Integrated Automatic Examination Assignment Reduces Radiologist Interruptions: A 2-Year Cohort Study of 232,022 Examinations.
Radiology departments face challenges in delivering timely and accurate imaging reports, especially in high-volume, subspecialized settings. In this retrospective cohort study at a tertiary cancer center, we assessed the efficacy of an Automatic Assignment System (AAS) in improving radiology workflo...
| Publicado en: | Journal of Digital Imaging Vol. 37; no. 1; pp. 25 - 31 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=175966510&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175966510 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Feb2024 vid: 37 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 175966510 175966510 175966510 10.1007/s10278-023-00917-7 175966510 ppf: 25 ppct: 6 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Integrated Automatic Examination Assignment Reduces Radiologist Interruptions: A 2-Year Cohort Study of 232,022 Examinations. aug: au: Law, Wyanne Terzic, Admir Chaim, Joshua Erinjeri, Joseph P. Hricak, Hedvig Vargas, Hebert Alberto Becker, Anton S. affil: https://ror.org/02yrq0923 Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA sug: subj: Radiology Service Administration Diagnostic Imaging Health Care Delivery, Integrated Workflow Automation Radiologists Outcome Assessment Human Prospective Studies Retrospective Design Record Review Tertiary Health Care Cancer Care Facilities Autoanalysis Radiology Information Systems Tomography, X-Ray Computed Appointments and Schedules Hospital Information Systems Health Priorities Health Resource Allocation Personnel Staffing and Scheduling Reminder Systems Program Implementation Program Evaluation Descriptive Statistics Turnaround Time Waiting Lists Health Informatics Systems Integration Organizational Efficiency Data Analysis Software Two-Tailed Test Probability Funding Source ab: Radiology departments face challenges in delivering timely and accurate imaging reports, especially in high-volume, subspecialized settings. In this retrospective cohort study at a tertiary cancer center, we assessed the efficacy of an Automatic Assignment System (AAS) in improving radiology workflow efficiency by analyzing 232,022 CT examinations over a 12-month period post-implementation and compared it to a historical control period. The AAS was integrated with the hospital-wide scheduling system and set up to automatically prioritize and distribute unreported CT examinations to available radiologists based on upcoming patient appointments, coupled with an email notification system. Following this AAS implementation, despite a 9% rise in CT volume, coupled with a concurrent 8% increase in the number of available radiologists, the mean daily urgent radiology report requests (URR) significantly decreased by 60% (25 ± 12 to 10 ± 5, t = -17.6, p < 0.001), and URR during peak days (95th quantile) was reduced by 52.2% from 46 to 22 requests. Additionally, the mean turnaround time (TAT) for reporting was significantly reduced by 440 min for patients without immediate appointments and by 86 min for those with same-day appointments. Lastly, patient waiting time sampled in one of the outpatient clinics was not negatively affected. These results demonstrate that AAS can substantially decrease workflow interruptions and improve reporting efficiency. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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