Pandit Ravi R, Boland Michael V
Glaucoma Center of Excellence, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland; Dana Center for Preventive Ophthalmology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
Glaucoma Center of Excellence, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland; Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Ophthalmology. 2015 Feb;122(2):227-32. doi: 10.1016/j.ophtha.2014.08.036. Epub 2014 Oct 22.
To determine the impact of a Digital Imaging and Communications in Medicine (DICOM) workflow on the linkage of demographic information to ophthalmic testing data.
Evaluation of technology.
Six hundred ninety-nine visual field testing encounters performed by 6 ophthalmic technicians and the transfer error queue of 37 442 ophthalmic test results.
At 3 months before and 6 and 18 months after implementation of a DICOM workflow, technicians recorded the work required to enter, confirm, or edit patient demographics in each visual field device. We also determined the proportion of imaging tests sent to an error queue for manual reconciliation because of incorrect demographic information before and 3, 6, and 18 months after the DICOM workflow was established.
The proportion of testing encounters for which staff had to enter, edit, or merge patient demographics and the proportion of misfiled images.
Staff entered, edited, or merged data for 48% of patients before implementation (n = 237). This decreased to 24% within 6 months and 20% within 18 months of implementing the DICOM archive (n = 230 and n = 232, respectively). Staff could locate a patient in a DICOM work list for 97% of encounters at 3 months and 99% at 18 months. Before implementation, 9.2% of the images required additional intervention to be associated with the correct patient (n = 3581). This decreased by 85% over 6 months to 1.4% (n = 9979; P < 0.01). There was an increase in the percentage of misfiled images between 6 and 18 months from 1.4% to 2.2% (n = 24 549; P < 0.01), representing an overall 76% decrease over 18 months relative to the pre-DICOM period.
Implementation of a DICOM-compatible workflow in an ophthalmology clinic reduced the need to enter or edit patient demographic information into imaging or testing devices by more than 50% and reduced the need to manage misfiled images by 76%. In a clinical environment that demands both efficiency and patient safety, the DICOM workflow is an important update to current practice.
确定医学数字成像和通信(DICOM)工作流程对人口统计学信息与眼科检查数据关联的影响。
技术评估。
6名眼科技术人员进行的699次视野检查以及37442份眼科检查结果的传输错误队列。
在实施DICOM工作流程前3个月以及实施后6个月和18个月,技术人员记录在每个视野检查设备中输入、确认或编辑患者人口统计学信息所需的工作。我们还确定了在建立DICOM工作流程之前以及之后3个月、6个月和18个月,因人口统计学信息错误而被发送到错误队列进行人工核对的成像检查比例。
工作人员必须输入、编辑或合并患者人口统计学信息的检查比例以及存档错误图像的比例。
在实施前,48%的患者(n = 237)的数据需要工作人员输入、编辑或合并。在实施DICOM存档后的6个月内,这一比例降至24%,18个月内降至20%(分别为n = 230和n = 232)。在3个月时,工作人员在DICOM工作列表中找到患者的成功率为97%,18个月时为99%。在实施前,9.2%的图像(n = 3581)需要额外干预才能与正确患者关联。6个月内这一比例下降了85%,降至1.4%(n = 9979;P < 0.01)。在6至18个月期间,存档错误图像的百分比从1.4%增加到2.2%(n = 24549;P < 0.01),相对于DICOM实施前的时期,18个月内总体下降了76%。
眼科诊所实施DICOM兼容工作流程后,将患者人口统计学信息输入或编辑到成像或检查设备中的需求减少了50%以上,管理存档错误图像的需求减少了76%。在要求效率和患者安全的临床环境中,DICOM工作流程是对当前实践的重要更新。