Artificial intelligence (AI) is revolutionizing the healthcare landscape as we speak. Its extraordinary potential to streamline processes, sharpen decision-making, and improve efficiencies is becoming increasingly evident. And its impact on safety leaders is no exception. 

While much of the conversation has centered around rapid technological and futuristic innovations, its most profound effects may also be seen and felt in the day-to-day work of improving patient safety by improving  data quality and, empowering safety leaders to make more informed decisions, anticipate risks earlier, and develop stronger interventions.

A seat at the governance table 

Healthcare safety leaders must first recognize their essential role in AI governance. Robust governance frameworks ensure AI tools are aligned with clinical priorities, ethically and safely deployed, and focused on measurable improvements. AI governance requires collaboration across departments, including IT, compliance, quality, and safety, and clinical leadership. As safety leaders, we must champion patient safety as a cornerstone of AI integration, ensuring that AI is both designed and implemented safely, and monitored for unintended consequences like bias or privacy violations.

Transforming the work of safety teams

AI offers several powerful opportunities to refine healthcare processes and amplify impact.

• Safety event reporting: AI can facilitate event reporting for the front-line reporter by suggesting severity and event classification. AI can also analyze the text of safety event reports, identifying trends, patterns, and themes without relying solely on coded fields. This is especially helpful where safety data are lumped into broad categories for event type, such as “other.”
• Event detection: Voluntary safety event reporting only finds 5-15% of safety events. By mining electronic health records (EHRs) and patient experience survey comments, AI can identify safety events of harm that go unreported. For example, diagnostic errors are often hidden and not identified with usual approaches. AI-facilitated event detection will ultimately lead to more accurate measurement of patient safety harms as well as help with prioritization of where to focus.
• Cause analysis: AI can analyze past events to uncover causal factors and recommend stronger corrective actions. For example, if a patient has a medication error, AI can search through past safety events and root cause analyses to identify similar cases and what was done to address them. This could help safety team members better identify strong actions that work as well as actions that didn’t work and to avoid déjà vu events.
• Chart review and abstraction: AI’s ability to synthesize information from medical records will streamline case reviews, mortality reviews, and quality measure reporting. Ideally, it will also free up time for more focus on improvement.
• Safety risk identification: Prediction tools can detect sepsis, adverse drug events, falls, and patient decompensation. These tools sift through vast quantities of data to identify patterns and risk factors in real time, so caregivers can intervene earlier and, in the process, reduce patient harm. As a result, healthcare leaders focus on proactive prevention instead of reactive problem-solving or “spot treating” safety issues.
• Driving patient engagement: Tools designed to improve communication and health literacy are making it easier for patients to navigate their journeys through the healthcare system. AI can analyze patient comments and feedback, uncovering hidden themes related to safety and opportunities for improvement. By leveraging AI-mined insights, safety leaders can create more patient-centered strategies to improve patient safety.
• Reducing third victim syndrome: Third victims are those who experience psychosocial harm due to indirect involvement in an adverse event. AI can streamline data analysis, identify risks faster, drive improvements, and lighten the administrative load—all ways of making safety staff more effective in their roles and, as a by-product, alleviate what’s known as third victim syndrome.
  

AI in healthcare: A path forward

We’re at a pivotal moment. AI unlocks immense capabilities that go far beyond streamlining processes and accelerating time from insight to action. It puts the power in our hands to strengthen human connections in an increasingly digital world. We’re already seeing the tremendous strides AI is making in addressing some of the most pressing safety issues. And it will only accelerate from here.

For safety leaders, this is both an opportunity and a call to action. By embracing AI thoughtfully and strategically, we can make care safer, more efficient, and more human-centered. The future of healthcare leadership isn’t just about keeping up with technology—it’s about harnessing it to create a better system for patients, clinicians, and organizations alike.

At Press Ganey, we’re embedding AI into our solutions and core capabilities, including our high reliability platform (HRP), Patient Safety Organization (PSO), and patient comment analysis. These innovations will help healthcare leaders proactively identify trends, predict risks, and deliver safe, higher-quality, and more compassionate care.

To continue the conversations around artificial intelligence and safety in healthcare, reach out to a member of Press Ganey’s safety team.