Rishabh Kapoor

American Association of Physicists in Medicine Task Group 263: Standardizing Nomenclatures in Radiation Oncology

A substantial barrier to the single- and multi-institutional aggregation of data to supporting clinical trials, practice quality improvement efforts, and development of big data analytics resource systems is the lack of standardized nomenclatures for expressing dosimetric data. To address this issue, the American Association of Physicists in Medicine (AAPM) Task Group 263 was charged with providing nomenclature guidelines and values in radiation oncology for use in clinical trials, data-pooling initiatives, population-based studies, and routine clinical care by standardizing: (1) structure names across image processing and treatment planning system platforms; (2) nomenclature for dosimetric data (eg, dose–volume histogram [DVH]-based metrics); (3) templates for clinical trial groups and users of an initial subset of software platforms to facilitate adoption of the standards; (4) formalism for nomenclature schema, which can accommodate the addition of other structures defined in the future. A multisociety, multidisciplinary, multinational group of 57 members representing stake holders ranging from large academic centers to community clinics and vendors was assembled, including physicists, physicians, dosimetrists, and vendors. The stakeholder groups represented in the membership included the AAPM, American Society for Radiation Oncology (ASTRO), NRG Oncology, European Society for Radiation Oncology (ESTRO), Radiation Therapy Oncology Group (RTOG), Children’s Oncology Group (COG), Integrating Healthcare Enterprise in Radiation Oncology (IHE-RO), and Digital Imaging and Communications in Medicine working group (DICOM WG); A nomenclature system for target and organ at risk volumes and DVH nomenclature was developed and piloted to demonstrate viability across a range of clinics and within the framework of clinical trials. The final report was approved by AAPM in October 2017. The approval process included review by 8 AAPM committees, with additional review by ASTRO, European Society for Radiation Oncology (ESTRO), and American Association of Medical Dosimetrists (AAMD). This Executive Summary of the report highlights the key recommendations for clinical practice, research, and trials.

Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology

It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision-making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.

SU-F-T-223: Radiotherapy Incident Reporting and Analysis System (RIRAS):Early Experience

BACKGROUND & PURPOSE RIRAS is a web-based information system deployed on the Veterans Health Administration intranet in early 2014 to collect adverse events and good catch data; analyze the causes and contributing factors; and find ways to prevent future occurrences. MATERIAL AND METHODS Incident learning consists of a feedback loop which starts with reporting an event, followed by analysis of contributing factors, and culminates in the development of a patient safety work product (PSWP) to prevent recurrence. RIRAS permits both anonymous and non-anonymous reporting. Each report is analyzed by a team of medical physicists who are independent of the reporting facility. The analysts usually contact the reporting facilities for additional information. We analyzed all reports and held telephonic interviews (when necessary) with the reporters. We then generated PSWPs with corrective/preventive and learning actions. Anonymous reporting is handled in the same manner, except without the ability to further interview the reporter. RESULTS In a significant number of reports, the causes and recommended preventive actions were considerably altered by the independent analysis and additional information from the facility. 130 reports have been entered in RIRAS; 9 misadministrations, 83 good catches, 3 anonymous good catches, and 35 earlier reported incidents from FY2005-14. 45% of the reported incidents occurred in the treatment delivery stages, 19% in on-treatment management, and 16% in pre-treatment verification. 80% of the good catches were found in the treatment delivery workflow. Majority of these incidents were due to inconsistent patient setup instructions or documentation, nonadherence to policies and procedures, lax time-out policy, distracted RTTs, and inadequate RTT staffing. CONCLUSION RIRAS has identified many areas for improvement and elevated the quality and safety of radiation treatments in the VHA. We found that the ability to learn is significantly diminished when the analysts do not have the ability to request additional information.

A smart healthcare portal for clinical decision making and precision medicine

There has been an unprecedented generation of healthcare data at clinical practices. With the availability of advanced computing frameworks and the ability to electronically mine data from disparate sources (e.g. demographics, genetics, imaging, treatment, clinical decisions, and outcomes) big data research in medicine has become a very active field of interest. In this paper, we discuss the challenges associated with designing clinical decision support systems that try to leverage such disparate data sources and create smart healthcare tools to aid medical practitioners for better patient care and treatment plans. We next propose an integrated data curation, storage and analytics portal, called HINGE (the Health Information Gateway and Exchange application), that can effectively address many of the outstanding challenges in this domain. HINGE specifically caters to healthcare data from radiation oncology patients however, the underlying formalisms and principles, as discussed here, are readily extendible to other disease types making it an attractive tool for the design of next generation clinical decision support systems.

Quality Improvements of Veterans Health Administration Radiation Oncology Services Through Partnership for Accreditation With the ACR

Approximately 20,000 US veterans receive radiation oncology services at a Veterans Healthcare Administration (VHA) medical facility each year. They currently have access to advanced technologies, which include image-guided intensity-modulated radiotherapy, stereotactic radiosurgery, and stereotactic body radiation therapy. Although this provides access to cancer therapies that are modern, safe, and efficient, the technical complexities of these treatments and clinical decision making that goes into the patient selection and prescriptions demand quality assurances at each VHA practice. To meet the challenges of this need, the VHA established a partnership in 2008 with the ACRs Radiation Oncology Practice Accreditation Program (ACR-ROPA). This report summarizes the experience of this ongoing partnership and demonstrates the combined impact of the VHAs mandate for ACR-ROPA accreditation and internal monitoring of all identified corrective actions at each of its radiation oncology practices.

SU-E-T-469: Implementation of VAs Web-Based Radiotherapy Incident Reporting and Analysis System (RIRAS)

Purpose: This Web-based Radiotherapy Incident Reporting and Analysis System (RIRAS) is a tool to improve quality of care for radiation therapy patients. This system is an important facet of continuing effort by our community to maintain and improve safety of radiotherapy.Material and Methods: VA’s National Radiation Oncology Program office has embarked on a program to electronically collect adverse events and good-catch data of radiation treatment of over 25,000 veterans treated with radiotherapy annually. This VA-Intranet based software design has made use of dataset taxonomies and data dictionaries defined in AAPM/ASTRO reports on error reporting. We used proven industrial and medical event reporting techniques to avoid several common problems faced in effective data collection such as incomplete data due to data entry fatigue by the reporters, missing data due to data difficult to obtain or not familiar to most reporters, missing reports due to fear of reprisal etc. This system encompasses the entire feedback loop of reporting an incident, analyzing it for salient details, and developing interventions to prevent it from happening again. The analysis reports with corrective, learning actions are shared with the reporter/facility and made public to the community (after deidentification) as part of the learning process. Results: Till date 50 incident/good catches have been reported in RIRAS and we have completed analysis on 100% of these reports. This is done due to the fact that each reported incidents is investigated and a complete analysis/patient-safety-work-product report is generated by radiation oncology domain-experts. Conclusions Because of the completeness of the data, the system has enabled us to analyze process steps and track trends of major errors which in the future will lead to implementing system wide process improvement steps and safe standard operating procedures for each radiotherapy treatment modality/technique and fulfills our goal of “Effecting Quality While Treating Safely”. RIRAS developed and copyrighted by TSG Innovations Inc.

SU-E-T-524: Web-Based Radiation Oncology Incident Reporting and Learning System (ROIRLS)

PURPOSE Describe a Web-based Radiation Oncology Incident Reporting and Learning system that has the potential to improve quality of care for radiation therapy patients. This system is an important facet of continuing effort by our community to maintain and improve safety of radiotherapy. MATERIAL AND METHODS The VA National Radiation Oncology Program office has embarked on a program to electronically collect adverse events and near miss data of radiation treatment of over 25,000 veterans treated with radiotherapy annually. Software used for this program is deployed on the VAs intranet as a Website. All data entry forms (adverse event or near miss reports, work product reports) utilize standard causal, RT process step taxonomies and data dictionaries defined in AAPM and ASTRO reports on error reporting (AAPM Work Group Report on Prevention of Errors and ASTROs safety is no accident report). All reported incidents are investigated by the radiation oncology domain experts. This system encompasses the entire feedback loop of reporting an incident, analyzing it for salient details, and developing interventions to prevent it from happening again. The operational workflow is similar to that of the Aviation Safety Reporting System. This system is also synergistic with ROSIS and SAFRON. RESULTS The ROIRLS facilitates the collection of data that help in tracking adverse events and near misses and develop new interventions to prevent such incidents. The ROIRLS electronic infrastructure is fully integrated with each registered facility profile data thus minimizing key strokes and multiple entries by the event reporters. CONCLUSIONS OIRLS is expected to improve the quality and safety of a broad spectrum of radiation therapy patients treated in the VA and fulfills our goal of Effecting Quality While Treating Safely The Radiation Oncology Incident Reporting and Learning System software used for this program has been developed, conceptualized and maintained by TSG Innovations Inc. and is deployed on the VA intranet as a Website. The Radiation Oncology Incident Reporting and Learning System software used for this program has been developed, conceptualized and maintained by TSG Innovations Inc. and is deployed on the VA intranet as a Website.

MO‐D‐105‐02: Veteran Health Administration : Radiation Oncology Quality and Safety Initiative (VHA‐ROQSI)

PURPOSE The overall goal of VHA-ROQSI is to monitor quality, safety, and effectiveness of radiotherapy within VHA. The electronic infrastructure developed to achieve these objectives can serve as a model for the radiation oncology community at large. METHOD AND MATERIAL The VHA-ROQSI is an initiative of the VHAs National Radiation Oncology Program office with an objective of electronically collecting and aggregating data to assess quality and safety of radiation treatment delivery and determine disease site-specific outcomes. The data collected will include; information on radiotherapy planning, delivery equipment, services provided patient volume, and quality assurance activities at each facility, calibration, accreditation and credentialing status of each facility. The integrated infrastructure will facilitate a rapid Web-based proactive peer review of all complex treatment plans and it will allow each facility to report adverse events and near miss information on patients for review by radiation oncology domain experts. The de-identified outcome data on patients will be abstracted directly from the hospital information system for population-based outcome analysis. RESULTS We have designed an electronic infrastructure that minimizes key strokes and multiple entries of redundant data by end users to accomplish each one of the aforementioned objectives. The prototypes of various modules for electronic data collection have been developed and are in beta testing. Once completed, the integrated system will facilitate peer review of complex treatment plans, collection of data elements for treatment quality and outcome assessment, and tracking of adverse events and near misses on patient treatments. CONCLUSION The VHA-ROQSI overcomes the challenge of submitting redundant data to disparate sources. This electronic infrastructure will circumvent the need for separate registries for outcome, quality, and safety tracking under development by various stakeholders at the present time. Disclosure: Rishabh Kapoor: Stocks: TSG Innovations Inc.

SU‐E‐T‐26: Automated Plan Evaluation System: Design and Implementation

Purpose: To present software for a Radiation therapy facility that will simplify the process of dosimetric plan evaluation and will help clinicians and physicists to review the plan. Materials and method: Every treatment plan requires certain dosimetriccharacteristics or parameters to be evaluated, which are essential for the assessment of a treatment plan. One can automate this process with the software that can understand the treatment plan and DVH data and gives you the desired results. This software accepts DICOM RT data from IHE‐RO compliant Varian Eclipse v 8.6 and computes DVH. There is also a facility to define disease site, technique and fractionation specific templates for dose volume constraints. This software helps you to analyze the normal tissue tolerances with the data given in the literature and also gives user the freedom to use α/β ratios to modify the tolerance values in accordance with dose‐fractionation scheme. The dosimetric indices such as conformity index and homogeneity index can also be calculated and compared with the user defined criteria in the template. Results: The prototype system has been used to design various templates for different treatment sites such as head and neck and breast. These templates are used to evaluate plan and dosimetric parameters for several patients. Conclusion: This prototype software provides a simplified solution for an automated dosimetric plan evaluation. The dosimetric parameters used in the plan evaluation is stored in an databasearchive for all the patients and this data is intended to used for further analysis.