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Emirates Health Services has a mission to improve the management of outpatient meetings, and partly does so by developing advanced artificial intelligence algorithms to ensure real -time analysis through its “solution to insights”.
The development of this software was stimulated by the need to meet several challenges in managing an outpatient meeting, which included prolonged patient waiting times, high shortcomings, resource allocation and lack of improved patient’s flow.
Dr. Sara Alshaya, Director of Data Department and Statistics at EHS, will talk about the development of software during the “Foottep Insights: A Healthcare Analytics Solution in order to optimize outpatient care” on Tuesday, 4 March, at 13:45, in Venetian, level 5, level 5, Palazzo about, at the global Himss25 conference in Las Vegas.
ALSHAYA quantitative analysis of data showing extended waiting periods of both nurses and doctors, especially during rush hour. This, she said, leads to a reduction in patients’ performance and dissatisfaction, and the feedback was emphasized by the frustrations of both patients and healthcare professionals on unskilled planning and overpopulation.
At this point there are insights of the trace, designed to apply AI analysis and traces in real time to optimize resource allocation, reduce waiting time and improve patient experiences.
“This initiative was aimed at increasing the improvement of operational efficiency by making decisions based on data, ultimately contributing to better patients’ results and general healthcare provision,” said Alshaya.
The initiative was developed after a structured process, starting with the assessment and planning with an precise assessment of existing outpatient management processes. Interested parties, including health care staff and scientists from data, identified key pain points, such as long waiting time, apply of resources and unskilled patient flow.
Combat targets and results of KPI were defined, data pipelines between EHR and the analytical platform were established, and the data was cleaned for storage in EHS data. Pilot models have helped improve the project.
Alshaya said that AI played a key role: “Especially in order to capture and analyze the step data in real time, enabling healthcare facilities to obtain insight into patients’ movement, visit of the visit and bottlenecks.
“The models also provide for the volume of patients during peak hours, enabling proactive allocation of resources to minimize problems with overcrowding and understatement,” she said.
Step observations caused significant improvements of operational performance and reduction of waiting times, which in turn led to physical benefits, including cost savings, increased efficiency and better patient satisfaction, said Alshaya.
“The use of advanced analytical positions of the project is a potential role model in the field of technology-based health care improvements,” she said. “In addition, the possibility of adapting the system offers the paths of integration of future AI models and more sophisticated predictive tools, which makes it an evolved frame capable of supporting long -term strategic goals of healthcare.”
Alshaya said that she hopes that participants will better understand how data -based solutions can transform outpatient care by using advanced analyzes and artificial intelligence.
“At the end of the session, they should feel inspired and prepared to support and use innovative technologies to constantly improve the provision of healthcare services,” she said.
He is the editor of Newscare Finance News.
E -Mail: jlagasse@himss.org
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