1603
clinical study

Worklist Reprioritization Using Artificial Intelligence Improves Turnaround Times Of Chest CT Examinations Positive For Acute Pulmonary Embolism

Materials & Methods

A total of 4,069 CT chest with contrast scans performed at a tertiary care medical center between Oct. 2019 and Feb. 2020 were retrospectively identified (ED – 1,470, Inpatient – 667, Outpatient – 1,932). Positive cases were flagged by the AI algorithm and brought to the top of the radiology worklist. The remaining 1,327 scans were read according to their priority, with no AI prioritization. All 4,069 cases reports were classified as positive or negative for pulmonary embolism using Natural Language Processing (NLP) on the radiology report to establish ground truth. The radiology turnaround time (RTAT) between positive and negative cases was compared for the cases that had AI result, and cases that did not. RTAT was defined as the time difference between scan completion and report completion time. 

Results

The average RTAT of positive pulmonary embolism (by NLP) cases that were analyzed by AI was 34.2 minutes, while the average RTAT of negative pulmonary embolism cases was 68.25 minutes. The difference between positive and negative cases of pulmonary embolism was 34.05 minutes (CI: 21.3275 to 46.7725 P < 0.01). The average RTAT of positive pulmonary embolism (by NLP) cases that were not analyzed by AI was 58.80 minutes while the average RTAT of negative incidental pulmonary embolism cases was 51.18 minutes. The difference between positive and negative cases of incidental pulmonary embolism was +7.62 minutes.

Conclusions

Using an AI algorithm that prioritizes cases with a positive pulmonary embolism, including incidentally detected pulmonary embolism, have a substantially shorter turnaround time when compared to negative cases.

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