Healthc Inform Res.  2020 Oct;26(4):344-350. 10.4258/hir.2020.26.4.344.

Real-Time Monitoring System to Manage Mental Healthcare Emergency Unit

• Housbane S
• Khoubila A
• Ajbal K
• Agoub M
• Battas O
• Othmani MB

• KMID: 2508627
• DOI: http://doi.org/10.4258/hir.2020.26.4.344

Abstract

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 mediumsized 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.

Keyword

Health Information Systems, Data Science, Decision Support Systems, Clinical, Decision-Making, Computer-Assisted, Clinical Informatics

Figure

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  Figure 1 Emergency real-time monitoring system design. Health professionals are data producers and consumers, and IT users periodically manage data processes.

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  Figure 2 Pentaho Kettle Extract Transformation Load (ETL) tool to retrieve emergency EMR data and to store it in the data warehouse databases.

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  Figure 3 Jupyter Notebook to create and manage ER dashboard.

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  Figure 4 Emergency waiting time dashboard webpage rendered with Voila.

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  Figure 5 Ubuntu Cron job file configuration to run automatically implemented ETL transformation and note-books.

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  Figure 6 Emergency waiting room real-time dashboard.

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  Figure 7 Emergency next patient clinical notes summary dashboard.

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  Figure 8 Emergency last 24-hour waiting time dashboard.

Reference

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