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As more and more healthcare institutions enter into mergers and acquisitions, data management has become a critical discipline in the industry. Combining patient data from separate electronic health record systems can be complex. IT managers must ensure that the correct data migrates to the new EHR and creates a single source of truth that considers all relevant patient information.

Unlike other industries, where errors can lead to problems such as financial errors, inaccurate data in healthcare can put lives at risk.

“It has become a big challenge for the healthcare industry,” says Venkataraman Chittoor, Chief Product and Technology Officer at Marathon Health. “When migrating two systems, we need to plan how they are used, mapped, and how to recognize data issues.”

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The Importance of Planning for EHR Data Integration

Healthcare mergers and acquisitions jumped more than 56% in 2021, according to a PwC report. Much of this is driven by organizations striving to consolidate fragmented sub-sectors of the healthcare system to create larger entities capable of delivering higher quality, patient-centric care that is rooted in digital capabilities. . Long-term care and home healthcare remain two of the areas most ripe for mergers and acquisitions.

Healthcare data can be particularly difficult to manage because it’s complex, a valuable target for cybercriminals and critical to patient outcomes, Chittoor says. While organizations in all industries face challenges when merging data from different systems, this is especially critical in healthcare, as this data can mean the difference between life and death.

“In health care, if you’re missing certain conditions or certain medications that people may have taken in the past, or if they’ve had other issues and the data isn’t entirely accurate, it can steer them in the wrong direction,” says Chittoor.

Health data is also a prime target for cybercriminals as it often contains financial and personal data that can be used to commit fraud. In June 2022 alone, 70 health data breaches of 500 or more records were reported to the Department of Health and Human Services’ Office for Civil Rights. To reduce these risks, healthcare organizations should carefully evaluate both organizations’ security policies and procedures during a merger or acquisition.

This complexity has made master data management a vital discipline in healthcare, says Chittoor. It’s critical that organizations spend a lot of time up front identifying how best to map data points and what the new infrastructure will look like, he adds. Healthcare IT managers need to determine the level of data they want to retain, enforce rules that maintain data quality, and ensure validation and alignment with core organization systems. This often involves members of the IT team and a QA team to validate data before the new system is released to patients.

“It’s not just about moving data between columns. It must be a full migration. Data exchange and storage has been a big challenge for healthcare companies, but they are making a lot of progress in catching up,” says Chittoor.

Integrate EHR data into quality assurance during a merger or acquisition

At Ochsner Health, data fusions begin with guiding principles that focus on best practices for migrating, using and presenting clinical data to users, says Amy Trainor, vice president of clinical IS systems at the organization. Since data quality is affected by the legacy system, how often it updates, and the features available, a best-practice approach helps ensure data is available in clinicians’ workflow .

Ochsner has completed several mergers and acquisitions in recent years. More recently, it merged with Rush Health Systems, gaining 30 additional clinics and seven hospitals in Mississippi and Alabama.

Even with the smallest partners, Ochsner performs data review to ensure accuracy. Continuity of care documents are particularly important because not all are created equal, Trainor says. True CCD summaries can include notes, vital data, and surgical records in addition to problems, allergies, medications, and vaccinations. Since these documents may not be consistent across systems, it is essential to verify their accuracy and carefully consider how they should be integrated into the new system.

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“We saw a range, from the most sophisticated documents to the most limited,” says Trainor. “We are evaluating and testing this through our data review process.”

Trainor notes that each merger and acquisition is unique in how it handles data migration. Often the hardest part is making sure that the patients main index is correct. Using disparate systems for patient registration is much more time consuming than replacing a single system. In one instance, Ochsner had three sources of truth to examine and no indication of which information was most up-to-date.

“These tend to really extend the lead time, because making sure the patient information is correct is of the utmost importance,” Trainor says.

Trainor recommends several best practices. The most important thing is to set a goal to focus on accurate, clinically relevant data, and then make sure the data is actionable, “not just migrating to tick the box,” she says. Because there are always unique circumstances, IT managers should also create a process to view incoming data with each partner. Clean patient records are essential, and organizations should spend more time getting it right.

“We want to make sure the data we have is as actionable and present in the clinicians’ workflow as possible,” she says.