MO‐D‐213‐03: An Innovative Solution for Data Aggregation and Collection to Improve Quality of Peer Review Using a Cloud Based Platform Within a Large Oncology Network

Abstract

Purpose:Introduce a cloud‐based platform in a large multi‐site Oncology network which allows for the capture of empirical data, in aggregate, across multiple sites for the purpose of process standardization and metrics reporting as a pathway for physician and physicist peer review.Methods:The cloud‐based system stores site profiles, technical elements, and patient specific clinical elements for each facility in the peer review process. A total of 137 sites across 17 states were added including basic site info, staffing, and equipment infrastructure in order to prepare the portal for peer review data collection. Evaluation elements specific to oncology peer review were determined at onset. Physician and Physicist quality team meetings were held to define and approve the quality elements used in the peer review portal based on professional society guidelines and best practices. A total of 407 evaluation elements were included for Physician and Physicist evaluation (129, 278 respectively). The combined evaluation elements were defined into 17 main categories and drilled down further to 106 sub categories.Results:13 Physician and Physicist Peer reviews were analyzed at 9 locations for purposes of this abstract. These included a mixture of overall program related and specific patient chart focused reviews. 1923 evaluation elements were answered by a total of 9 Physician and Physicist reviewers (3, 6 respectively). Recommendations were selected on a scaled approach. General recommendation, Minor Recommendation and Major Recommendation were documented on an indicator of severity while Commendation was used to document findings of exceptional attributes in care.Conclusion:Using a cloud‐based platform is a valuable solution to resolve the issues that have inundated peer review issues of the past. Technology combined with strategic vision will change the future of peer review to administer standardization and predictive analytics throughout an entire network to raise the level of quality patient care.