Real-Life Lessons in Intelligent Patient Safety Execution: 4 Takeaways

Better, safer care can no longer be an aspiration for healthcare organizations. It must be an operational reality. 

Fragmented data, underreported events, and breakdowns in system design still cause preventable harm. Collaboration and responsible AI can help close the gap between patient safety priorities and execution. 

During a recent Leading Voices of Care webinar, RLDatix executives and customer SCA Health shared four actions for safer, more reliable care with leaders from more than 350 healthcare organizations. 

1. Connect patient safety insights through a platform approach 

According to a CHIME survey with RLDatix, three out of four healthcare leaders say too many tools slow response and resolution times and affect patient safety. It’s one reason more organizations are moving to a platform approach. 

RLDatix CEO Dan Michelson described this shift as a “mega trend” in healthcare. 

"All of our customers are moving in that direction,” he said. 

When tools work in isolation, teams piece information together instead of acting on it. More than 100 organizations have moved to the RLD360 Platform, connecting safety applications with cloud computing and advanced analytics that surface insights faster. 

"That’s really what safety and event and risk management is all about: bringing those incidents to the collective experience so that both you and maybe others can learn from them,” Michelson said. 

2. Lean into peer-to-peer learning around patient safety 

Lasting patient safety improvement doesn’t come from a platform alone. Real change happens when partnership and platform align to raise the standard of care, including partnership among peer organizations. 

That’s why RLDatix created a Customer Center of Excellence, where customers share real-world priorities and pressure points. 

"We’re bringing together about 15 of our top strategic customers in a focused learning community to help us think more deliberately about what the future of safety workforce and operations looks like,” said Kimberli Corcoran, MSN, RN, NE-BC, executive director of the RLDatix Customer Center of Excellence. 

The same thinking drives the RLDatix Safety Institute, an AHRQ-listed Patient Safety Organization (PSO) that uses AI to turn healthcare safety data into actionable insights and reports. 

3. Involve frontline teams in safety system design 

SCA Health, one of the largest ambulatory surgery center providers in the U.S., worked with RLDatix to customize risk event reporting for the surgical setting. Nurses, technicians, and clinicians helped design it to fit surgical workflows. 

"We really wanted to become a quality system where we were capturing not just patient falls, [but] all deviations of the norm, the generators, the professional conduct, all the things, and that has become part of our culture as a result,” said Lisa Sinsel, MSN, RN, vice president, Clinical Quality, SCA Health. 

Since 2016, SCA Health has built a systemwide culture of safety improvement and near-miss reporting. It cut reporting time by three to five minutes per event and deployed near-real-time safety insights across facilities, helping prevent recurring errors. An optimization committee uses end-user feedback to strengthen operations. 

"We started using our data to learn, and what we were learning was where we could spend more of our time mitigating the risk,” Sinsel said. “We started to develop proactive risk assessments in RLDatix based on where we were seeing outcomes.” 

The approach has sustained improvements for more than a decade and earned SCA Health the 2026 RLDatix Excellence in Implementation Award. 

4. Use AI to uncover why patient safety events happen 

The greatest promise of AI in patient safety isn’t faster analysis. It’s a better chance to prevent harm in the first place. 

"We have to get away from being able to identify when something happened to being able to figure out why it happened in order to get ahead of it,” said Barbara Staruk, chief product officer for RLDatix. “We’ve talked about that as an industry for a long time. Now, we can finally do it.” 

The barrier isn’t commitment. It’s scattered data. 

"Healthcare’s safety ecosystem is fragmented,” said Richard Jarvis, chief technology officer for RLDatix. “Incident data sits in one system, staffing in another, credentialing in a third, and no one sees the whole picture until something goes wrong. AI can’t fix what it can’t see. Connecting that data is where prevention starts.” 

RLDatix is closing that gap by bringing AI across its connected ecosystem, informed by more than one million safety events from 600 organizations. That scale helps surface patterns a single organization might miss. This changes how organizations capture, understand, and act on risk. 

Capture more events with less burden 

Staff report events through a simple conversation, which means more reports with richer detail. 

See risk while it’s emerging 

The Safety Command Center brings critical signals into one view, flagging emerging concerns, putting serious events first, and surfacing overdue reviews and root cause analysis actions. 

AI has to meet the same standard as the care it supports. RLDatix tests, governs, and monitors its AI with the same rigor customers apply to patient safety, so leaders can trust both the insight and the action it drives. 

The result is patient safety that moves from looking back to looking ahead, protecting patients and the people who care for them. 

Find out more 

The RLD360 Platform has become the standard for patient safety innovation. Explore the Leading Voices of Care series to hear more.

FAQs 

What is intelligent patient safety? 

Intelligent patient safety combines connected data, technology, analytics, and human expertise to identify risk, learn from safety events, and act earlier to prevent harm. 

How can connected data improve patient safety? 

Connected data gives healthcare teams a fuller view of safety, risk, workforce, and compliance information. This helps organizations spot patterns, prioritize concerns, and make informed decisions. 

Why should frontline teams help design patient safety systems? 

Frontline teams understand clinical workflows and the barriers to reporting. Their input makes systems easier to use, increases adoption, and improves the quality of information collected. 

How can AI support patient safety? 

AI can simplify event reporting, identify emerging risks, and prioritize events that need attention. In healthcare, it must be tested, governed, and monitored carefully. 

What is peer-to-peer learning in patient safety? 

Peer-to-peer learning lets healthcare organizations share experiences, challenges, and effective practices, so they can apply collective knowledge rather than learning in isolation.