SU-E-T-191: PITSTOP: Process Improvement Techniques, Software Tools, and Operating Principles for a Quality Initiative Discovery Framework.

Abstract

To develop a quality initiative discovery framework using process improvement techniques, software tools and operating principles. Process deviations are entered into a radiotherapy incident reporting database. Supervisors use an in-house Event Analysis System (EASy) to discuss incidents with staff. Major incidents are analyzed with an in-house Fault Tree Analysis (FTA). A meta-Analysis is performed using association, text mining, key word clustering, and differential frequency analysis. A key operating principle encourages the creation of forcing functions via rapid application development. 504 events have been logged this past year. The results for the key word analysis indicate that the root cause for the top ranked key words was miscommunication. This was also the root cause found from association analysis, where 24% of the time that an event involved a physician it also involved a nurse. Differential frequency analysis revealed that sharp peaks at week 27 were followed by 3 major incidents, two of which were dose related. The peak was largely due to the front desk which caused distractions in other areas. The analysis led to many PI projects but there is still a major systematic issue with the use of forms. The solution we identified is to implement Smart Forms to perform error checking and interlocking. Our first initiative replaced our daily QA checklist with a form that uses custom validation routines, preventing therapists from proceeding with treatments until out of tolerance conditions are corrected. PITSTOP has increased the number of quality initiatives in our department, and we have discovered or confirmed common underlying causes of a variety of seemingly unrelated errors. It has motivated the replacement of all forms with smart forms.