Artificial intelligence (AI) is making ‍meaningful inroads in healthcare, and not just in‍ radiology ⁣and clinical documentation. Experts say chief information officers (CIOs) should prioritize automation in document management ⁤and operational workflows to drive efficiency and reduce staff workload.

One expert, McMillin,‍ stated that AI can revolutionize administrative processes, ensuring critical information⁤ flows efficiently throughout ‍healthcare⁤ organizations. This includes automating the movement of documents, which eliminates bottlenecks and reduces delays.

Health systems manage large volumes ⁤of unstructured content, such as medical ⁣images, referral packets, consent forms, and financial documents. AI, including generative AI and agentic⁤ AI, offers opportunities to improve efficiency in these areas.

According to McMillin, AI can automate document routing, optimize⁢ prior authorization, streamline self-care referrals, and accelerate claims processing. By integrating AI into these workflows, hospitals can reduce administrative burdens and allow staff to concentrate on more critical tasks.

A significant ⁣barrier to AI adoption is awareness. Many front-line staff members are unaware of AI’s potential to enhance their workflows. Technology leaders must take the⁢ initiative to demonstrate these possibilities.

McMillin suggests that CIOs ⁤don’t need to be ⁣workflow experts but should understand AI’s potential ‍impact on operations. Piloting AI-driven process improvements in areas like medical record processing or prior authorization workflows can be a good starting point.

Health systems using AI sandboxes—secure environments for experimenting with AI models—are already seeing positive results. The more CIOs and their teams‍ engage with these tools, the faster they⁣ can deploy meaningful improvements.

Keeping up with AI advancements⁣ can be challenging. McMillin advises leveraging trade shows, vendor partnerships, and internal champions to stay informed. Delegating research to team members from IT, clinical applications, or health information management (HIM) can⁤ also help.

However, McMillin cautions that poor data quality remains a significant ‍hurdle. AI is⁣ only as ⁤good as the ⁤data it uses. Health systems must invest in data governance to ensure consistency and accuracy.

Organizations ‍that proactively manage their data will gain a competitive advantage, enabling them ⁢to deploy AI solutions more quickly and effectively. AI’s effectiveness is directly tied to the quality of structured and unstructured data within a health system.

Frequent⁢ changes to workflows can frustrate clinicians and administrative staff. Health systems need structured interaction plans for AI⁢ rollouts, ensuring‍ that users ⁤understand updates and how ‍they improve workflows.

McMillin notes that ⁤AI’s most impactful applications are often those that remain invisible‍ to users, streamlining processes⁢ without requiring behavioral changes from staff.

health system CIOs should invest time in understanding AI’s impact beyond clinical settings.⁢ Those who take the initiative now ⁢will create efficiencies that benefit their ⁣entire ⁢association.