Enhancing Healthcare Delivery with IoT-Enabled Remote Patient Monitoring

Industry:
about paysafe

A pioneering healthcare provider dedicated to transforming patient care by integrating IoT technology into their services. Specializing in remote monitoring and personalized treatment plans, they aim to address the critical challenges of overcrowded hospitals, escalating care costs, and the necessity for individualized patient attention. With a strong commitment to leveraging technological advancements, this provider focuses on enhancing the quality of care through continuous health monitoring, aiming to significantly reduce hospital readmissions and enable proactive, preventive healthcare strategies.

Reviewed on
5/5
40
%

Reduction in Hospital Readmissions

24/7

Patient Health Monitoring

100
+

Improved Patient Engagement

6
+

Data-Driven Clinical Decisions

The Challenge

The healthcare industry is at a crucial juncture, facing challenges such as overcrowded hospitals, rising costs of care, and the need for personalized patient treatment. Our client, a forward-thinking healthcare provider, was particularly concerned about the high rate of hospital readmissions and the lack of continuous patient monitoring outside clinical settings.

Traditional healthcare models were failing to address these issues effectively, leading to suboptimal patient outcomes and increased healthcare costs. There was a pressing need for a paradigm shift towards more proactive and preventive care models that could leverage the latest in technology to monitor patient health in real-time, ensuring timely intervention and reducing the burden on healthcare facilities.

What did
Entiko do

Entiko embarked on a transformative project to deploy an IoT-enabled remote patient monitoring system that would revolutionize the way our client delivered care. We started by equipping patients with wearable devices capable of continuously monitoring vital signs such as heart rate, blood pressure, and glucose levels.

 

These devices transmitted data in real-time to a cloud-based platform, where advanced analytics and machine learning algorithms assessed patient health trends and flagged any anomalies. Our system enabled healthcare providers to monitor patients remotely, receiving instant alerts in case of potential health issues, thus allowing for immediate intervention. We also developed a patient portal, enhancing patient engagement by allowing individuals to track their health data and receive personalized health tips.

This comprehensive approach not only improved patient outcomes but also significantly reduced the need for hospital readmissions by enabling early detection and treatment of potential health issues.

 

The Results

The technology that we use to support Paysafe

Wearable IoT Devices
Cloud Computing
Machine Learning Algorithms
Python
Node.JS
Java
Objective-C
RxJava

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