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3 Barriers Limiting EHR Data Use for Patient Safety Research

EHR data use for patient safety research has three main barriers, including access approval, data interpretation, and cooperation with EHR personnel.

By Sara Heath

New research shows that EHR data use for clinical improvement and patient safety research comes with several challenges.

In a recent case study of three different commercially-available EHRs, researchers identified three barriers to using EHR data: approval for access to and review of EHR data, EHR data interpretation, and collaboration with hospital IT and EHR personnel.

The research team sought to better understand these barriers, as well as explore methods to mitigate them and make EHR data use for patient safety research more productive.

EHR data access approval

According to the researchers, many healthcare institutions limit remote access to EHR data for research purposes, despite Institutional Board review and approval. This is likely due to hospital fears of large-scale healthcare data breaches, which have been occurring at an increasing rate.

While these measures may have been extreme considering other security protocol, the researchers concluded that they were likely not going away. However, the team did say institutional board review processes should be enough for hospitals to override certain security protocol for research teams.

“After institutional review, patient safety research projects should be deemed safe to carry out, assuming the organization has implemented robust firewalls and advanced level 3 authentication procedures as outlined by the National Institute of Standards and Technology (NIST),” the research team explained.

“Applying these measures to all remote users would greatly reduce an organization's security risks and allow clinicians and researchers alike to make better use of EHR data remotely to improve patient care.

The research team also had difficulties with the type of EHR data they could access. This included access to EHR charts and secure direct messages, which could otherwise have informed the researchers of instances where urgent tests had been overlooked.

The research also indicated network access difficulties, with one of the test site’s requiring the researchers to utilize a separate network for security reasons. This caused much of the data download to be slow and arduous.

EHR data interpretation

The research team found two main issues in EHR data interpretation, the first of which being a lack of structured EHR data.

“Structured data is important because it can help computer algorithms garner meaning from the data and has been a focus of meaningful use (MU) requirements,” the research team explained.

The lack of structured data made it so the research team received massive amounts of unsorted information. When they wanted to see EHR data about radiology test results, for example, they received data about all pathology. Researchers then had to sort through the information themselves, which proved to be arduous.

Going forward, the research team proposed the healthcare industry agree on a set of data standards across the board, making research more efficient.

EHR data transcription was also difficult because much of the information had to be exported in PDF format. As a result, the research team had to manually transcribe the data into their systems.

Competing priorities with EHR personnel

Researcher cooperation with hospital IT staffs may lead to more complications, the team said. Many IT teams are working on separate projects – EHR optimization, meaningful use attestation – and are therefore unable to fully collaborate or cooperate with researcher needs.

The research team noted that meaningful use attestation and other hospital IT projects are important. However, they say that as EHRs reach universal adoption, priorities should shift toward research.

“We posit that all organizations (not just those with “research” as part of their mission) should dedicate additional IT personnel and implement near real-time clinical data warehouses with easy-to-use report writing capabilities to support quality improvement and patient safety improvement efforts,” the researchers said. “This would allow current IT staff to focus on operational activities.”

Going forward, the healthcare research industry must consider goals toward making research more feasible and efficient. Although these goals prove difficult, they may be key in improving clinical quality and patient safety.




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