Community Health System

Laura Shue is the Director of Analytics at Community Health System. She focuses on delivering actionable insights that enhance healthcare quality, safety, and operational efficiency. Her role involves overseeing enterprise-wide data governance, quality, and integrity policies while integrating data from diverse sources to support strategic goals.

Laura shared her expert insights for the 2025 edition of MedTech Outlook. She shared her valuable experience and challenges that she encounters every day, along with advice for the next generation of healthcare analysts.

Key Lessons for Improving Patient Care

With over 20 years of my experience in healthcare analytics, the key lessons to improve patient care and operations are Focus, Collaborate, Communicate, and Empathize.

Prioritizing Healthcare Data Insights

I suggest applying the “ROAG” (pronounced ROGUE) criteria to prioritize the value of insights:

Relevance: Get as close to the behavior needing intervention as possible. Insights also need role relevance: a dashboard displaying facility performance against target for ALOS is less useful to a Chief Operating Officer than a dashboard that lets them drill down on LOS O/E ratios by service line.

Operational impact: Focused data efforts zero on system failures or exceptions to established standards – bottlenecks, inefficiencies. Operational impact also means having the right people at the table.

“In healthcare, we are here to make a difference, so show the staff how the new upgrade, system, or change translates into improvements for patients.”

Actionability: Data paired with an immediate intervention should be prioritized. Real-time intervention preventing a bad patient outcome is more valuable than data that does not trigger immediate course correction. Seeing something coming is more valuable than knowing it happened after the fact.

Goals: It’s all about alignment. Data that gets us closer to our goals around quality and safety of our care, margin improvement, and patient experience, when paired with the principles of actionability, operational impact, and relevancy, is where we need our focus.

4’S of Analytics

Ensuring data remains trusted, accurate, and accessible across teams and departments while protecting privacy, meeting regulations, and managing costs is important. Here is what I think sets apart a professional centralized analytics team from routine reporting: It is the 4’S of Analytics:

Scalable: We all need cost containment. We need scalable solutions that can process increasing amounts of data, grow with new users and applications, maintain security and compliance, and maintain performance.

Sustainable: We need efficiency. Governed and clean data, balanced performance and cost, and have security (access controls, audit trails) built into the design to scale up or down without constant reengineering. Lifecycle management is key.

Supportable: We need a partnership. We build data solutions in tandem with operable support models. Dashboards, even automated ones, require periodic maintenance. We ensure users can access the insights needed without disruption or major downtime. Supportable means sticking to standardized technology stacks and avoiding single points of failure.

Serviceable: We need our connections. We want to design usable and understandable data solutions that require minimal manual intervention, solutions that integrate well with existing vendors, systems, and workflows. Problems are quickly diagnosed, ensuring high reliability of data.

Building and Guiding Analytics Teams

In such a rapidly changing healthcare environment, building and guiding analytics teams that adapt and translate data into measurable improvements in patient outcomes relies on communication and empathy. Start with the vision of the desired end state. In healthcare, we are here to make a difference, so show the staff how the new upgrade, system, or change translates into improvements for patients. Adaptive teams are teams with high levels of trust, so I behave in a manner that garners trust. A culture that prioritizes learning over blame and growth over personal mastery naturally fosters adaptive teams.

Challenges in Advancing Analytics

Articulating that value proposition helps in navigating challenges in advancing analytics with a large health system. Every Analytics leader faces the same general challenge. We all know the blank stares returned when we respond to the question, “What do you do for a living?” We counter the challenge of the value proposition of analytics in large health systems by helping leaders and frontline staff access timely, relevant, and actionable insights.

Advice for the Future Healthcare Analysts

I would set the expectation of accelerated lifecycles for acquiring new technologies, methods, and tools. Our ability to learn and to help be the connectors that translate business problems into actionable insights is our most prized asset.

Analytics is not a great career for someone who wants to sit behind a computer screen and crunch code or numbers. Crunching code will continue the current automation path. Our connections are our magic: how do we quickly bridge people, data, and technology? How do we build relationships across teams, understanding the goals and the context our stakeholders live in? How do we frame our analysis? Our best developers are intuitive at their core – but in very specific ways: they are good at detecting patterns, spotting trends, and drawing connections that others might miss.