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How Analytics Can Inform EHR Workflow Optimization, Clinician Burden

Advanced text analytics of EHR inbox messages could help guide EHR workflow optimization to mitigate clinician burden.

Using advanced text analytics to assess inbox messages can inform EHR workflow optimization to address clinician burden, according to a study published in the American Journal of Managed Care (AMJC).

EHRs have transformed the daily work of primary care physicians (PCPs). However, despite promised benefits of health IT, PCPs find that they spend more than half of their work hours on the EHR, with a significant portion spent on administrative tasks. 

To understand EHR inbox management at a more granular level, researchers used advanced text analytics on EHR inbox messages from 2018 for 184 PCPs from 18 practices.

The analysis revealed 30 different work themes that fell into two categories: medical and administrative tasks.

More than half (50.8 percent) of the messages were related to medical issues and 34.1 percent focused on administrative matters.

More specifically, 17.6 percent involved scheduling issues, 13.6 percent of the messages involved ambiguous diagnosis issues, and 13.2 percent involved condition management problems. Additionally, 9.5 percent involved paperwork problems and 6.7 percent dealt with identified symptoms issues.

“The dissemination of EHR systems reduced the work burden on support staff while at the same time increasing PCPs’ work burden,” the study authors pointed out. “With this, EHR impact on physicians’ wellness has become a great concern for most healthcare organizations.”

The researchers noted that the purpose of their study was to help develop a scalable approach to identify work themes in PCP inbox messages that could enhance EHR workflow optimization to mitigate clinician burden.

For instance, messages related to the management of complex clinical conditions and patient health need PCP involvement, whereas messages related to “simpler” clinical tasks like routine preventive work or administrative tasks such as scheduling are better managed by other team members.

“The value of this methodological approach is that it allows analyzing physician work composition at a great level of detail,” they wrote. “This provides critically important diagnostic tools to help inform policies that address compensation of PCPs, as well as redesign of related workflow processes to improve quality, cost of care, and staff work satisfaction.”

The study authors noted that the use of advanced text analytics allows for a detailed understanding of PCPs’ work without the need for manual review of messages.

“The methodology and tools developed in this study allow unprecedented understanding of the substance and complexity of work themes managed by PCPs through EHR inbox messages,” the researchers emphasized.

“Moreover, the ability to understand heterogeneity in work composition across PCPs and practices is critical to be able to identify opportunities to improve the quadruple aim: quality, cost, patient satisfaction, and physician satisfaction,” they added.

The researchers noted that the study has several limitations. First, they used the methodology on PCPs from a single institution, so the findings are not necessarily generalizable to other healthcare facilities or physicians from other specialties.

Additionally, the study authors explained that they extracted EHR data from the Epic EHR system. Other EHR platforms may produce different insights regarding work composition because of different inbox message formats, they suggested.

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