The Experts below are selected from a list of 12378 Experts worldwide ranked by ideXlab platform
Michelle Passarge - One of the best experts on this subject based on the ideXlab platform.
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a swiss cheese Error detection method for real time epid based quality assurance and Error Prevention
2017Co-Authors: Michelle Passarge, M K Fix, P Manser, Marco Stampanoni, Jeffrey V SiebersAbstract:PURPOSE To develop a robust and efficient process that detects relevant dose Errors (dose Errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the Error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program. METHODS A Swiss cheese Error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment-plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed Error detection tests: an aperture check that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of Errors were selected to modify the original plan. A series of angle-resolved predicted EPID images was artificially generated for each test case, resulting in a sequence of pre-calculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both Error detection methods were applied to the generated test cases with realistic noise variations. RESULTS Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose Errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the Error, determination of Error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose Error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%. CONCLUSIONS An EPID-frame-based Error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose Errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose Errors, identified Errors in an earlier stage, displayed a higher robustness to noise variations and indicated the Error source. This article is protected by copyright. All rights reserved.
David L B Schwappach - One of the best experts on this subject based on the ideXlab platform.
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a vignette study to examine health care professionals attitudes towards patient involvement in Error Prevention
2012Co-Authors: David L B Schwappach, Olga Frank, Rachel DavisAbstract:Background Various authorities recommend the participation of patients in promoting patient safety, but little is known about health care professionals' (HCPs') attitudes towards patients' involvement in safety-related behaviours. Objective To investigate how HCPs evaluate patients' behaviours and HCP responses to patient involvement in the behaviour, relative to different aspects of the patient, the involved HCP and the potential Error. Design Cross-sectional fractional factorial survey with seven factors embedded in two Error scenarios (missed hand hygiene, medication Error). Each survey included two randomized vignettes that described the potential Error, a patient's reaction to that Error and the HCP response to the patient. Setting Twelve hospitals in Switzerland. Participants A total of 1141 HCPs (response rate 45%). Measurements Approval of patients' behaviour, HCP response to the patient, anticipated effects on the patient–HCP relationship, HCPs' support for being asked the question, affective response to the vignettes. Outcomes were measured on 7-point scales. Results Approval of patients' safety-related interventions was generally high and largely affected by patients' behaviour and correct identification of Error. Anticipated effects on the patient–HCP relationship were much less positive, little correlated with approval of patients' behaviour and were mainly determined by the HCP response to intervening patients. HCPs expressed more favourable attitudes towards patients intervening about a medication Error than about hand sanitation. Conclusions This study provides the first insights into predictors of HCPs' attitudes towards patient engagement in safety. Future research is however required to assess the generalizability of the findings into practice before training can be designed to address critical issues.
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barriers and facilitators to chemotherapy patients engagement in medical Error Prevention
2011Co-Authors: David L B Schwappach, M WernliAbstract:Background: Medical Errors are a serious threat to chemotherapy patients. Patients can make contributions to safety but little is known about the acceptability of Error-preventing behaviors and its predictors. Patients and methods: A cross-sectional survey study among chemotherapy patients treated at the oncology/ hematology unit of a regional hospital was conducted. Patients were presented vignettes of Errors and unsafe acts and responded to measures of attitudes, behavioral control, norms, barriers, and anticipated reaction. Results: A total of 479 patients completed the survey (52% response rate). Patients reported a high level of anticipated activity but intentions to engage for safety varied considerably between the hypothetical scenarios (range: 57%–96%, v 2 P < 0.001). Health, knowledge and staff time pressure were perceived as most important barriers. Instrumental [odds ratio (OR) = 1.3, P = 0.046] and experiential attitudes (OR = 1.4, P < 0.001), expectations attributed to clinical staff (OR = 1.2, P = 0.024) and behavioral control (OR = 1.8, P < 0.001) were predictors for patients’ behaviors. Conclusions: Patients are affirmative toward engaging for safety but perceive considerable barriers. Intentions to engage in Error Prevention vary by clinical context and are strongly influenced by attitudes, normative and control beliefs. To successfully involve patients in medical Error, Prevention clinicians need to address their patients’ beliefs
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predictors of chemotherapy patients intentions to engage in medical Error Prevention
2010Co-Authors: David L B Schwappach, M WernliAbstract:Patients can make contributions to the safety of chemotherapy administration but little is known about their motivations to participate in safety-enhancing strategies. The theory of planned behavior was applied to analyze attitudes, norms, behavioral control, and chemotherapy patients' intentions to participate in medical Error Prevention.
Jeffrey V Siebers - One of the best experts on this subject based on the ideXlab platform.
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a swiss cheese Error detection method for real time epid based quality assurance and Error Prevention
2017Co-Authors: Michelle Passarge, M K Fix, P Manser, Marco Stampanoni, Jeffrey V SiebersAbstract:PURPOSE To develop a robust and efficient process that detects relevant dose Errors (dose Errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the Error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program. METHODS A Swiss cheese Error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment-plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed Error detection tests: an aperture check that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of Errors were selected to modify the original plan. A series of angle-resolved predicted EPID images was artificially generated for each test case, resulting in a sequence of pre-calculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both Error detection methods were applied to the generated test cases with realistic noise variations. RESULTS Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose Errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the Error, determination of Error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose Error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%. CONCLUSIONS An EPID-frame-based Error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose Errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose Errors, identified Errors in an earlier stage, displayed a higher robustness to noise variations and indicated the Error source. This article is protected by copyright. All rights reserved.
Marco Stampanoni - One of the best experts on this subject based on the ideXlab platform.
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a swiss cheese Error detection method for real time epid based quality assurance and Error Prevention
2017Co-Authors: Michelle Passarge, M K Fix, P Manser, Marco Stampanoni, Jeffrey V SiebersAbstract:PURPOSE To develop a robust and efficient process that detects relevant dose Errors (dose Errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the Error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program. METHODS A Swiss cheese Error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment-plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed Error detection tests: an aperture check that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of Errors were selected to modify the original plan. A series of angle-resolved predicted EPID images was artificially generated for each test case, resulting in a sequence of pre-calculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both Error detection methods were applied to the generated test cases with realistic noise variations. RESULTS Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose Errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the Error, determination of Error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose Error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%. CONCLUSIONS An EPID-frame-based Error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose Errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose Errors, identified Errors in an earlier stage, displayed a higher robustness to noise variations and indicated the Error source. This article is protected by copyright. All rights reserved.
M Wernli - One of the best experts on this subject based on the ideXlab platform.
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barriers and facilitators to chemotherapy patients engagement in medical Error Prevention
2011Co-Authors: David L B Schwappach, M WernliAbstract:Background: Medical Errors are a serious threat to chemotherapy patients. Patients can make contributions to safety but little is known about the acceptability of Error-preventing behaviors and its predictors. Patients and methods: A cross-sectional survey study among chemotherapy patients treated at the oncology/ hematology unit of a regional hospital was conducted. Patients were presented vignettes of Errors and unsafe acts and responded to measures of attitudes, behavioral control, norms, barriers, and anticipated reaction. Results: A total of 479 patients completed the survey (52% response rate). Patients reported a high level of anticipated activity but intentions to engage for safety varied considerably between the hypothetical scenarios (range: 57%–96%, v 2 P < 0.001). Health, knowledge and staff time pressure were perceived as most important barriers. Instrumental [odds ratio (OR) = 1.3, P = 0.046] and experiential attitudes (OR = 1.4, P < 0.001), expectations attributed to clinical staff (OR = 1.2, P = 0.024) and behavioral control (OR = 1.8, P < 0.001) were predictors for patients’ behaviors. Conclusions: Patients are affirmative toward engaging for safety but perceive considerable barriers. Intentions to engage in Error Prevention vary by clinical context and are strongly influenced by attitudes, normative and control beliefs. To successfully involve patients in medical Error, Prevention clinicians need to address their patients’ beliefs
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predictors of chemotherapy patients intentions to engage in medical Error Prevention
2010Co-Authors: David L B Schwappach, M WernliAbstract:Patients can make contributions to the safety of chemotherapy administration but little is known about their motivations to participate in safety-enhancing strategies. The theory of planned behavior was applied to analyze attitudes, norms, behavioral control, and chemotherapy patients' intentions to participate in medical Error Prevention.