Expert: 5 Keys to Enhance Data Maturity and Unlock $100M+ Improvements

Editor’s Note: This article is based on an educational breakout session at the Healthcare Analytics Summit 2024 (HAS 24) entitled, Key Lessons Learned and Results Achieved in our Multi-Year Data and Analytics Journey: $100M+ Improvements, presented by Rhiannon Harms, Chief Data & Analytics Officer at UnityPoint Health.

In the realm of healthcare, the abundance of data can overwhelm organizations. Therefore, the key to making a real impact lies in prioritizing valuable data and analytics while also easing the burden of extracting actionable insights.

According to Rhiannon Harms, the chief data and analytics officer at UnityPoint Health (UPH), this prioritization isn’t just advantageous but essential for healthcare organizations aiming to succeed in an ever-evolving industry. Thus, organizations can unearth insights that fuel innovation, enhance patient outcomes, and streamline operational efficiency by focusing on high-value information.

At the Healthcare Analytics Summit (HAS) in February, Harms urged participants to define what qualifies as valuable data and analytics for their specific organization and needs.

She also emphasized the advantages of collaborative partnerships across departments that leverage data for decision-making purposes and underscored the importance of consistently measuring, communicating, and demonstrating how data and analytics drive organizational success.

Becoming ‘Problem-Solving Partners’ and Promoting Enterprise Analytics

Harms said she views the data and analytics department as a central hub for collaborating across the UPH system to enhance outcomes and ensure long-term sustainability through strategic data management, analytical insights, and operational improvements.

At the beginning of its journey to becoming a data-driven organization in 2011, she said UPH took measured steps to promote enterprise analytics to gain valuable insights into patient care, operational efficiency, and financial performance.

“We see ourselves as problem-solving partners,” Harms said. “We try not to talk about ourselves as analysts, business analysts, data scientists, or actuaries. We want our operational, clinical, and financial leaders to know that we are here to help them solve their problems. We just happen to use data and analytics as the tool in our toolbelt to help you solve those problems.”

Their responsibility within the health system is to identify opportunities for improvement to do better for the patients and communities they serve. To do that, the health system, which has a presence in Iowa, Illinois, and Wisconsin, focuses on five areas of execution to ensure they use data in ways that meet their strategic goals, including:

• Embedding analytics into the strategic planning process.
• Creating a culture where clinicians and business leaders use data to make decisions.
• Identifying areas of opportunity to improve patient and organizational outcomes.
• Developing solutions used to protect population health and financial trends.
• Using enterprise analytics to serve problem-solving partners with a focus on delivering the most valuable solution. 

Turning Data into Actionable Information Using AI, Natural Language Generation Tools

Thanks to a journey toward better utilization of data platforms and analytics applications, including augmented intelligence (AI) and natural language generation, the analytics department, she said, is now more capable of assisting the entire organization. This has led to the establishment of collaborative systems to boost overall performance, with every discussion grounded in the question: What are we trying to achieve together?

Their goal, she added, is to turn data into actionable information – a challenge that many health systems continue to grapple with. “If you don’t get that foundation right, it becomes really hard to do all the rest of the things you want to do,” Harms told attendees.

UnityPoint Health’s data and analytics department uses AI to assist in setting long-term strategic goals and addressing previous challenges. Some goals required more time for qualitative analysis, while others were less ambitious.

To streamline this process, the health system used natural language generation to convert metadata into easily understandable English text. This change resulted in improved goal tracking and sustained progress. By ensuring everyone understands the data presented and can identify significant changes or normal variations, communication within the organization has dramatically improved, Harms said.

Along the way, senior leadership emphasized the importance of using Statistical Process Controls (SPCs) to monitor KPIs, and they prioritized training individuals to interpret SPC charts. 

Practical Takeaways for Improving Data Maturity Across Health Systems

She concluded her session with the following suggestions for health systems looking to improve their data maturity:

1. Start where you are. Analytics is a journey so make the commitment to improvement from wherever you are.
2. Do what you say. Create predictability by clearly articulating your goals and providing transparent and frequent updates.
3. Develop robust partnerships. Build mutually beneficial relationships that deliver results. 
4. Ruthlessly prioritize. Increasing demands for analytics is a favorable result and must be managed effectively.
5. Stay mission-focused. Maintain a focus that puts your mission at the center of your decisions.

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

Notes from the Field: 7 Questions with Rhiannon L. Harms, Chief Data and Analytics Officer at UnityPoint Health

Health Catalyst Names UnityPoint Health Winner of the 2024 Flywheel Award

Nobel Laureate and CRISPR Co-Inventor Jennifer Doudna Discussed Gene-Editing Breakthroughs at HAS24