However, there is a gap between theoretical vision for how systems should emerge and practical experience with encountering and solving the many issues that present themselves in the course of building working systems. This can lead misunderstanding of where efforts need to be focused.The move toward “big data” as part of routine practice in radiation oncology has begun. The persistent efforts of a nascent group of physicists and physicians developing clinically viable “big data” solutions are beginning to demonstrate working systems. Momentum will be added to these efforts by mandates accruing from the Patient Protection and Affordable Care Act and the impetus of the “Moon Shot on Cancer”. The vision for the future of Radiation Oncology in specific and health care in general is increasingly data centric.
This meeting will assemble researchers active in this area to exchange information on practical implementation of “big data” as part of routine clinical practice to promote practice quality improvement and research. The objective is to emerge with specific, practical recommendations for standard data elements to extract and clinical approaches to promote entry and accessibility of this data. The meeting summary will present a practical vision of timelines and priorities for radiation oncology.
Group leaders should accept a mandate to work with their groups in the months leading up to the work shop to create a preliminary document specifying practical recommendations for the radiation oncology community on data elements that can/should be gathered and clinical process steps needed to implement the changes. The preliminary recommendations will be presented as part of the work shop and should be refined based on discussions with the workshop attendees to create a finalized document that can be reported as proceedings from the meeting.
The meeting will be organized around four primary subjects with subgroups designated to collaborate ahead of the meeting on crafting and vetting recommendations that could be adopted by other clinics to promote pooling of data sets and improved automation of data collection.
Specific recommendations will be discussed and refined by the entire group of attendees as part of the meeting.
The meeting will be divided into two sections 1) Prioritizing and Standardizing what to measure, 2) Clinical and Enterprise Implementation.
Each breakout sessions will address three primary objectives three primary objectives 1) use case examples 2) discussion of barriers and 3) specific recommendations.·
- For use case examples groups should use the literature and their connections to identify examples of use cases where groups have successfully gathered and used data for large (>500) sets of patients to demonstrate the value of this data type.·
- Discussion of barriers, e.g. lack of routinely created as treated plan sums as a barrier to retrospectively extracting DVH data, should be used to highlight clinical processes and functionality in vended technologies that impeded ability to aggregated this data type. Suggestions for solutions should be discussed.·
- Specific recommendations should identify and prioritize data elements that if they were systematically gathered by all participants at their respective institutions would enable addressing practice quality improvement and translational research efforts that groups think are most important.
Following the breakout sessions, the findings for each data type group will be presented to the entire workshop group for discussion and additional recommendations. The core key elements group will have cross-over and collaboration leading up to the conference. A set of papers will be published to promulgate the recommendations of the workshop members.
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