Clinical Interactions in Electronic Medical Records Towards the Development of a Token-Economy Model

• Main Authors: Co, Nicole Allison S, Limcaco, Jason, Tan, Hans Calvin L, Estuar, Ma. Regina Justina E, Pulmano, Christian E, Villamor, Dennis Andrew, Sugon, Quirino, Jr, Bautista, Maria Cristina G, Acacio-Claro, Paulyn Jean
• 格式: text
• 出版: Archīum Ateneo 2022
• 主題: Token Economy; Blockchain; Healthcare; Electronic Medical Records; Process Mining; Computer Sciences; Databases and Information Systems; Health and Medical Administration; Health Information Technology; Health Law and Policy
• 在線閱讀: https://archium.ateneo.edu/gsb-pubs/63; https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1060&context=gsb-pubs

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.