Automated Incidental Findings Notification Through the Electronic Health Record Utilizing Dictation Macros

The objective of this study is to implement an actionable incidental findings (AIFs) communication workflow integrated into the electronic health record (EHR) using dictation macros to improve the quality of radiology reports and facilitate delivery of findings to clinicians. The workflow was implemented across an academic multi-hospital health system and used by over 100 radiologists from 12 divisions. Standardized macros were created for different organ systems including the thyroid, lungs, liver, pancreas, spleen, kidney, female reproductive, and others, designed based on the ACR Novel Quality Measure Set. All macros contained special codes enabling automated notification of clinicians in Epic EHR and unique codes to allow for tracking. When notified, clinicians can fast track ordering of follow-up imaging exams. All alerts were monitored by radiology operations who ensured messages were acknowledged within 73 h. From September 2023 to March 2024, 12,919 AIFs alerts were filed for 10,766 patients. Median age was 65 years, and 63.6% were female and 36.4% were male. Most alerts were submitted for outpatients (73.5%), and a majority originated from CT exams (57.3%) followed by radiographs (12.2%) and ultrasound (11.5%). Number of submissions per radiologist ranged from 0 to 930 with a median of 62. Median time to alert acknowledgment was 8.1 h, and 93.9% were acknowledged within 73 h. Follow-up orders were placed for 62.3% of patients. A standardized AIFs communication workflow utilizing dictation macros can help facilitate delivery of findings and follow-up recommendations to clinicians.