In a trend that shows no signs of slowing down, hospitals and health systems are consolidating, acquiring, and merging more than ever. With these new entities growing, there are many challenges in combining and streamlining their constituent parts. Especially data — and lots of it.
Integrating data assets after a merger or acquisition is central to operational and strategic success. But it can be difficult to navigate as teams are reorganized and new projects and initiatives are reprioritized under the newly combined entity.
Furthermore, decisions about electronic health records, enterprise resource planning, and other critical IT systems integrations will ultimately determine the form and timing of short- and long-term data and analytics plans.
Integrated lessons learned
Advocate Health – a product of megamerger – combining legacy healthcare systems Advocate Aurora Health and Atrium Health – has been more than 18 months in the process. The company’s experience so far provides some valuable insights and tips on the migration and data integration process.
Headquartered in Charlotte, North Carolina, the new health system now operates in six states: Alabama, Georgia, Illinois, North Carolina, South Carolina, and Wisconsin. With 69 hospitals, more than 21,000 physicians, and serving nearly 6 million patients each year, it is the third-largest nonprofit health system in the country.
“As the integration process began at Advocate Health in December 2022, it became clear that data integration needed to be done thoughtfully and pragmatically because of the urgent need to understand the current state as well as enable long-term needs that were yet to be identified,” he said. Tina Esposito, chief data officer at Advocate Health.
Short term needs
Executive leadership has directed from Day One that clinical outcomes and patient experiences will continue to be closely monitored, ensuring the health system delivers on its commitment to clinical excellence and patient safety in the community.
“As with most health systems, there are similarities in how outcomes are measured across the respective legacy health systems, but there are also differences,” Esposito explains. “The central business intelligence team assessed the differences and identified similar priorities, allowing for the rapid creation of a standardized business view of clinical outcomes and patient experience.
“Using visualization tools provided Advocate Health with one of its first standardized integrated reports—within two months of the integration—allowing the executive team and board to closely monitor and ensure clinical performance,” she continued. “Meanwhile, the same team worked closely with clinical thought leaders to ensure the 2024 measurement systems would be identical across both priority measures and goals.”
Data and analytics teams have used multiple tools to enable rapid data integration, helping to gain a seamless view of data.
“In addition to the database of data aggregation and “Visualization software, careful planning for security, and access across the entire organization ensure that everyone who needs to see performance can easily see it,” Esposito notes. “Advocate Health can ensure continued focus and execution to ensure the best health outcomes and experiences as a newly combined entity.”
Long term needs
As organizations become more integrated, strategic and operational business needs require a single view of enterprise data – integrated into a single view.
“With the current footprint reflecting two separate EHR instances — in addition to many others when looking at legacy data and physician-related data — and two separate ERP instances, the existing modern data platform initiative has become even more important,” Esposito said.
“Originally envisioned as a platform to enable advanced analytics and AI, a modern data platform is also a mechanism to democratize integrated data by leveraging central resources for cleansing, compliance, and governance in a cloud-based architecture,” she continued. “As business rules are applied, the platform becomes an integrated data source, making data more accessible for data science/AI and analytics purposes.”
Work on building the platform continues with careful consideration of priority data sources and further work within data teams to onboard, integrate and manage for the organization appropriately.
Integration point for required data
“This effort involves multiple teams across our data and analytics footprint, including cloud data engineering, data governance, and data science,” Esposito explains. “The platform will serve as the essential data integration point across the organization.
“A recent example is the ability to support the strategic and operational data needs of a specialty and retail pharmacy as one enterprise where the source data resides in two separate EHR instances as well as a third-party database,” she added.
Organizational integration is often understood and pursued in the context of bringing cultures and activities closer together, she said.
“In today’s information age, it is important to consider the respective data assets and how they will come together to ultimately enable new strategic and operational priorities to be integrated,” she notes. “Without integrated data, it is impossible to understand the starting point of a new or potential entity.
“Throughout the data integration effort, vision will drive a bright long-term future, but it needs to be combined with a pragmatic short-term approach to address needs from Day One,” Esposito concludes.
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