Every year, approximately 1,200 severe mistreatments happen in radiation therapy. Radiation therapy lawsuits rank in the top third of all medical specialties with an average of $313,000 per claim settled or litigated. The current method for detecting treatment errors is by a weekly patient chart check, where each treatment record is manually reviewed on a weekly basis. This labor-intensive and inefficient method prevents us from detecting the treatment error at an early stage. Here we propose a novel software system, ChartAlert, for automating patient chart checking. ChartAlert is a near real-time adaptive electronic checking system that can be configured to support different clinical workflows and different sources of patient treatment chart data in radiotherapy. We have already developed preliminary software based on the clinical workflow of our clinics. Our preliminary data indicated its effectiveness in automated patient chart checking. In this proposal, we will extend ChartAlert to general radiation oncology clinics. We will demonstrate the feasibility of the ChartAlert approach and its advantages over the standard manual checking method. We will determine the software specifications, design and implement a proof-of-concept system, and verify the proposed system at the partner site. Successful completion of these aims will demonstrate the feasibility and commercial potential of the ChartAlert approach. Ultimately, this work will result in an intelligent patient chart checking software, which will increase patient chart check efficiency, save staff time, improve cancer patient treatment safety, and preventing potential lawsuits.
Treatment errors in radiation oncology occur at a rate of 2% per patient, and radiation therapy lawsuits rank in the top third of all medical specialties with regard to claims made, claims paid, and damages. Current methods of detecting treatment errors are manual and inefficient. There is a critical need for efficient treatment error detection in order to save cost and improve patient safety. We propose to develop a scalable and comprehensive software system (ChartAlert) for automated patient chart error detection in radiation therapy. ChartAlert can be extended to other types of patient charts to check treatment and prescription consistency and improve patient safety, such as emergency medicine and pharmacy.
