Technical Note: Use of automation to eliminate shift errors.

Elizabeth L Covington,Rex A Cardan,Richard A Popple

doi:10.1002/acm2.12830

Elizabeth L Covington, Rex A Cardan + Show 1 more

Open Access

https://doi.org/10.1002/acm2.12830

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Abstract

PurposeTo create automated tools within the treatment planning system (TPS) that eliminate the common error pathway of providing incorrect shift instructions to therapists.Materials/MethodsTwo scripts were created within the TPS using the Eclipse API (Varian Medical Systems, Palo Alto, CA). One script detects whether or not the user origin has been placed correctly at the intersection of the simulation markers while the other calculates a shift instruction sheet that can be printed for treatment.ResultsAnalysis of our RO‐ILS database identified eight errors caused by improper setting of the user origin in the treatment planning system. The user origin script flagged all of the treatment plans for markers inconsistent with user origin. Automated calculation of shifts eliminated the error pathway of miscalculating or transcribing shift values.ConclusionAutomation can eliminate the common error pathway of providing the wrong shifts to therapists. The scripts have been made available as open‐source software for implementation at other radiotherapy clinics.

Highlights

Incident learning systems are a key component of safety culture in the medical field.[1,2,3,4,5] The Radiation Oncology Incident Learning System (RO‐ILS) is an incident learning system sponsored by both ASTRO and AAPM which enables users to submit radiation oncology‐related incidents to a national database.[6,7] With this database, RO‐ILS is able to review large numbers of events and provide education to clinics on the types of incidents reported via quarterly reports and case studies
Out of over two thousand reports, 396 were deemed the highest priority and coded with up to three keywords. When analyzing this subset of high priority events, 44% were found to belong to the following error pathways: “problematic plan approved for treatment,” “wrong shift instructions given to therapists,” and “wrong shift performed at treatment.”
During an analysis of our own RO‐ILS data, we found that one of our highest occurring errors was “wrong shift instruction given to therapists.”

Summary

Introduction

Incident learning systems are a key component of safety culture in the medical field.[1,2,3,4,5] The Radiation Oncology Incident Learning System (RO‐ILS) is an incident learning system sponsored by both ASTRO and AAPM which enables users to submit radiation oncology‐related incidents to a national database.[6,7] With this database, RO‐ILS is able to review large numbers of events and provide education to clinics on the types of incidents reported via quarterly reports and case studies. RO‐ILS can serve as an institution’s primary ILS for review and management of incidents. A recent paper by Ezzell et al looked at the highest priority reports from RO‐ILS.[6] Out of over two thousand reports, 396 were deemed the highest priority and coded with up to three keywords. When analyzing this subset of high priority events, 44% were found to belong to the following error pathways:

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