Ravi R Pandit1, Michael V Boland2. 1. 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. 2. 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. Electronic address: boland@jhu.edu.
Abstract
PURPOSE: To determine the impact of a Digital Imaging and Communications in Medicine (DICOM) workflow on the linkage of demographic information to ophthalmic testing data. DESIGN: Evaluation of technology. PARTICIPANTS: Six hundred ninety-nine visual field testing encounters performed by 6 ophthalmic technicians and the transfer error queue of 37 442 ophthalmic test results. METHODS: 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. MAIN OUTCOME MEASURES: The proportion of testing encounters for which staff had to enter, edit, or merge patient demographics and the proportion of misfiled images. RESULTS: 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. CONCLUSIONS: 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.
PURPOSE: To determine the impact of a Digital Imaging and Communications in Medicine (DICOM) workflow on the linkage of demographic information to ophthalmic testing data. DESIGN: Evaluation of technology. PARTICIPANTS: Six hundred ninety-nine visual field testing encounters performed by 6 ophthalmic technicians and the transfer error queue of 37 442 ophthalmic test results. METHODS: 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. MAIN OUTCOME MEASURES: The proportion of testing encounters for which staff had to enter, edit, or merge patient demographics and the proportion of misfiled images. RESULTS: 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. CONCLUSIONS: 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.
Authors: Michael F Chiang; Michael V Boland; Allen Brewer; K David Epley; Mark B Horton; Michele C Lim; Colin A McCannel; Sayjal J Patel; David E Silverstone; Linda Wedemeyer; Flora Lum Journal: Ophthalmology Date: 2011-06-16 Impact factor: 12.079
Authors: Liam J Caffery; David Clunie; Clara Curiel-Lewandrowski; Josep Malvehy; H Peter Soyer; Allan C Halpern Journal: J Digit Imaging Date: 2018-08 Impact factor: 4.056