The Experts below are selected from a list of 30672 Experts worldwide ranked by ideXlab platform
David Joseph - One of the best experts on this subject based on the ideXlab platform.
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detailed Review and analysis of complex radiotherapy clinical trial planning data evaluation and initial experience with the swan software system
2008Co-Authors: Martin A Ebert, Annette Haworth, Rachel Kearvell, B Hooton, Rhonda Coleman, Nigel Spry, Sean Bydder, David JosephAbstract:Abstract Aim Contemporary radiotherapy clinical trials typically require complex three-dimensional (3D) treatment planning. This produces large amounts of data relating technique and dose delivery for correlation with patient outcomes. Assessment of the quality of this information is required to ensure protocol compliance, to quantify the variation in treatments given to patients and to enhance the power of studies to determine correlates of patient outcomes. Materials and methods A software system (‘SWAN’) was developed to facilitate the objective analysis, quality-assurance and Review of digital treatment planning data from multi-centre radiotherapy trials. The utility of this system was assessed on the basis of its functionality and our experience of its use in the context of multi-centre clinical trials and trials-support activities. Results The SWAN system has been shown to have the functionality required for use in several multi-centre trials, including Automated Review and archive processes. Approximately 800 treatment plans from over 30 participating institutions have so far been assessed with the system for several treatment planning scenarios. To illustrate this we include a description of the use of the system for a large-recruitment prostate radiotherapy trial being undertaken in Australasia, including examples of how the Review process has changed clinical practice. Conclusion The successful implementation of SWAN has been demonstrated in a number of clinical trials. The software provides an opportunity for comprehensive Review of treatment parameters that could impact on clinical outcomes and trial results. Such quality-assurance (QA) has previously been difficult or impossible to achieve, particularly for a clinical trial involving large numbers of patients. Such Reviews have highlighted inconsistencies in clinical practice that have since been addressed through feedback from the Review process. The process of data collection and Review should be undertaken by dedicated, experienced and skilled staff in order to ensure efficiency.
Martin A Ebert - One of the best experts on this subject based on the ideXlab platform.
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detailed Review and analysis of complex radiotherapy clinical trial planning data evaluation and initial experience with the swan software system
2008Co-Authors: Martin A Ebert, Annette Haworth, Rachel Kearvell, B Hooton, Rhonda Coleman, Nigel Spry, Sean Bydder, David JosephAbstract:Abstract Aim Contemporary radiotherapy clinical trials typically require complex three-dimensional (3D) treatment planning. This produces large amounts of data relating technique and dose delivery for correlation with patient outcomes. Assessment of the quality of this information is required to ensure protocol compliance, to quantify the variation in treatments given to patients and to enhance the power of studies to determine correlates of patient outcomes. Materials and methods A software system (‘SWAN’) was developed to facilitate the objective analysis, quality-assurance and Review of digital treatment planning data from multi-centre radiotherapy trials. The utility of this system was assessed on the basis of its functionality and our experience of its use in the context of multi-centre clinical trials and trials-support activities. Results The SWAN system has been shown to have the functionality required for use in several multi-centre trials, including Automated Review and archive processes. Approximately 800 treatment plans from over 30 participating institutions have so far been assessed with the system for several treatment planning scenarios. To illustrate this we include a description of the use of the system for a large-recruitment prostate radiotherapy trial being undertaken in Australasia, including examples of how the Review process has changed clinical practice. Conclusion The successful implementation of SWAN has been demonstrated in a number of clinical trials. The software provides an opportunity for comprehensive Review of treatment parameters that could impact on clinical outcomes and trial results. Such quality-assurance (QA) has previously been difficult or impossible to achieve, particularly for a clinical trial involving large numbers of patients. Such Reviews have highlighted inconsistencies in clinical practice that have since been addressed through feedback from the Review process. The process of data collection and Review should be undertaken by dedicated, experienced and skilled staff in order to ensure efficiency.
T Fox - One of the best experts on this subject based on the ideXlab platform.
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Automated data mining of a proprietary database system for physician quality improvement
2008Co-Authors: Peter A S Johnstone, Tim Crenshaw, Diane G Cassels, T FoxAbstract:Purpose Physician practice quality improvement is a subject of intense national debate. This report describes using a software data acquisition program to mine an existing, commonly used proprietary radiation oncology database to assess physician performance. Methods and Materials Between 2003 and 2004, a manual analysis was performed of electronic portal image (EPI) Review records. Custom software was recently developed to mine the record-and-verify database and the Review process of EPI at our institution. In late 2006, a report was developed that allowed for immediate Review of physician completeness and speed of EPI Review for any prescribed period. Results The software extracted >46,000 EPIs between 2003 and 2007, providing EPI Review status and time to Review by each physician. Between 2003 and 2007, the department EPI Review improved from 77% to 97% (range, 85.4–100%), with a decrease in the mean time to Review from 4.2 days to 2.4 days. The initial intervention in 2003 to 2004 was moderately successful in changing the EPI Review patterns; it was not repeated because of the time required to perform it. However, the implementation in 2006 of the Automated Review tool yielded a profound change in practice. Using the software, the Automated chart Review required ∼1.5 h for mining and extracting the data for the 4-year period. Conclusion This study quantified the EPI Review process as it evolved during a 4-year period at our institution and found that automation of data retrieval and Review simplified and facilitated physician quality improvement.
Karen S Kmetik - One of the best experts on this subject based on the ideXlab platform.
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Automated Review of electronic health records to assess quality of care for outpatients with heart failure
2007Co-Authors: David W Baker, Stephen D Persell, Jason A Thompson, Neilesh S Soman, Karen M Burgner, David T Liss, Karen S KmetikAbstract:In this study, Baker and colleagues compared Automated Review of electronic health record (EHR) fields with Automated Review followed by manual Review of the EHR to assess the quality of care of ou...
Michael Jeffers - One of the best experts on this subject based on the ideXlab platform.
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image analysis as an adjunct to manual her 2 immunohistochemical Review a diagnostic tool to standardize interpretation
2010Co-Authors: Lynne Dobson, Catherine Conway, Alan Hanley, Alexander W Johnson, Sean Costello, Anthony Ogrady, Yvonne Connolly, Hilary Magee, Daniel G Oshea, Michael JeffersAbstract:Dobson L, Conway C, Hanley A, Johnson A, Costello S, O’Grady A, Connolly Y, Magee H, O’Shea D, Jeffers M & Kay E (2010) Histopathology 57, 27–38 Image analysis as an adjunct to manual HER-2 immunohistochemical Review: a diagnostic tool to standardize interpretation Aims: Accurate determination of HER-2 status is critical to identify patients for whom trastuzumab treatment will be of benefit. Although the recommended primary method of evaluation is immunohistochemistry, numerous reports of variability in interpretation have raised uncertainty about the reliability of results. Recent guidelines have suggested that image analysis could be an effective tool for achieving consistent interpretation, and this study aimed to assess whether this technology has potential as a diagnostic support tool. Methods and results: Across a cohort of 275 cases, image analysis could accurately classify HER-2 status, with 91% agreement between computer-aided classification and the pathology Review. Assessment of the continuity of membranous immunoreactivity in addition to intensity of reactivity was critical to distinguish between negative and equivocal cases and enabled image analysis to report a lower referral rate of cases for confirmatory fluorescence in situ hybridization (FISH) testing. An excellent concordance rate of 95% was observed between FISH and the Automated Review across 136 informative cases. Conclusions: This study has validated that image analysis can robustly and accurately evaluate HER-2 status in immunohistochemically stained tissue. Based on these findings, image analysis has great potential as a diagnostic support tool for pathologists and biomedical scientists, and may significantly improve the standardization of HER-2 testing by providing a quantitative reference method for interpretation.
