Hospital Resource Availability Dashboards for Surge Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Healthcare facilities face challenges in efficiently managing resource availability during unexpected surges in patient admissions, leading to potential shortages due to the lack of centralized systems for tracking critical resources like ventilators, which results in suboptimal decision-making based on incomplete or outdated information.
Innovation Solution
A collaborative resource utilization system that aggregates real-time or near real-time data from multiple medical facilities, generating graphical user interfaces to visualize critical resource availability and infectious disease information across various geographical scopes, enabling informed resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hospitals maintain sufficient resources for expected patient peaks, then patient care quality is maintained, but resource utilization efficiency deteriorates due to resources being stretched thin or unavailable during unexpected surges
Solution Approach 1:
The patent merges resource tracking across multiple hospitals into a single centralized system. The resource management system aggregates data from multiple hospital facilities, allowing resources to be allocated across the entire network rather than being siloed at individual facilities. This enables efficient redistribution of resources during surges while maintaining care quality.
Solution Approach 2:
The system creates a universal resource pool that serves multiple hospitals and multiple types of resources (ventilators, beds, staff). The centralized platform provides multi-functional capabilities including real-time monitoring, predictive analytics, and automated allocation across diverse resource types and facilities.
2Device complexity
If hospitals track resources locally without centralized systems, then data privacy and system simplicity are maintained, but information completeness deteriorates leading to suboptimal decision-making
Solution Approach 1:
The patent introduces a centralized resource management system as an intermediary between individual hospitals. This intermediary aggregates data from multiple sources, processes it through predictive analytics, and provides allocation recommendations. The intermediary layer maintains system simplicity by handling the complexity of data integration and analytics centrally while keeping individual hospital systems relatively simple.
Solution Approach 2:
The system implements continuous feedback loops where real-time resource data from multiple hospitals is fed into predictive analytics models, which generate allocation recommendations that are then implemented and monitored. The feedback mechanism ensures information completeness by continuously updating the system with actual resource status and allocation outcomes.
3Measurement precision
If real-time data aggregation from multiple facilities is implemented, then resource allocation accuracy is improved, but data processing complexity and infrastructure requirements increase
Solution Approach 1:
The patent applies preliminary action through predictive analytics that forecast future resource needs based on historical data and current trends. By performing predictions in advance, the system prepares allocation strategies before actual resource shortages occur, improving allocation accuracy without requiring complex real-time processing during critical moments.
Solution Approach 2:
The system changes parameters by transforming raw data from multiple facilities into standardized formats and aggregated metrics. The predictive analytics models transform historical data into future predictions, and the system transforms complex multi-source data into simple allocation recommendations that can be easily implemented.
Data Source
AI summary
Systems and methods are provided for collecting, aggregating, and visualizing resource availability information for one or more medical facilities. In one example, a method includes receiving first data from a first medical facility, the first data received via a first data streaming process and in a first format; receiving second data from a second medical facility, the second data received via a second data streaming process and in a second format; processing the first data and the second data to generate one or more resource availability graphical user interfaces (GUIs); and outputting the one or more resource availability GUIs for display on a display device.