
To name just some of the many organizations that helped DiMe develop the healthcare AI implementation playbook: American Academy of Pediatrics, American College of Radiology, American Nurses Association, Cedars-Sinai, Coalition for Health AI, Consumer Technology Association, Intel, Kaiser Permanente, Beth Israel Deaconess Medical Center, Stanford University, UPMC Enterprises, Vanderbilt University Medical Center and the U.S. Department of Veterans Affairs.
"If we don't get implementation right … I don't know what the sustainable future of the healthcare industry is and why any investor would continue to invest in healthcare AI if we cant take it to scale," DiMe CEO Jennifer Goldsack said at the playbook launch event last week.
THE LARGER TREND
DiMe's mission is to support health systems, providers, patients and the general public to advance digital health transformation.
Last year, the organization launched a platform to evaluate privacy, security and equity standards to make sense of an exploding digital health software and products industry, along with a DiMe Seal to indicate meeting the organization's quality and trustworthiness standards.
There were 400,000 health software applications available to consumers and 30,000 for providers, health systems and other enterprise organizations, DiMe said in a statement at the time.
While healthcare AI has only grown since that time, data and integration challenges have persisted, according to a report from Bessemer Venture Partners, Amazon Web Services and Bain & Company that was released earlier this year.
"This wave of AI adoption has been driven by 'test and learn' urgency, with boards and CEOs pushing teams to discover possible use cases," the report stated. "Mid-to-large providers are the exception, as they are early adopters with more resources to bring AI into production."
ON THE RECORD
"Seventy percent of health AI pilots fail, not because of technology, but because of people and process challenges," Goldsack said in a statement. "Without implementation, we waste a generational opportunity to make the system sustainable, and we fail to deliver at scale for every person our healthcare industry exists to serve."
Andrea Fox is senior editor of Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a HIMSS Media publication.
