AHA: Four building blocks are critical for AI in healthcare

Artificial intelligence has the potential to transform care delivery. However, hospitals and health systems will need to first build an effective AI infrastructure of people, policies, resources and technology.

That’s the contention of a new report from the American Hospital Association’s Center for Health Innovation.


“Advocates say AI technologies can improve outcomes and lower costs at each stage of the care cycle” including prevention, detection, diagnosis and treatment, according to the AHA report.

However, to realize this promise, hospitals and health systems must build a clinical AI infrastructure based on four building blocks that are critical in healthcare.

People: Hospitals and health systems will need to set up organizational charts and assign responsibilities to a group of leaders who not only will oversee the priority and execution of AI projects, but also will be accountable for their outcomes.

Policies: Given that data governance is a critical component of any effective clinical AI program, healthcare organizations will need strong policies in this area to protect the privacy and security of patient data flowing into and out of an AI algorithm.

Resources: Providers that deploy AI to improve care across the continuum will need to allocate financial resources and time to ensure that the AI-enabled solution produces the outputs expected by senior leaders.

Technology: Hospitals and health systems will need to invest in technologies that not only integrate actionable AI insights into the workflow on the front end, but also technologies that feed accurate data into AI algorithms to generate insights.

“AI-powered technologies present opportunities for forward-looking hospitals and health systems to reimagine care delivery along every step of the care continuum,” concludes the report. “With the right infrastructure, partnerships with vendors, and clinician and patient buy-in, it can help prevent disease, detect important changes in patients’ medical conditions, diagnose patients more accurately and faster, and tailor treatment plans to individual patients.”

The report also lays out strategies and tactics to overcome common barriers to AI adoption in clinical settings.

“Far and away, the biggest challenges that hospitals and health systems will face when attempting to use AI in care delivery are concerns by physicians and patients,” notes AHA.

To address patient concerns, the report recommends using AI to engage with patients on a regular basis; leveraging AI and health chatbots to connect patients with clinicians; and utilizing AI to personalize and individualize the healthcare experience.

For physicians and other clinicians, AHA advises leveraging AI to augment clinical decision-making at the point of care; using AI to manage increasingly unsustainable workloads; sharing clinical and scientific verification and valuation to confirm that the AI algorithm has been tested on a valid dataset; involving clinicians in reviewing processes, methodology, curation, integration and ethical decisions of AI systems and tools; and utilizing validated frameworks and learning from successes and failures.