Advocate’s CDO offers advice from experience on integrating data assets after acquisition

In a trend that shows no signs of slowing, hospitals and health systems are merging, acquiring, and connecting more than ever before. With these sprawling new entities come many challenges in connecting and streamlining their constituent parts. Especially data—and lots of it.

Integrating data assets after a merger or acquisition is critical to operational and strategic success. However, it can be very difficult to navigate as teams are regrouped and new projects and initiatives are re-prioritized within the newly combined entity.

Additionally, decisions about electronic health records, enterprise resource planning, and integration of other important IT systems will ultimately determine the shape and timing of short-term and long-term data and analytics plans.

Lessons learned from integration

Health Advocate – Product mega-merger combining legacy healthcare systems Advocate Aurora Health and Atrium Health – has been underway for more than 18 months. Her experience to date offers valuable insights and guidance on the data migration and integration process.

The new health system, based in Charlotte, North Carolina, now covers 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 a year, it is the third-largest nonprofit health system in the country.

“As the integration began at Advocate Health in December 2022, it became clear that data integration would need to be done thoughtfully and pragmatically, taking into account the immediate needs of understanding the current state while also enabling the long-term needs that had yet to be defined,” he said. Tina Esposito, Chief Data Officer at Advocate Health.

Short term needs

From day one, executive leadership has committed to continued, close monitoring of clinical outcomes and patient experiences to ensure the health system delivers on its promise to provide clinical leadership and patient safety in its communities.

“Like most health systems, there were similarities in how outcomes were measured across the legacy health systems, but also differences,” Esposito explained. “A central business intelligence team assessed the differences and identified similar priorities, enabling the rapid production of a standard enterprise view of clinical outcomes and patient experience.

“The use of visualization tools provided Advocate Health with one of its first standardized integrated reports—within two months of affiliation—enabling the leadership team and board to closely monitor and ensure clinical outcomes,” she continued. “In the meantime, this same team worked closely with clinical thought leaders to ensure that the measurement systems for 2024 were identical in both priority metrics and goals.”

Data and analytics teams used multiple tools to enable rapid data integration, allowing for seamless visibility.

“In addition to databases that aggregate data and visualization software, careful planning around security and access throughout the organization ensured that anyone who needed to view results could easily view them,” Esposito noted. “Advocate Health was able to ensure continued focus and execution on delivering the best health outcomes and experiences as a newly combined entity.”

Long-term needs

As an organization integrates, its operational and strategic business needs require an enterprise view of data – integrated into a single view.

“With a footprint that now reflects two separate EHR instances – in addition to a larger number when you consider legacy and physician-related data – and two separate ERP instances, the existing modern data platform initiative has become increasingly important,” Esposito said.

“Originally conceived as an enabler for advanced analytics and AI, the modern data platform is also a mechanism for democratizing integrated data in a way that leverages central resources for cleansing, customization, and curation within a cloud-based architecture,” she continued. “Once business rules are applied, the platform becomes a source of integrated data, making it more accessible for data science/AI and analytics.”

The platform continues to evolve, with careful consideration of priority data sources. Data teams then work to implement, connect, and adapt that data to the needs of the organization.

Integration point of the data you need

“This effort involves multiple teams within our data and analytics umbrella, including cloud data engineering, data management, and data science,” Esposito explained. “This platform will serve as the integration point for the data we need across the organization.

“A final example is the ability to handle specialty and retail pharmacy operational and strategic data as one enterprise, where the source data resides in two separate EHR instances as well as a third-party database,” she added.

Organisational integration is often understood and implemented in the context of combining cultures and activities, she added.

“In today’s information age, it is equally important to consider the right data assets and how they will connect to each other to ultimately enable newly integrated operational and strategic priorities,” she noted. “Without integrated data, it is impossible to understand the starting point of a new entity or its potential.

“Throughout the data integration effort, vision will drive a bright long-term future, but it must be equally tied to a short-term pragmatic approach to address day-one needs,” Esposito concluded.

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