Real-Time Monitoring System to Manage Mental Healthcare Emergency Unit

Autor: Samy Housbane, Adil Khoubila, Khaoula Ajbal, Mohamed Agoub, Omar Battas, Mohamed Bennani Othmani
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Healthcare Informatics Research, Vol 26, Iss 4, Pp 344-350 (2020)
Druh dokumentu: article
ISSN: 2093-3681
2093-369X
DOI: 10.4258/hir.2020.26.4.344
Popis: Objectives Real-time relevant information helps guide the healthcare decision-making process in daily clinical practice as well as the management and optimization of healthcare processes. However, proprietary business intelligence suite solutions supporting the production of decision-making information requires investment that is out of reach of small and medium-sized healthcare facilities or those with limited resources, particularly in developing countries. This paper describes our experience in designing and implementing a real-time healthcare monitoring system solution to manage healthcare emergency units. Methods Through the use of free Business Intelligence tools and Python data science language we designed a real-time monitoring system, which was implemented to explore the Electronic Medical Records system of a university mental health emergency unit and render an electronic dashboard to support health professional daily practice. Results Three main dashboards were created to monitor patient waiting time, to access the clinical notes summary for the next waiting patient, and to obtain insights into activity during the last 24 hours. Conclusions The designed system could serve as a monitoring support model using free and user-friendly data science tools, which are good alternatives to proprietary business intelligence solutions and drastically reduce cost. Still, the key to success in decision-making systems is based on investment in human resources, business intelligence skills training, the organizational aspect of the decision-making process, and data production quality insurance.
Databáze: Directory of Open Access Journals