Automated Patient Query Selection for Reduced Consultation Time
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Solution Overview
Problem
Patients often face long waiting periods to consult healthcare professionals, and remote consultations through computing devices can be inefficient due to the need for manual information gathering, which consumes time and resources.
Innovation Solution
A computer-implemented method for automated patient interaction, involving parsing patient complaints, determining a subset of patient queries based on the complaint and patient data, communicating these queries to a computing device, receiving responses, generating output data, and training machine-learning algorithms to improve query selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual information gathering is used in remote consultations, then healthcare professionals can interact with patients, but the time spent by healthcare professionals increases
Solution Approach 1:
The system enables patients to provide information about their health status automatically through a computing device without requiring manual intervention from healthcare professionals. The automated system collects, processes, and analyzes patient data, allowing patients to serve themselves in the information gathering process, thereby reducing the time healthcare professionals need to spend on manual information collection.
Solution Approach 2:
The patent replaces the manual mechanical process of healthcare professionals asking questions and taking notes with an automated electronic system. The system uses computing devices, data processing algorithms, and communication protocols to automatically gather, transmit, and analyze patient information, substituting the mechanical manual interaction with an automated digital process that reduces time consumption.
2Loss of information
If multiple queries are posed to the patient to gather comprehensive information, then the information being gathered is more complete, but the number of queries increases and patient engagement decreases
Solution Approach 1:
The system employs feedback mechanisms where the automated system analyzes patient responses in real-time and dynamically adjusts subsequent queries. Based on the information provided by the patient, the system determines which queries are most relevant and prioritizes them, avoiding redundant questions and focusing on information that will most effectively complete the health assessment, thereby maintaining completeness while improving efficiency.
Solution Approach 2:
Instead of systematically asking all possible queries, the automated system uses algorithms to identify and select only the necessary subset of queries required to achieve adequate information gathering. The system applies partial action by targeting only the most relevant questions based on preliminary data analysis, avoiding excessive queries that would reduce patient engagement while still obtaining sufficient information for effective care.
3Loss of time
If automated systems are used to gather patient information, then the time spent by healthcare professionals is reduced, but the complexity of the system increases
Solution Approach 1:
The automated system is divided into distinct functional modules including a computing device for data collection, a communication module for transmitting data, and a processing module for analyzing information. This segmentation allows each component to perform its specific function independently, making the overall complex system more manageable and easier to implement. The system divides the information gathering process into discrete steps handled by different components, reducing the perceived complexity while maintaining automation benefits.
4Loss of energy
If computing resources are used efficiently in patient interactions, then the cost of service is reduced, but the automation level must be optimized
Solution Approach 1:
The system dynamically adjusts the level of automation based on the specific patient interaction requirements and available computing resources. The automated information gathering process can be configured to operate at different levels of automation, allowing the system to optimize between resource consumption and automation extent. The system can adapt its automated query generation and data processing intensity according to the complexity of the patient presentation and the computational capacity available, achieving efficient resource utilization while maintaining appropriate automation levels.
Data Source
AI summary
Provided is a system and method for automated patient interaction. The method includes parsing a patient complaint comprising a plurality of words, determining a subset of patient queries from a plurality of patient queries based on the patient complaint and patient data, communicating the subset of patient queries to a first computing device; receiving, from the first computing device, responses to at least a portion of the subset of patient queries; generating output data based on the subset of patient queries and the responses; communicating the output data to a second computing device; receiving, from the second computing device, a user input corresponding to at least one patient query of the subset of patient queries; and training, based on the user input, at least one machine-learning algorithm configured to output at least one patient query based on at least one of the patient complaint and a subsequent patient complaint.