The use of electronic medical records (EMRs) plays a crucial role in the successful implementation of the Universal Healthcare Law which promises quality and affordable healthcare to all Filipinos. Consequently, the current adoption of EMRs should be studied from the perspective of the healthcare provider. As most studies look into use of EMRs by doctors or patients, there are very few that extend studies to look at possible interaction of doctor and patient in the same EMR environment. Understanding this interaction paves the way for possible incentives that will increase the use and adoption of the EMR. This study uses process mining to understand simulated doctor-patient interaction, with the goal of developing interaction features and a token economy framework to increase EMR adoption. Results from the process mining showed that current EMR interaction remains low, and highlighted the need for interaction features to promote preventive healthcare. Moreover, process mining from the simulated logs showed that consistency and time are important factors in encouraging usage. Activity category, relative frequency of activity, relative case frequency of activity and average time spent on activity are features that may serve as the foundation for a token economy framework for EMRs.
Co, N. A. S., Limcaco, J. C., Tan, H. C. L., Estuar, M. R. J. E., Pulmano, C., Villamor, D., Sugon, Q., Bautista, M. C. G., & Claro, P. J. A. (2022). Clinical interactions in electronic medical records towards the development of a token-economy model. Procedia Computer Science, 196, 461–468. https://doi.org/10.1016/j.procs.2021.12.037