Artificial intelligence (AI) solutions can reduce administrative headaches for nurses and clinicians and offer them more time for actual patient care. The technology can automate documentation and administrative tasks like scheduling, so shifts aren’t over- or understaffed. It can provide clinical decision support using relevant, evidence-based information. And robotics can physically assist nurses with medication administration or mobile patient transfers to reduce burden, promote safety and enable clinicians to focus on higher-value tasks.

Those are just some of AI’s selling points. But not all nurses are buying it.

Issues around ethics, transparency and perhaps fear of the unknown are holding back hospitals who have or plan to invest in AI and machine learning solutions. Healthcare leaders see the benefits, but those benefits aren’t being adequately conveyed to the biggest beneficiaries.

“We jump, we create, we develop, we have our third-party people, we buy and then we implement right to the point of care,” said HIMSS Clinical Informatics Advisor Whende Carroll, MSN, RN, NI-BC, FHIMSS. “But we are not really explaining to nurses what is happening and what we’re doing — the purposes of the technology and the intelligence that it has.”

Carroll observed that nurses and clinicians rely on evidence-based decisions and anticipate tangible evidence of AI's efficacy. Historically, AI and machine learning have primarily served analytical purposes, traditionally associated solely with data scientists.

However, frontline healthcare workers directly benefit from the clinical utilization of analytics, leveraging its pattern-recognition capabilities to monitor disease progression, treatment efficacy and patient responses to interventions. Additionally, AI optimizes acute-care operations by assessing patient flow across organizations, facilitating efficient staff and resource allocation.

Addressing patient flow bottlenecks greatly satisfies nurses, who struggle with optimizing scheduling and resource management to deliver care most effectively in real time, she emphasized.

“Nurse informatics can really promote adoption, but it requires a multifaceted approach,” Carroll said. That includes finding the root causes of challenges and educating clinicians and nurses with practical, not technical, language.

Hospitals and health systems also must pay more attention to transparency, oversight and governance when introducing AI into facilities and workflows. “We need to understand AI processes and outcomes, the inputs and the outputs and ensure that we are all part of how we evaluate those things,” she pointed out. That includes addressing ethical concerns around privacy, bias, accountability and fear of dehumanizing patient care.

Informaticists play a role in helping AI gain traction among healthcare practitioners, especially those with limited tech literacy skills.

“One of the things that we can do is promote the benefits of AI and highlight the advantages of it — like how it improves outcomes and workflows for nurses,” Carroll said. She suggests starting with touting efficiencies gained from automating administrative tasks like scheduling, incorporating natural language processing in documentation and optimizing patient admission and discharge processes. Even robotics now play a growing role in reducing nursing’s physical demands with machines that deliver medications and help with patient mobility.

“I believe AI is going to transform roles,” Carroll said, “so we can have the right resource allocations that enhance patient experience and outcomes and give clinicians more time to spend with patients doing the things that they should be doing, rather than tasks that overload them.”