Harvard pilots ‘IR-Peer,’ a new team-based learning system for interventional radiology

Harvard Medical School is achieving early success implementing a new team-based peer learning system in interventional radiology, researchers detailed Aug. 31 in JACR.

RadPeer has been around for 20 years, allowing diagnostic specialists to regularly review one another’s work and provide feedback. However, such tools are less prevalent on the interventional side of the profession, experts noted. To address this issue, Harvard and its affiliated entities gathered feedback from all members of the IR team, including rad techs, nurses, advanced practice providers, residents, fellows and attendings.

They launched their HIPAA-compliant peer-to-peer platform in April 2022, providing a forum for IR pros to discuss clinical complications and learn from each other.

“The implementation of a peer learning system in IR has the potential to improve quality and safety and reduce malpractice risk by improving provider learning,” corresponding author Dania Daye, MD, PhD, with the Department of Interventional Radiology at Massachusetts General Hospital, and co-authors advised. Such a system also could allow proceduralists to “learn from their errors or near misses as well as receive feedback about cases with excellent outcomes or intraprocedural technique,” they added. “Our results suggest that anonymity and ensuring a simple process for reporting with actionable feedback are critical features of peer learning platforms that should be incorporated in future iterations of this model.”

Following the initial launch in spring 2022, Daye and colleagues monitored case submissions for the next 24 weeks, providing monthly reports to departmental leaders. They also conducted surveys both before and after the intervention to assess IR-Peer’s impact. Harvard tallied a total of 92 peer learning submissions during the study period, at an average of 3.8 each week. Another 26 came in through the division’s monthly complication review conference, for a grand total of 98 unique case references.

Complications/adverse events occurred across 64% of the 92 submitted cases, the authors reported, while 36% related to a learning opportunity that did not involve one. Nurses found that IR-Peer made the complication-reporting process easier, while all members of the clinical IR team believed it improved the process. Several reports highlighted the “excellent” communication it fostered, both within the IR team and with other referring physicians.

“Peer learning frameworks such as IR-PEER provide a more equitable communication platform for multidisciplinary teams to capture and archive learning opportunities which support quality and safety improvement efforts,” the authors reported in the study abstract.

Daye et al. underlined that 36% of cases were focused only on learning opportunities and would not have been captured by traditional adverse-reporting methods. They see promise in their work and urge others in the specialty to explore similar initiatives.

“Team-based peer learning in IR allows for a systematic, objective and fair collection of complications and learning opportunities from multiple clinical stakeholders to enhance quality and safety,” the authors concluded. “To our knowledge, few such programs currently exist in IR in the United States. Available data show positive provider experience and improved outcomes from diagnostic radiology programs, and the successful implementation of such a model in IR can change the paradigm of how peer feedback is delivered in IR and can improve quality and safety in procedural areas.”

Read more, including potential study limitations, in JACR at the link below.

Marty Stempniak

Marty Stempniak has covered healthcare since 2012, with his byline appearing in the American Hospital Association's member magazine, Modern Healthcare and McKnight's. Prior to that, he wrote about village government and local business for his hometown newspaper in Oak Park, Illinois. He won a Peter Lisagor and Gold EXCEL awards in 2017 for his coverage of the opioid epidemic. 

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