Development of a Framework for a Blockchain-Enabled Token Economy Model in an Electronic Medical Record System: Quantifying User Engagement During Doctor-Patient Consultations
Date of Award
2020
Document Type
Dissertation
Degree Name
Master of Science in Chemistry
Department
Information Systems & Computer Science
First Advisor
Ma. Regina Justina E. Estuar, PhD
Abstract
Tangible incentives to increase social collaboration and improve tech- nology adoption are essential for the sustainability of an electronic health platform. This research paper studied the development of a framework for a blockchain-enabled token economy model for electronic medical record sys- tems. A token economy is used as an intervention method to increase the usage and adoption of an EMR by providing incentives for engagement with the system. A total of 8,891,495 EMR usage logs, from 2016 - 2017, were used as a dataset to generate an activity-network flow through process min- ing. The logs were processed to show an aggregate count of the frequency of each action performed, and a process map was formed. The incentives are in the form of a currency that is awarded to an agent after certain criteria are met with regards to their system usage. A token economy model using a systems modeling approach was developed to ensure the system network is sustainable such that the amount of transactions and circulating tokens on the network is maintained over time. A token economy model was devel- oped that, when used in a simulation with certain parameters and internal variables, shows that transactions occur over the entire time period repre- senting one year, and that the tokens available on the entire system does not get fully depleted. The model was validated through comparison with a baseline simulation, parameter variation, and extreme condition tests.
Recommended Citation
Villamor, Dennis Andrew, (2020). Development of a Framework for a Blockchain-Enabled Token Economy Model in an Electronic Medical Record System: Quantifying User Engagement During Doctor-Patient Consultations. Archīum.ATENEO.
https://archium.ateneo.edu/theses-dissertations/405