Throughout the Northeast of the United States and around the world, the Mass General Hospital brand stands for high-quality healthcare delivery and outcomes and world-class research. Formerly Partners Healthcare, Mass General Brigham consists of 12 world-class healthcare facilities. John Pyhtila joins me in this episode to share how AI and advanced analytics is reshaping how Mass General Brigham both operates efficiently, often hard in healthcare delivery, and provides world-class care to patients.

Key Takeaways

Describe your title and role.

I am the Chief Data and Analytics Officer. I split my time roughly equally between outward-facing and inward-facing activities. From an outward-facing perspective, spending time with stakeholders is important for providing the business pulse of what's going on clinically and ensuring that we are delivering value. Inward-facing, my organization is growing significantly with some growing pains. The growth curve requires a significant amount of my time and focus to ensure that we are operating effectively and efficiently. I expect that after we stabilize, my time will shift towards a 75% outward-facing and 25% inward-facing.

Where does the analytics function sit in the organization and who does it report into?

I report directly to our Chief Clinical Officer, Dr. Gregg Meyer, who reports to our CEO, Dr. Anne Klibanski.

Is that the right place for the analytics function to report?

I believe it's the right place for both data and analytics to live. The Chief Clinical Officer role represents the business from both a clinical perspective and an operational perspective. I view analytics and the data to support analytics as more of a business function versus a technical function.

Describe the organizing model you have adopted for analytics.

We have a distributed model. We have centralized groups that oversee data and analytics in support of day-to-day operations—clinical and also administrative. We have groups that support the research side—the broad set of researchers that we have at the institutions. We make sure they have their data and analytic needs met. In addition, we have a core team focused on artificial intelligence (AI) to support clinical diagnosis, specifically in the radiology and imaging space. We use AI algorithms to make diagnoses more precise. Centralized, there's also an underlying IS infrastructure team. Finally, there are analysts and data resources scattered throughout different departments, and the hospitals, that use our data infrastructure to answer specific business questions. The broader analytics community numbers above 1,000 people.

What are four or five important qualities and behaviors of analytics leaders?

1. Clear vision and strategy for where the group needs to go, and ensuring that you're providing the group with proper direction.
2. Good resource management to create a diverse and inclusive team environment to get the most out of every employee and support a diverse set of ideas.
3. Collaborative and good communicator because analytics is not only a technical function. Forming collaborative relationships with business and clinical leaders, and communicating complex ideas clearly to those leaders, is very important.
4. Good coach not only for direct reports, but also to set the coaching expectation from the direct reports through the entire team and raise the game of everybody in the organization.
5. Empowering so the team can solve complex problems to deliver business value.

How do you measure performance and success when it comes to analytics?

We can deliver the best analytic algorithms, but if the business isn't achieving value from those models and not taking better actions, and if patients aren't getting better care, we haven't achieved anything. The ultimate measure of our performance is, are we achieving those end business outcomes? And then, to ensure that we're achieving those end business outcomes, how are we functioning internally? Do we have the right operational processes? Do we have the right people in the right seats? Do we have the right level of expertise? Are we growing our team? Are we using the right tools? Is our data of high quality? Is our methodology robust? Are we going through the right set of review processes to ensure that analytics are of top quality? All of those are measures that we use to ensure that, more from a process perspective, we have the right pieces in place to deliver end value.

This has been especially notable in 2020. I'm proud of my team's response to COVID. We reorganized our team of about 150 people into a set of scrum teams so that we could deliver critical insights on distribution, utilization, patient equity, staffing, surveillance, capacity management, executive reporting, and the list goes on. The demands on our team changed almost daily, and we'd have to quickly shift our priorities. Interestingly, during this time, my team experienced the highest engagement scores that we have ever achieved, even though we were working extremely long hours.

For more insights from John, listen to the full podcast.