Understanding Adoption of Electronic Medical Records: Application of Process Mining for Health Worker Behavior Analysis

• Main Authors: Villamor, Dennis Andrew R, Pulmano, Christian E, Estuar, Ma. Regina Justina E
• 格式: text
• 出版: Archīum Ateneo 2020
• 主題: Computer Sciences; Databases and Information Systems; Insurance
• 在線閱讀: https://archium.ateneo.edu/discs-faculty-pubs/305; https://dl.acm.org/doi/10.1145/3418094.3418109

In the Philippine Health Insurance Company (PHIC) Advisory 04-2016, Primary Care Providers were given until the end of the year to adopt any of the certified electronic medical record providers for submission of patient profiling and patient consultations. With much emphasis on how electronic medical records can pave the way for better health care, this study presents finding on one year usage of a certified electronic medical record in selected areas in the Philippines. The study uses a novel approach in understanding technology adoption through process mining - technique often used in Business Process Analysis (BPA). A total of 8.8 million system-generated usage logs including: Session ID, Timestamp, URL Visited, URL Source, User ID were extracted as part of the dataset. Pre-processing techniques were performed on the data set prior to process mining. In using process mining to understand user behavior based on system-generated usage logs, one must consider: how to identify a case (i.e. how to group activities together), and how to structure your data in a way that allows the inference of real world activities and processes. Using standard adoption models shows us that adoption of early implementation of EMRs remain at basic usage with only a few users fully embracing the technology. However, use of process mining in understanding user behavior depicts actual workflow and presents adoption at a more advanced level.