Abstract
Background/Aims The aim is to educate programmers on how to pull chemotherapy infusion data from Clarity. The data are complex, and it can be take a while to learn the Clarity Data model, which can be difficult to understand. At Kaiser Permanente Northern California (KPNC), we developed a smaller model and an easy-to-understand workflow of the data. We would like to share our learnings, including how to link treatment plans, orders, dispensing, and administration together; and our knowledge of how to find completed treatment plans, days and cycles.
Methods To demonstrate the method for pulling data, we will show a data diagram with linkages to the different Beacon Clarity tables and a sample SQL explaining some of the filters/business logic and why the linkage must be done a certain way.
Results We hope users will find the information from KPNC’s experience useful, and that by the end of the presentation, users will gain a better understanding of how to pull chemotherapy infusion data from Clarity. We also hope to save other sites from having to spend as much time doing the initial analysis work that KPNC did.
Conclusions For KPNC, pulling chemotherapy infusion data was eye-opening. The complexity of the data was significant, particularly linking the data from the initial “planned” treatments to orders, episodes, flowsheets, dispensing, mixing the medications, and finally to what is administered. Often times treatment plans were changed along the way due to chemotherapy reaction or toxicity, and linking the data back to the original plan was therefore complicated. We will review what we learned in this process with other users, so that they may benefit from KPNC’s experience.
