Literature DB >> 29691135

Order Entry Protocols Are an Amenable Target for Workflow Automation.

James Tudor1, Chad Klochko2, Milind Patel2, Daniel Siegal2.   

Abstract

PURPOSE: Order entry protocol selection of advanced imaging studies is labor-intensive, can disrupt workflow, and may displace staff from more valuable tasks. The aim of this study was to explore and compare the behaviors of radiologic technologists and radiologists when determining protocol to identify opportunities for workflow automation.
METHODS: A data set of over 273,000 cross-sectional examination orders from four hospitals within our health system was created. From this data set, we isolated the 12 most frequently requested examinations, which represent almost 50% of the entirety of advanced imaging volume. Intergroup comparisons were made between behavior of radiologic technologists and radiologists or residents when determining protocol. Frequencies of changes were calculated. Common parameters of changed examinations were identified.
RESULTS: The overall change rate for both radiologists and residents (4%) is very low and comparable to the overall change rate of radiologic technologists (1%). The change rates for the 12 most ordered examinations were calculated and compared individually. Most examinations that underwent change involved a patient with a low estimated glomerular filtration rate, a patient with a contrast allergy, or a provider ordering a general examination but in fact wanting an organ-specific protocol or an angiographic study.
CONCLUSION: Order entry protocol selection of the most frequently ordered advanced imaging examinations was rarely a value-added activity because these examinations are rarely changed. Changes follow predictable patterns that make order entry protocol selection of most radiology orders for advanced imaging amenable to workflow automation.
Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Workflow automation; data analysis; determining protocol; value-added activity; workflow

Mesh:

Year:  2018        PMID: 29691135     DOI: 10.1016/j.jacr.2018.02.003

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  3 in total

Review 1.  Automated Protocoling for MRI Exams-Challenges and Solutions.

Authors:  Jonas Denck; Oliver Haas; Jens Guehring; Andreas Maier; Eva Rothgang
Journal:  J Digit Imaging       Date:  2022-08-30       Impact factor: 4.903

2.  Artificial Intelligence in Imaging: The Radiologist's Role.

Authors:  Daniel L Rubin
Journal:  J Am Coll Radiol       Date:  2019-09       Impact factor: 5.532

Review 3.  Identifying Opportunities for Workflow Automation in Health Care: Lessons Learned from Other Industries.

Authors:  Teresa Zayas-Cabán; Saira Naim Haque; Nicole Kemper
Journal:  Appl Clin Inform       Date:  2021-07-28       Impact factor: 2.342

  3 in total

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