Research Article
A Smart Pain Management System Using Big Data Computing
@INPROCEEDINGS{10.1007/978-3-319-94180-6_23, author={Waleed Al Shehri and Rashid Mehmood and Hassan Alayyaf}, title={A Smart Pain Management System Using Big Data Computing}, proceedings={Smart Societies, Infrastructure, Technologies and Applications. First International Conference, SCITA 2017, Jeddah, Saudi Arabia, November 27--29, 2017, Proceedings}, proceedings_a={SCITA}, year={2018}, month={7}, keywords={Big data computing Apache spark HealthCare Pain management Numeric Pain Rating Scale (NPRS) Electronic Health Records (EHRs) Patients’ data}, doi={10.1007/978-3-319-94180-6_23} }- Waleed Al Shehri
Rashid Mehmood
Hassan Alayyaf
Year: 2018
A Smart Pain Management System Using Big Data Computing
SCITA
Springer
DOI: 10.1007/978-3-319-94180-6_23
Abstract
Pain is a universal experience and there is hardly a human being who has never experienced pain at one time or another. Managing pain is of high priority for healthcare organizations given the increasing incidence of pain among patients and the costs associated with it. The current standards and practices in pain management are limited to mostly manual processes hindering innovations in this area. This paper proposes a smart pain management system based on big data computing technologies. The system devises pain management strategies based on the relevant standards and patients’ data, and these strategies are identified, applied, and monitored by the system in real-time. A perpetual feedback loop is created among the system components and the outcomes are communicated to the stakeholders to enable reflections and continuous improvements in the pain management standards, strategies, and processes. The system architecture and its architectural components are described. A preliminary analysis is provided using handwritten and digital pain management related data.
