At Rochester, Minn.-based Mayo Clinic, tech adoption comes down to one question: Does it fit into the workflow?
“If technology adds friction, it fails,” said Edwina Bhaskaran, MSN, RN, the health system’s chief clinical systems and informatics leader.
As Mayo deploys AI at scale, Ms. Bhaskaran is helping build flexible governance models to innovate quickly while keeping culture and responsible use front of mind. In this Becker’s Q&A, she discusses where the technology is delivering results and how the organization is building trust with clinicians.
Q: You oversee more than 1,000 team members across clinical systems and informatics. How have you structured leadership, governance and culture to keep teams aligned while still moving quickly at Mayo’s scale?
Edwina Bhaskaran: At our organization, our foundation starts with our culture. We focus on our RICH TIES values — respect, integrity and compassion, healing; teamwork, innovation, excellence and stewardship — and these guide every decision that we make. We also ensure the needs of our patients come before everything else, and we feel like teamwork is the engine that makes that successful.
When you have a team that is matrixed and so large, it really comes down to leadership. My approach has always been to understand my own strengths and weaknesses and then surround myself with individuals who are complementary. It’s also about making them feel comfortable enough to say, “I don’t think you’re going in the right direction,” and provide that direction back.
From a governance standpoint, structures can’t be entirely static. They need to evolve with our organizational needs and the pace at which we’re moving. We’ve built flexible frameworks that allow for rapid decision-making while maintaining accountability and transparency, and we anchor governance back into culture and the needs of the patient.
Q: You’ve led the deployment of generative AI supporting decisions for more than 3 million patients. Where have you seen the most meaningful clinical or operational impact so far, and what guardrails were essential to earn clinician trust?
EB: My philosophy around this has been pretty simple — it starts with the workflows. Where do these tools fit seamlessly into existing workflows, and if they don’t, do they deliver such high-impact outcomes that the change required is worth it? If technology adds friction, it fails.
Ambient documentation tools have been an example where we saw accelerated adoption. We’ve learned a lot from deploying those tools — what works, what doesn’t — as well as the importance of word of mouth and end-user experience.
Ensuring clinician trust requires strong guardrails. We make sure AI-generated suggestions have clear labels and are traceable back to the source data, and we operate off a human-in-the-loop design so clinicians remain the ultimate decision-makers. We also ensure deployment is done in controlled environments before scaling and continuously monitor performance for accuracy. When we do it right, it feels like an invisible helper, not a disruptive force.
Q: Mayo’s clinical systems now process billions of data points daily. How are you translating that volume of data into actionable insights for front-line care teams rather than additional complexity?
EB: One of the ways that we do it is by engaging our care teams early and often. We believe in care team-led and decentralized innovation, not just at the point of implementation, but during development.
If the tool is going to be meaningful for our patients, it has to elicit the right action from our care teams, and that can only happen when you have them involved in shaping that from the start. It’s also not a one-and-done — it is an iterative process, and we have to constantly tweak and adjust.
The decentralized approach allows us to move faster into actionable insights, but we also look to care teams to help identify which tools we may not want to scale. When clinicians can see fingerprints of themselves or their peers in a solution, it becomes a game-changer for adoption. At that point, data becomes the catalyst not just for innovation, but for alleviating administrative burden.
Q: As a nurse leader, how does your clinical background shape your approach to informatics strategy, particularly when balancing innovation with patient safety and workforce realities?
EB: It provides an end-to-end view of our healthcare processes — from scheduling and access all the way through revenue cycle. Having that clinical and nursing background provides a sense of empathy that helps balance both the technology needs and what clinicians feel from a day-to-day perspective.
It helps drive where our priorities should be and what our areas of focus should be. The rate of change that our clinicians are currently facing is pretty high, not just from technology but from other external forces as well. Being able to understand and appreciate that helps inform how we approach innovation while recognizing workforce realities and what we may need to decommission and retire.
The post If AI ‘adds friction, it fails’: How Mayo Clinic scales technology appeared first on Becker's Hospital Review | Healthcare News & Analysis.
Source: Read Original Article
