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整合自动检查分配减少放射科医生的中断:一项 2 年 232022 例检查的队列研究。

Integrated Automatic Examination Assignment Reduces Radiologist Interruptions: A 2-Year Cohort Study of 232,022 Examinations.

机构信息

Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Department of Radiology, Oncologic Imaging Division, NYU Langone, New York, NY, USA.

出版信息

J Imaging Inform Med. 2024 Feb;37(1):25-30. doi: 10.1007/s10278-023-00917-7. Epub 2024 Jan 9.

DOI:10.1007/s10278-023-00917-7
PMID:38343207
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10976913/
Abstract

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 (95 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.

摘要

放射科在提供及时、准确的影像报告方面面临挑战,尤其是在高容量、亚专科化的环境中。在一家三级癌症中心的回顾性队列研究中,我们通过分析实施后 12 个月内的 232,022 次 CT 检查,评估了自动分配系统(AAS)通过分析实施后 12 个月内的 232,022 次 CT 检查,评估了自动分配系统(AAS)在提高放射科工作流程效率方面的效果,并将其与历史对照期进行了比较。AAS 与全院预约系统集成,并设置为根据即将到来的患者预约,自动优先和分配未报告的 CT 检查给可用的放射科医生,并结合电子邮件通知系统。在实施 AAS 后,尽管 CT 量增加了 9%,同时可用放射科医生的数量增加了 8%,但平均每日紧急放射学报告请求(URR)显著减少了 60%(25 ± 12 至 10 ± 5,t = -17.6,p < 0.001),高峰日(95 分位数)的 URR 减少了 52.2%,从 46 降至 22 个请求。此外,对于没有即时预约的患者,报告的平均周转时间(TAT)显著减少了 440 分钟,对于当天有预约的患者,TAT 减少了 86 分钟。最后,一个门诊诊所中抽取的患者等待时间没有受到负面影响。这些结果表明,AAS 可以大大减少工作流程中断,提高报告效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f31d/10976913/d540bd235819/10278_2023_917_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f31d/10976913/82be9d2ff5c7/10278_2023_917_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f31d/10976913/d540bd235819/10278_2023_917_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f31d/10976913/82be9d2ff5c7/10278_2023_917_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f31d/10976913/d540bd235819/10278_2023_917_Fig2_HTML.jpg

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