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Safety and Quality in Lung Radiotherapy

Gilmore, Martyn

[Thesis]. Manchester, UK: The University of Manchester; 2020.

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Abstract

Purpose: Investigate and appraise the use of Failure Mode Effect Analysis for routine risk assessment in lung radiotherapy and evaluate the efficacy of Quality Improvement measures introduced within the lung radiotherapy treatment planning process. Methods: A Multi-Disciplinary Team (MDT) was formed to carry out an FMEA for lung radiotherapy with one member acting as facilitator. A process map and list of failure modes was scored independently and discussed at a meeting where additional modes were identified and agreed. Timings were recorded and local incident data was compared to failure modes to determine the efficacy of the method. For the Quality Improvement (QI) event, three interventions were combined in a single change designed to improve the efficiency of lung radiotherapy plan checking. These were scripting of plan checks; the introduction of electronic questionnaires; and migration of the independent dose calculation task to the plan checker. Timings and plan rejection rates were passively gathered and compared for two separate three-month periods before and after intervention. Incident reports were also analysed to determine the number of false negatives for each period. Results: The FMEA was completed in less than 30 hours with 36 Failure modes identified. Of 38 incidents occurring since April 2017, 13 (34 %) were not predicted by the FMEA and a further four failure modes were introduced as a result. For the QI event, 105 and 96 patients were analysed pre and post intervention respectively and average overall planning timing was reduced by 2.8 hours (p <0.001). Plan rejections were reduced from 13/105 (12 %) to 7/96 (7%) although this was not statistically significant (p> 0.05). No overall change in the volume of incident reporting was found. Conclusions: FMEA can be used for routine risk assessment but should be combined with validation using incident reporting data wherever possible. Similarly, automated scripting, equestionnaires and process redesign can be used to improve efficiency in the planning process but quality improvement should include robust data collection and analysis to determine impact and inform further intervention.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Clinical Science
Degree programme:
DClinSci Medical Physics (MCC)
Publication date:
Location:
Manchester, UK
Total pages:
110
Abstract:
Purpose: Investigate and appraise the use of Failure Mode Effect Analysis for routine risk assessment in lung radiotherapy and evaluate the efficacy of Quality Improvement measures introduced within the lung radiotherapy treatment planning process. Methods: A Multi-Disciplinary Team (MDT) was formed to carry out an FMEA for lung radiotherapy with one member acting as facilitator. A process map and list of failure modes was scored independently and discussed at a meeting where additional modes were identified and agreed. Timings were recorded and local incident data was compared to failure modes to determine the efficacy of the method. For the Quality Improvement (QI) event, three interventions were combined in a single change designed to improve the efficiency of lung radiotherapy plan checking. These were scripting of plan checks; the introduction of electronic questionnaires; and migration of the independent dose calculation task to the plan checker. Timings and plan rejection rates were passively gathered and compared for two separate three-month periods before and after intervention. Incident reports were also analysed to determine the number of false negatives for each period. Results: The FMEA was completed in less than 30 hours with 36 Failure modes identified. Of 38 incidents occurring since April 2017, 13 (34 %) were not predicted by the FMEA and a further four failure modes were introduced as a result. For the QI event, 105 and 96 patients were analysed pre and post intervention respectively and average overall planning timing was reduced by 2.8 hours (p <0.001). Plan rejections were reduced from 13/105 (12 %) to 7/96 (7%) although this was not statistically significant (p> 0.05). No overall change in the volume of incident reporting was found. Conclusions: FMEA can be used for routine risk assessment but should be combined with validation using incident reporting data wherever possible. Similarly, automated scripting, equestionnaires and process redesign can be used to improve efficiency in the planning process but quality improvement should include robust data collection and analysis to determine impact and inform further intervention.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:323531
Created by:
Gilmore, Martyn
Created:
31st January, 2020, 15:22:06
Last modified by:
Gilmore, Martyn
Last modified:
2nd March, 2021, 11:00:56

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