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Description
The BoxLens platform offers an integrated solution that combines hardware, software, analytics, and actionable insights to provide comprehensive visibility into essential supply chain metrics. Utilizing a blend of artificial intelligence and established business rules, it suggests various actions for users to take. The system automatically updates the next steps based on the actions executed, ensuring that all activities are documented for future analysis and enhancement of algorithms. Users can access a consolidated dashboard that highlights key performance indicators (KPIs) related to the supply chain. Additionally, it features real-time telemetry that syncs with the client's ERP data, along with alerts for any deviations or undesirable occurrences. Notifications can be sent through multiple channels, including dashboards, SMS, email, voice calls, or WhatsApp. The platform performs diagnostic evaluations of supply chain metrics in relation to relevant ERP data and operational conditions. Furthermore, it predicts possible supply chain disruptions in real-time, employing machine learning models that draw from historical data to forecast future trends. This capability allows for proactive planning at the source and timely interventions during operations. Moreover, it provides standardized templates that facilitate operations, quality assurance, and management reporting, thereby enhancing overall efficiency. In essence, BoxLens not only streamlines supply chain processes but also equips businesses with the tools needed to adapt and respond to dynamic market conditions.
Description
Evaluate reopening strategies to guarantee optimal staffing, PPE, and additional resources are in place. Forecast patient numbers for each hospital or unit within a flexible timeframe. Accurately monitor and predict bed availability. Anticipate emergency department and post-anesthesia care unit holds over varying timeframes. Capture real-time data to anticipate capacity for each unit and service. Reduce the number of canceled surgeries by providing early alerts about significant increases in patient census. Analyze and forecast off-service placements effectively. Predict and manage patient discharges efficiently. The fundamental type of analytics serves to distill extensive data into smaller, more practical insights. Descriptive analytics aims to provide an overview of past events, while diagnostic analytics delves deeper to uncover the reasons behind those events. Conventional management engineering methods are generally sufficient for performing this level of analysis; however, predictive analytics represents a more advanced approach that helps organizations to proactively address future challenges. This progression from descriptive to diagnostic, and finally to predictive analytics, enables healthcare facilities to enhance their operational efficiency and improve patient care outcomes.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Tagbox Solutions
Founded
2016
Country
Singapore
Website
www.tagbox.co/boxlenstm/
Vendor Details
Company Name
FutureFlowRx
Country
United States
Website
futureflowrx.com
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
Product Features
Patient Management
Admissions Management
Bed Management
Discharge Management
Historical Reporting
Patient Flow Management
Patient Location Tracking
Patient Monitoring
Real Time Reporting
Waiting Time Tracking
