Published
32nd European Conference on Operational Research (EURO 2022)
The intertwining of cost structure and prescription pattern: a case study of electronic medical records data mining
Abstract
The aim of this study is to use data mining techniques to identify prescribing patterns in health care plans, as well as to determine whether
variation in health insurance plans and benefits may affect health care
treatment. Electronic health records were collected from regional hospitals in Thailand with the prescribing guidelines of the National Public
Health Administration. Due to complexity of healthcare management
with wide range of drug options and treatment protocols, the costs
of treating patients in government-funded programs were significantly
higher than with patients in out-of-pocket programs. This study has
investigated the variation in benefit plans, which can make a difference
in treatment outcomes when multiple options are available. The impact
was significant on health service providers’ profit margins. The study
has showcased how big data and cloud technology can be integrated in practice, and how to support data migration from regional hospital
databases to the cloud. By utilizing database technology that can help
improve the performance of healthcare-related software, the process
can ensure the delivery of healthcare services. The findings suggested
that prescribing variability in diagnosed patients and chronic disease
symptoms by mapping prescribing patterns were related to choice of
brand preference for patients under universal coverage plans in which
their healthcare costs was dropped due to government subsidy regulations and constraints.
The intertwining of cost structure and prescription pattern: a case study of electronic medical records data mining. ฟินแลนด์, 32nd European Conference on Operational Research (EURO 2022) (1-1).