As 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 leaders must ensure 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 mistakes may lead to issues 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 it is used, mapped and how to recognize data issues.”
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The Importance of Planning for EHR Data Integration
Healthcare mergers and acquisitions surged by more than 56 percent in 2021, according to a report by PwC. Much of this is driven by organizations striving to consolidate fragmented subsectors of the healthcare system to create bigger entities that can deliver higher-quality, patient-centric care anchored in digital capabilities. Long-term care and home health remain two of the strongest areas for mergers and acquisitions.
Healthcare data can be especially challenging to deal with because it is complex, a valuable target for cybercriminals, and critical to patient outcomes, says Chittoor. While organizations in all industries face challenges when merging data from different systems, it’s especially critical in healthcare because that data can mean the difference between life and death.
“In healthcare, if you miss certain conditions or medications people may have been taking in the past, or if they had other issues and the data is not entirely accurate, it may steer them in the wrong direction,” says Chittoor.
Healthcare data is also a prime target for cybercriminals because it often contains financial and personal data that can be used to commit fraud. In June 2022 alone, 70 healthcare data breaches of 500 or more records were reported to the Department of Health and Human Services’ Office for Civil Rights. To reduce such risks, healthcare organizations need to assess carefully the security policies and procedures of both organizations during a merger or acquisition.
This complexity has made master data management a vital discipline in healthcare, says Chittoor. It’s essential for organizations to spend a lot of time up front identifying how to best map data points and what the new infrastructure will look like, he adds. Health IT leaders need to determine what level of data they want to keep, apply rules that maintain data quality, and ensure validation and alignment with the lead organization’s systems. This often involves IT team members and a quality assurance team to validate data before the new system is released to patients.
“It’s not just moving data between columns. It needs to be a comprehensive migration. Data exchanges and storage have been a big challenge for healthcare companies, but they are making a lot of progress in catching up,” says Chittoor.
Integrating EHR Data with Quality Assurance During a Merger or Acquisition
At Ochsner Health, data mergers start with guiding principles that focus on best practices for migrating, using and presenting clinical data to users, explains Amy Trainor, the organization’s vice president of IS clinical systems. Because the quality of data is affected by the previous system, how often it was updated and what functionality was available, a best-practice approach helps ensure data is available in the clinicians’ workflow.
Ochsner has entered into several mergers and acquisitions in recent years. Most recently, it merged with Rush Health Systems, gaining 30 additional clinics and seven hospitals in Mississippi and Alabama.
Even with the smallest partners, Ochsner completes a data review to ensure accuracy. Continuity of care documents are especially important because they are not all created equal, says Trainor. True CCD summaries can include notes, vitals and surgical records in addition to problems, allergies, medications and immunizations. Because these documents may not be consistent across systems, it’s essential to review their accuracy and consider carefully how they should be integrated into the new system.
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“We have seen a range, from the most sophisticated documents to the most limited,” says Trainor. “We evaluate and test this through our data review process.”
Trainor notes that each merger and acquisition is unique in how it manages data migration. Often, the most challenging part is ensuring that the master patient index is correct. Using disparate systems for patient registration requires much more lead time than replacing a single system. In one case, Ochsner had three sources of truth to review and no indication of which information was the most up to date.
“These tend to really extend the timeline, as ensuring the patient information is correct is of utmost importance,” says Trainor.
Trainor recommends several best practices. The most important is to set a goal to focus on accurate, clinically relevant data and then ensure that data is actionable, “not just migrate to check the box,” she says. Because there are always unique circumstances, IT leaders should also create a process to view the incoming data with every partner. Clean patient files are critical, and organizations should spend the extra time to get it right.
“We want to ensure that the data we have is as actionable and present in the clinicians’ workflow as possible,” she says.