The Impact of Data Management on the Achievable Dose and Efficiency of Computed Tomography During the COVID-19 Era: A Facility-Based Ambispective Study

PURPOSE: This study primarily aimed to evaluate the effectiveness of computational data management and analytical software for establishing departmental diagnostic reference levels (DRLs) for computed tomography (CT) scanning in clinical settings, and monitor achievable doses (ADs) for CT imaging, particularly during the coronavirus disease 2019 (COVID-19) era. Secondarily, it aimed to correlate these standards with national and international benchmarks. PATIENTS AND METHODS: This ambidirectional cohort study enrolled 4668 patients (6419 CT-based examinations) who visited King Fahd Hospital of the University from May 25, 2021, to November 4, 2021. Participants’ demographic data were acquired from their electronic medical charts, in addition to all corresponding CT-dose determinant parameters. The study was divided into two phases (pre- and post-data management) based on the implementation of digital data management software. RESULTS: In both phases of the study, the size-specific dose estimate (SSDE) was the most significant confounder of dose determination compared to the dose-length product (DLP) and computed tomography dose index (CTDI) (P = 0.003). The head was the most frequently imaged body region (pre-implementation, 1051 examinations [35.1%]; post-implementation, 1071 examinations [31.3%]; P = 0.001), followed by the abdominal region (pre-implementation, 616 examinations [20.6%]; post-implementation, 256 examinations [7.48%]; P = 0.001). Based on the SSDE, DLP, and volume CTDI, the average per-section radiation exposure among organ-based scanning type was highest for the lumbar spine during the pre- and post-implementation periods. CONCLUSION: Data management software enabled the establishment of DRLs and reduction of ADs in CT examinations, which consequently improved key performance indicators, despite the ergonomic complexities of COVID-19. Institutions are encouraged to apply DRLs and ADs via automatic systems that monitor patient dose indices to evaluate aggregate results.