Abstract: We developed a semi-automated interpretation tool using the Python programming language for interpreting Serum Protein Electrophoresis (SPEP) laboratory data and generating a text report. Our app uses SPEP data and patient history to automatically draft an interpretation comment that is ultimately edited by a Clinical Pathologist for the clinical report. The tool improves efficiency and accuracy in the interpretation step of the SPEP reporting clinical workflow. The tool code is available on GitHub for adaptation for local use.

Describe the new knowledge and additional skills the participant will gain after attending your presentation.: By attending this presentation the attendees might discover the potential of implementing informatics methods for manual workflows in their current practice. There is also a potential to adapt and implement the app for local use.

Authors:

Ghazaleh Eskandari (Presenter)
Houston Methodist Hospital

Paul Christensen, Houston Methodist Hospital
S. Long, Houston Methodist Hospital