Clinical Decision Platform for ED and ICU Patient Monitoring
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Solution Overview
Problem
Emergency departments (ED) and intensive care units (ICU) often face understaffing and inadequate electronic systems, leading to missed diagnoses of critical conditions such as acute lung injury and sepsis, due to insufficient resources and trained professionals.
Innovation Solution
A user engagement platform that utilizes processors and memory to evaluate patient data parameters, comparing them to thresholds to identify abnormalities, and generates alerts and diagnoses, integrating with electronic health records (EHR) systems to support clinical decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If hospitals reduce budgets for various departments, then operational costs are reduced, but the ability to hire adequate health care professionals deteriorates
Solution Approach 1:
The system enables self-service by automatically evaluating patient data parameters and generating diagnoses without requiring additional health care professionals. The processor compares data parameters to thresholds and identifies abnormalities autonomously, allowing the system to perform diagnostic functions that would otherwise require human expertise.
Solution Approach 2:
The patent replaces the mechanical system of human professional evaluation with an automated electronic system. The processor substitutes for health care professionals by evaluating patient data parameters, comparing them to thresholds, and generating diagnoses, thereby eliminating the need for additional human resources while maintaining diagnostic capability.
2Measurement precision
If health care professionals manually evaluate patient data, then diagnostic accuracy can be maintained, but time consumption and resource requirements increase
Solution Approach 1:
The patent replaces the mechanical system of manual professional evaluation with an automated electronic system. The processor rapidly evaluates patient data parameters by comparing them to pre-established thresholds, maintaining diagnostic accuracy while eliminating the time consumption associated with manual review by health care professionals.
Solution Approach 2:
The system enables continuous evaluation of patient data without interruption. The processor can simultaneously evaluate multiple data parameters and continuously monitor patient status, ensuring that diagnostic accuracy is maintained at all times without the breaks or delays inherent in manual evaluation processes.
3Reliability
If electronic health records systems are enhanced with advanced evaluation capabilities, then diagnostic capability is improved, but system complexity increases
Solution Approach 1:
The patent enhances diagnostic capability by changing the parameters evaluated by the system. The processor compares data parameters to pre-established thresholds, allowing the system to identify abnormalities and generate diagnoses. This parameter-based approach improves reliability while maintaining manageable system complexity through the use of clear, quantifiable criteria.
Solution Approach 2:
The system segments the diagnostic process into distinct functional components: data parameter evaluation, threshold comparison, abnormality identification, and diagnosis generation. This segmentation improves reliability by ensuring each function is performed correctly while keeping overall system complexity manageable through modular design.
Data Source
AI summary
Systems and methods are disclosed for providing a user engagement platform to support clinical decisions. The user engagement platform is a point of care decision support platform for inpatients in an emergency department (ED), an intensive care unit (ICU), or other medical care department or facility that services patients with critical care needs. The user engagement platform is configured to receive and process data parameters obtained from a patient electronic health record (EHR), identify abnormalities based on such data parameters, prompt a user (e.g., clinician or other healthcare professional such as a nurse) to consider conditions common in ICU or ED patients that could result in patient death and update the patient EHR based on such user input.