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Learn moreExplore how Aidoc’s clinical AI solutions can increase hospital efficiency, show proven return on investment, and help enable better outcomes.
Learn moreDiscover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
Learn moreSee the latest research, case studies, tips and more to start improving outcomes with healthcare AI today.
Learn moreLearn more about Aidoc’s approach, mission and leadership team that is revolutionizing healthcare with AI.
Learn moreMechanical pulmonary arterial thrombectomies performed for acute PE and CT angiogram (CTA) were reviewed over a four-year period. The algorithm to directly notify PERT members was initiated in early 2022. The cohort was divided into pre-implementation and post-implementation groups. Time of CTA acquisition, time of notification of a clinical provider by the reading diagnostic radiologist, and time of thrombectomy were gathered and used to compare times to thrombectomy and time from imaging to notification of a clinical provider between the two groups. Clinical outcomes including hospital length of stay and ICU length of stay were collected.
A total of 13 patients including six patients in the pre-implementation phase and seven patients in the post-implementation phase. Implementation of the algorithm was associated with a mean decrease in time from CT angiography to mechanical thrombectomy by 40% (17.1 hours vs. 10.1 hours) and time from imaging to notification of clinical provider by 38% (0.8 hours vs. 0.3 hours). Clinical outcomes showed a 23% (13 days vs. 10 days) reduction in the length of stay in the ICU and 18% (17 days vs. 14 days) in overall inpatient length of stay.
The use of an AI algorithm suggests a significant reduction in time from initial imaging to mechanical pulmonary arterial thrombectomy by screening CT angiograms and directly notifying a PERT of potential candidates.
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