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Impact of Early Direct Patient Notification on Follow-Up Completion for Nonurgent Actionable Incidental Radiologic
James Ryan Loftus1, Nadja Kadom2, Timothy M Baran1
1Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York.
Purpose:
The aim of this study was to evaluate whether early direct patient notification in addition to an existing multistage recommendation-tracking system (Backstop) increases follow-up completion rates for actionable incidental findings (AIFs). Patient attitudes toward early notification were also assessed.
Methods:
This prospective, randomized controlled trial recruited patients with AIFs requiring follow-up being enrolled into the Backstop system. Patients were randomized into four groups: those receiving additional early direct notification in a mailed letter (group 1, similar to Pennsylvania Act 112), by phone (group 2), or in an electronic portal message (group 3) and a control group (group 4) without additional notifications added to the existing Backstop system. Differences in follow-up completion rates among these groups were determined using χ2 tests. Patients were surveyed on binary yes/no and Likert-type scale questions, and descriptive statistics are reported.
Results:
Data from 2,548 randomized patients were analyzed for the study, including 593 patients notified by letter, 637 notified by phone, 701 notified by portal, and 617 control patients. Group 3 demonstrated the lowest rate of follow-up completion within 1 month of the follow-up due date at 36.4%, compared with 58.7% for group 1, 60.4% for group 2, and 53.2% for group 4 (P < .0001 for all). Group 2 was the only group to have a significantly higher completion rate than group 4 (P = .014). Patients responded positively regarding early notification and preferred electronic portal communication.
Conclusions:
Early direct notification had a mixed impact on follow-up completion rates on the basis of communication modality but was positively received by patients and may have health care benefits when implemented within a recommendation-tracking system.
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