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. 2021 Sep 29;7(1):100812.
doi: 10.1016/j.adro.2021.100812. eCollection 2022 Jan-Feb.

An Investigation of Radiation Treatment Learning Opportunities in Relation to the Radiation Oncology Electronic Medical Record: A Single Institution Experience

Y Jessica Huang  1 , Vikren Sarkar  1 , Adam Paxton  1 , Hui Zhao  1 , Frances Fan-Chi Su  1 , Ryan Price  1 , Bill J Salter  1
Affiliations

An Investigation of Radiation Treatment Learning Opportunities in Relation to the Radiation Oncology Electronic Medical Record: A Single Institution Experience

Y Jessica Huang et al. Adv Radiat Oncol. .

Abstract

Purpose: A modern radiation oncology electronic medical record (RO-EMR) system represents a sophisticated human-computer interface with the potential to reduce human driven errors and improve patient safety. As the RO-EMR becomes an integral part of clinical processes, it may be advantageous to analyze learning opportunities (LO) based on their relationship with the RO-EMR. This work reviews one institution's documented LO to: (1) study their relationship with the RO-EMR workflow, (2) identify best opportunities to improve RO-EMR workflow design, and (3) identify current RO-EMR workflow challenges.

Methods and materials: Internal LO reports for an 11-year contiguous period were categorized by their relationship to the RO-EMR. We also identify the specific components of the RO-EMR used or involved in each LO. Additionally, contributing factor categories from the ASTRO/AAPM sponsored Radiation Oncology Incident Learning System's (RO-ILS) nomenclature was used to characterize LO directly linked to the RO-EMR.

Results: A total of 163 LO from the 11-year period were reviewed and analyzed. Most (77.2%) LO involved the RO-EMR in some way. The majority of the LO were the results of human/manual operations. The most common RO-EMR components involved in the studied LO were documentation related to patient setup, treatment session schedule functionality, RO-EMR used as a communication/note-delivery tool, and issues with treatment accessories. Most of the LO had staff lack of attention and policy not followed as 2 of the highest occurring contributing factors.

Conclusions: We found that the majority of LO were related to RO-EMR workflow processes. The high-risk areas were related to manual data entry or manual treatment execution. An evaluation of LO as a function of their relationship with the RO-EMR allowed for opportunities for improvement. In addition to regular radiation oncology quality improvement review and policy update, automated functions in RO-EMR remain highly desirable.

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Figures

Fig 1
Figure 1
Radiation oncology electronic medical record (RO-EMR) related learning opportunities (LO) categorization decision tree.
Fig 2
Figure 2
Results of specific radiation oncology electronic medical record (RO-EMR) components contributing to learning opportunities (LO) from either (a) RO-EMR input side or (b) RO-EMR output side.
Fig 3
Figure 3
An example of single page display for pretreatment time out. This example contains the patient name, date of birth, prescription/dose site overview, special instruction, and imaging guidance instruction for the treatment site.
See this image and copyright information in PMC

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