The Fusion of Incident Learning and Failure Mode and Effects Analysis for Data-Driven Patient Safety Improvements

Paradis, Kelly C.; Naheedy, Katherine Woch; Matuszak, Martha M.; Kashani, Rojano; Burger, Pamela; Moran, Jean M.

doi:10.1016/j.prro.2020.02.015

Cited by 8 publications

(14 citation statements)

References 41 publications

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“…Routine physics quality plan check was employed for the automated plans, which then proceeded on to a second phase of clinical evaluation. Before clinical use, a prospective hazard analysis was performed using a streamlined failure mode and effects analysis described by Paradis et al 38 A process map for clinical use of the script was generated with associated hazards (failure modes) from multidisciplinary feedback. The priority score for each failure mode (a version of the relative risk priority number from TG-100) was assigned as high, medium, or low.…”

Section: Methodsmentioning

confidence: 99%

Development and Clinical Implementation of an Automated Virtual Integrative Planner for Radiation Therapy of Head and Neck Cancer

Jaworski

Vineberg²,

Yao³

et al. 2023

Advances in Radiation Oncology

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Section: Methodsmentioning

confidence: 99%

Development and Clinical Implementation of an Automated Virtual Integrative Planner for Radiation Therapy of Head and Neck Cancer

Jaworski

Vineberg²,

Yao³

et al. 2023

Advances in Radiation Oncology

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“…The first stage identified the step in the institution care path the event originated, at which step it was caught, and how often a relevant safeguard designed to catch the event was crossed. All events considered as incidents were assigned a severity score based on the 1 to 3 initial scoring scale (representing low, medium, or high severity) used as part of the AAPM Task Group Report 275 28 and by one of the collaborating institutions 24 . Other scales also exist, such as the French Nuclear Safety Authority.…”

Section: Methodsmentioning

confidence: 99%

“…This approach has been widely used in radiation oncology at both the institutional and societal level 19–23 . Importantly, there is recent work combining both an ILS and FMEA to complement the strengths of both approaches 13,24 …”

mentioning

confidence: 99%

Multi-Institutional Stereotactic Body Radiation Therapy Incident Learning: Evaluation of Safety Barriers Using a Human Factors Analysis and Classification System

et al. 2022

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ObjectivesStereotactic body radiation therapy (SBRT) can improve therapeutic ratios and patient convenience, but delivering higher doses per fraction increases the potential for patient harm. Incident learning systems (ILSs) are being increasingly adopted in radiation oncology to analyze reported events. This study used an ILS coupled with a Human Factor Analysis and Classification System (HFACS) and barriers management to investigate the origin and detection of SBRT events and to elucidate how safeguards can fail allowing errors to propagate through the treatment process.MethodsReported SBRT events were reviewed using an in-house ILS at 4 institutions over 2014–2019. Each institution used a customized care path describing their SBRT processes, including designated safeguards to prevent error propagation. Incidents were assigned a severity score based on the American Association of Physicists in Medicine Task Group Report 275. An HFACS system analyzed failing safeguards.ResultsOne hundred sixty events were analyzed with 106 near misses (66.2%) and 54 incidents (33.8%). Fifty incidents were designated as low severity, with 4 considered medium severity. Incidents most often originated in the treatment planning stage (38.1%) and were caught during the pretreatment review and verification stage (37.5%) and treatment delivery stage (31.2%). An HFACS revealed that safeguard failures were attributed to human error (95.2%), routine violation (4.2%), and exceptional violation (0.5%) and driven by personnel factors 32.1% of the time, and operator condition also 32.1% of the time.ConclusionsImproving communication and documentation, reducing time pressures, distractions, and high workload should guide proposed improvements to safeguards in radiation oncology.

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“…Our team has extensive experience with using safety and event reporting to drive software development, 10 as well as with incorporating risk analysis techniques such as failure mode and effects analysis 18,25 to enhance patient safety in our clinic. When the scope of our software development expanded beyond read-only software, our team incorporated a hazard analysis into our software release process (see Supplementary Materials -Multimedia File 3 for an example).…”

Section: Prospective and Retrospective Risk Analysesmentioning

confidence: 99%

“…We have previously reported on a subset of our software to support patient safety 10,12 as well as on how to leverage a fusion of incident learning and failure mode and effects analysis to enable data-driven targeting of high-risk errors. 18 In this work, we describe our development and implementation cycle for the safe use of in-house developed clinical software. In the Methods and Materials section, we report on how the cycle was modified from its initial development in support of UMPlan, our in-house clinical TPS at the University of Michigan, 19,20 and was then adapted to support use of other clinical software developed in house.…”

Section: Introductionmentioning

confidence: 99%

A Safe and Practical Cycle for Team-Based Development and Implementation of In-House Clinical Software

Moran¹,

Paradis

Hadley

et al. 2022

Advances in Radiation Oncology

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Due to a gap in published guidance, we describe our robust cycle of in-house clinical software development and implementation, which has been used for years to facilitate the safe treatment of all patients in our clinics. Methods and Materials: Our software development and implementation cycle requires clarity in communication, clearly defined roles, thorough commissioning, and regular feedback. Cycle phases include design requirements and use cases, development, physics evaluation testing, clinical evaluation testing, and full clinical release. Software requirements, release notes, test suites, and a commissioning report are created and independently reviewed before clinical use. Software deemed to be high-risk, such as those that are writable to a database, incorporate the use of a formal, team-based hazard analysis. Incident learning is used to both guide initial development and improvements as well as to monitor the safe use of the software. Results: Our standard process builds in transparency and establishes high expectations in the development and use of custom software to support patient care. Since moving to a commercial planning system platform in 2013, we have applied our team-based software release process to 16 programs related to scripting in the treatment planning system for the clinic. Conclusions: The principles and methodology described here can be implemented in a range of practice settings regardless of whether or not dedicated resources are available for software development. In addition to teamwork with defined roles, documentation, and use of incident learning, we strongly recommend having a written policy on the process, using phased testing, and incorporating independent oversight and approval before use for patient care. This rigorous process ensures continuous monitoring for and mitigatation of any high risk hazards.

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The Fusion of Incident Learning and Failure Mode and Effects Analysis for Data-Driven Patient Safety Improvements

Cited by 8 publications

References 41 publications

Development and Clinical Implementation of an Automated Virtual Integrative Planner for Radiation Therapy of Head and Neck Cancer

Development and Clinical Implementation of an Automated Virtual Integrative Planner for Radiation Therapy of Head and Neck Cancer

Multi-Institutional Stereotactic Body Radiation Therapy Incident Learning: Evaluation of Safety Barriers Using a Human Factors Analysis and Classification System

A Safe and Practical Cycle for Team-Based Development and Implementation of In-House Clinical Software

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