Care Matching Algorithm for Provider Recipient Compatibility
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Solution Overview
Problem
Current in-home care systems lack efficient provider matching and scheduling, leading to inadequate care delivery and stress for family members, as they often rely on low-tech manual processes that fail to ensure compatibility between care providers and recipients, compromising the quality of care and recipient safety.
Innovation Solution
A system that utilizes a database of historical provider and recipient information, along with feedback analysis, to generate a compatible provider profile for each recipient, optimizing matching based on skills, personality, and location, while also providing AI-driven normalization of feedback to ensure effective care delivery and scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual scheduling and matching processes are used, then device complexity is reduced, but productivity and care quality deteriorate
Solution Approach 1:
The patent replaces manual mechanical scheduling processes with an automated computer-based system that uses algorithms to match caregivers with recipients and optimize routing. The system substitutes human manual effort with automated computational processes, significantly improving scheduling efficiency while managing complexity through software architecture.
Solution Approach 2:
The system enables automated self-matching between caregivers and recipients based on compatibility algorithms, eliminating the need for manual intervention in the matching process. The system serves itself by automatically optimizing schedules and routes without requiring external coordination, thereby improving productivity.
2Reliability
If automated matching systems are implemented, then care quality improves, but loss of information increases due to data processing requirements
Solution Approach 1:
The system incorporates feedback mechanisms where caregivers and recipients provide ratings and comments about their interactions. This feedback is processed by the algorithm to continuously improve matching accuracy, ensuring that care quality improves while minimizing information loss through iterative learning from actual care experiences.
Solution Approach 2:
The system performs preliminary background checks, credential verification, and compatibility assessments before making caregiver-recipient matches. By conducting these information-gathering actions in advance, the system ensures reliable matching decisions are made with complete information available, reducing data processing losses during the actual matching process.
3Measurement precision
If comprehensive provider profiling is conducted, then matching precision improves, but device complexity increases
Solution Approach 1:
The provider profiling system is segmented into distinct modules: background check module, credential verification module, compatibility assessment module, and rating analysis module. Each module handles a specific aspect of profiling independently, improving matching precision through comprehensive data collection while managing complexity through modular architecture that allows independent development and maintenance of each profiling component.
Data Source
AI summary
The present invention relates to systems and methods for ensuring quality of care services by matching a care recipient to a provider. The system accesses a database of historical provider and recipient information, as well as feedback from the providers and recipients to correlate the ratings to features in the profiles of the providers and recipients. This can be used to generate an in-demand profile for the provider specific to any given recipient profile. Thus, when a new recipient is being on-boarded, this recipient's profile is queried to determine what an in-demand provider profile would look like for the given recipient. The available recipients are filtered by physical distance from the recipient as well as by qualifications. Then the difference between the available providers and the in-demand profile is computed. Distances less than a dynamic threshold are considered candidates for providing care to the recipient. A care provider is then selected.