Need Determination System Using Audio-Based Similarity Matching
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Solution Overview
Problem
Current methods for determining the needs of subjects with long-term conditions and their informal caregivers are cumbersome and inefficient, often failing to accurately assess both parties' requirements, leading to sub-optimal service combinations.
Innovation Solution
A need determination system that uses a user interface to input current subject and caregiver information, applies a combination similarity measure to stored data to identify similar patterns, and employs machine learning to refine needs, incorporating audio recordings and data sets to extract and confirm needs with low technical effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face-to-face interaction between health care provider, subject and ICGs is used to assess needs, then comprehensive needs identification can be achieved, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent creates virtual copies of the assessment process by using audio recordings of conversations between subjects and ICGs, along with audio recordings of health care provider assessments. These audio copies are then processed through automatic speech recognition and natural language processing to extract needs information, eliminating the need for direct face-to-face interaction while preserving the comprehensive assessment capability.
Solution Approach 2:
The patent replaces the mechanical system of face-to-face human interaction with an automated computer-based system that uses audio recording, speech recognition, and natural language processing technologies. This substitution maintains the ability to identify comprehensive needs while dramatically reducing the time required for assessment.
2Reliability
If comprehensive needs assessment of both subject and ICGs is performed, then complete service combination can be determined, but technical effort and complexity increase
Solution Approach 1:
The patent implements a universal assessment system that simultaneously evaluates needs of multiple stakeholders (subjects and ICGs) through a single integrated process. The system handles audio recording, speech recognition, natural language processing, and needs extraction for all parties involved in one unified operation, reducing the perceived complexity while maintaining comprehensive assessment capability.
Solution Approach 2:
The system enables self-service by allowing subjects and ICGs to provide their own assessment data through recorded conversations, reducing the burden on health care providers. The automatic processing of these recordings extracts needs information without requiring manual analysis, thereby maintaining reliability while reducing technical effort.
3Measurement precision
If traditional needs assessment methods are used, then thorough evaluation can be conducted, but care efficiency deteriorates
Solution Approach 1:
The patent performs preliminary actions by recording audio data and conducting speech recognition processing before the actual needs determination takes place. This preparation work is done in advance, allowing the system to quickly retrieve and analyze previously processed information, thereby maintaining thorough assessment while improving overall care efficiency.
Solution Approach 2:
The patent replaces manual needs assessment mechanics with automated computer-based processing of audio recordings. This substitution enables thorough evaluation of needs while dramatically improving care efficiency by eliminating time-consuming manual analysis and enabling parallel processing of multiple assessment cases.
Data Source
AI summary
The invention relates to a need determination system including a user interface for enabling a person to input a current combination of a current subject, at least one current informal caregiver (ICG) giving care to the current subject, and at least one relationship between the current subject and the at least one current ICG. A combination similarity measure is applied to the current combination and stored combinations, in order to determine a stored combination which is similar to the current combination, where a need of the current subject and/or a need of the at least one current ICG are determined based on one or more needs assigned to a stored subject and/or stored ICGs of the determined similar stored combination. This allows for a reliable and fast determination of needs of a subject and/or an ICG with relatively low technical efforts.