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Continuing Quality Improvement Radiation Oncology

Continuing Quality Improvement Radiation Oncology. Jeff Michalski, MD, MBA, FACR Professor and Vice-Chair Department of Radiation Oncology Washington University School of Medicine. Modern RT.

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Continuing Quality Improvement Radiation Oncology

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  1. Continuing Quality ImprovementRadiation Oncology Jeff Michalski, MD, MBA, FACR Professor and Vice-Chair Department of Radiation Oncology Washington University School of Medicine

  2. Modern RT • Recent sophistication – large fraction of modern treatment technology and practices developed in the past ten years • High technical complexity • Multiple systems (software and hardware) • Limited to non-existent guidance/standards • High pressure • Increased potential for catastrophic failures

  3. Staff and public exposures Suboptimal treatments Misadministrations Underdose Overdose Anatomical misses Magnitude From few percent to lethal doses From couple of millimeters to complete misses Regulatory Nuclear Regulatory Commission Errors that do not necessarily affect patients but have regulatory/legal consequences Sources Staff Software Hardware Random Affect one to few patients Systematic Affect hundreds of patients Potentially in a short period Errors in Radiation Oncology

  4. BackgroundGlobal Problem “…it calls into question the integrity of hospital systems and their ability to pick up errors and the capability to make sustainable changes.” Sir Liam Donaldson, Chief Medical Officer, Department of Health • Towards Safer Radiotherapy. London: The Royal College of Radiologists, 2008. • Radiotherapy Risk Profile, Geneva: World Health Organization, 2009.

  5. Error Reporting • We are not airline industry nor nuclear power • Perfection in complex systems across hundreds of diverse clinics is impossible • Reporting systems for sake of reporting alone are a great way to squander resources and demoralize staff • Error reporting as a part of broader process improvement efforts can be very valuable

  6. Event Reporting • Mandatory (statutory) • Reporting required by law • NRC in U.S. • State requirements • Mainly concentrated on well defined treatment delivery errors • Guidelines for near-miss reporting typically not provided • Voluntary • Mainly at institutional level • Some states in the U.S. have voluntary reporting systems – utility for radonc not clear • Errors and near misses tracked

  7. Voluntary ReportingDependent on Many Factors • Culture • Reporting guidelines • Reporting system • Competence to interpret reported data • Willingness to implement, when necessary, significant changes based on collected data and subsequent analyses • Ability to share the collected data and provide feedback

  8. Reporting Culture • Indemnity against disciplinarily proceedings and retribution • Confidentiality • To the extent practical, separation of those collecting the event data from those with the authority to impose disciplinary actions • An efficient method for event submission • A rapid, intelligent, and broadly available method for feedback to the reporting community

  9. Taxonomy and Event Classification • Event reporting should enable process improvement • This requires efficient processing and analysis of data • Submitted events must be classified and organized • Enables efficient processing, analysis, and communication of data and trends

  10. Web-Based Reporting

  11. System AcceptancePaper

  12. System AcceptanceVoluntary Web-based Mutic et al, Submitted for publication, Med Phys, May 2010

  13. System AcceptanceVoluntary Web-based Mutic et al, Submitted for publication, Med Phys, May 2010

  14. Therapy Nursing Dosimetry Physics Simulator

  15. What are we doing? • Organizational learning • Error and near miss reporting • Use reported events to improve processes and clinical tools • Standardization • QAIS • QC – Based on reported errors and risk analysis • Electronic • Automated • Intelligent • Workflow tools - Based on reported errors and risk analysis

  16. RT TPS Database R&V Database Electronic Chart Check Work Flow OQA Database rtog Query Scripts ascii dcm txt EcCk • Warning and Alerts • Pending work • Delivery problem indicators • Independent checks • TPS & RV • Prescription • Field Parameters • Consistency Reports etc • Protocol Compliance • Data • Approvals, etc • Statistics • Benchmarking • Future system improvements

  17. Sample EcCk Report

  18. Precheck scripts - workflow

  19. Precheck: sample report

  20. Plan Quality Benchmarking Moore et al, Submitted for publication, IJROBP, May 2010

  21. Dynalog-based IMRT QA Report

  22. Tomotherapy: Sinogram based QA

  23. The downside to the electronic worldAs implemented today • Record and Verify (R&V) system was originally designed to operate as an independent system (Big Brother) • Today these systems are integral part of the delivery process and the independent verification process is missing • If data in the R&V system is wrong there is much less opportunity and chance that the error may be discovered

  24. Possible Solution • Electronic QA system (EQS) • Independent system which compares TPS data with the data in the R&V system • Greatly improves ability to compare initial data transfer and consistency of data in the R&V

  25. Distributed Data Collection Each clinic with its own independent database Centralized Database Manufacturers Regulatory Agencies Professional Societies

  26. Conclusion • Error reporting in technologically advanced healthcare presents an opportunity to improve patient safety • Independent oversight of established systems is desirable to monitor safety systems and implement immediate intervention • Centralized reporting of errors and similar events (near misses, latent errors) is highly encouraged • Use reported errors to improve commercial systems

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