Ventilation Recommendation System Using Historic Patient Profiles
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Solution Overview
Problem
Clinicians face challenges in ensuring clinical competency for patients with various conditions due to the complexity of mechanical ventilators and the need for personalized ventilation strategies.
Innovation Solution
A computer-implemented method generates recommendations for ventilating a target subject by creating a target subject profile and identifying similar historic subject profiles based on etiological, configuration, and parameter information, using consistency and number of outcomes to inform recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If mechanical ventilators are made more sophisticated with multiple modes and settings, then ventilation capability and precision are improved, but device complexity and difficulty of operation increase
Solution Approach 1:
The patent introduces a clinical decision support system as an intermediary between the complex ventilator system and the clinician. This system includes a processor that receives patient data, compares it against a database of historic profiles, and generates recommended ventilation settings. This mediator handles the complexity of interpreting multiple ventilator modes and settings, presenting simplified recommendations to clinicians while maintaining access to sophisticated ventilation capabilities.
Solution Approach 2:
The system enables self-service through automated generation of ventilation recommendations. The processor automatically analyzes patient data, identifies matching historic profiles, and produces ventilation setting recommendations without requiring manual interpretation by clinicians. This automation handles the complex analysis of multiple ventilator parameters and disease states, freeing clinicians from navigating the complexity directly.
2Manufacturing precision
If mechanical ventilators are made more sophisticated with multiple modes and settings, then ventilation capability is improved, but ease of operation deteriorates
Solution Approach 1:
The clinical decision support system serves as an intermediary that translates complex ventilator capabilities into easy-to-follow recommendations. The processor automatically compares patient data against historic profiles and generates specific ventilation setting recommendations, eliminating the need for clinicians to manually navigate multiple ventilator modes and settings. This maintains sophisticated ventilation capability while dramatically improving ease of operation.
Solution Approach 2:
The system incorporates feedback by continuously monitoring patient response to ventilation settings and adjusting recommendations accordingly. The processor receives ongoing patient data, compares it against historic outcomes, and refines ventilation recommendations based on observed responses. This feedback loop simplifies operation by automatically adapting to patient needs rather than requiring manual adjustment of complex settings.
3Reliability
If clinicians rely on manual expertise and training, then clinical competency can be achieved, but time consumption and learning curve increase
Solution Approach 1:
The system performs preliminary action by pre-processing patient data and pre-comparing it against a comprehensive database of historic profiles during setup. The processor identifies matching profiles and generates initial ventilation recommendations before clinical decisions are finalized. This preliminary analysis reduces the time clinicians need to spend on training and decision-making, while maintaining reliable clinical competency through evidence-based recommendations.
Solution Approach 2:
The system uses copying by replicating successful ventilation strategies from historic profiles. Instead of requiring clinicians to develop expertise from scratch, the system copies proven ventilation settings and approaches from similar patient cases in the database. This allows rapid deployment of clinically competent strategies without extensive training, while maintaining reliability through validation against historic outcomes.
Data Source
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AI summary
A mechanism for generating one or more recommendations for using a ventilation system. A target subject profile is determined that characterizes a target subject and a ventilation system used for the target subject. Historic subject profiles that share a same etiology and ventilation characterization as the target subject profile are identified, where the identified subject profiles also share similar parameter information to the target subject profile. The treatment outcome consistency and/or number of identified historic subject profiles are used to produce the recommendation(s).