Mental Health Resource Allocation via Wellness Score Gradient Analysis
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Solution Overview
Problem
Traditional mental health treatment methods are time-consuming and slow to produce results, limiting the ability to optimize resource allocation and measure treatment efficacy effectively.
Innovation Solution
A computer-implemented method for allocating mental health treatment resources, which involves collecting and analyzing individual patient mental health assessment data to compute wellness scores, determine treatment efficacy progress, and adjust treatment regimens based on correlated fixed and variable factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional mental health treatment methods are used, then treatment can be provided to patients, but the process is time-consuming and slow to produce results
Solution Approach 1:
The system implements continuous feedback loops by repeatedly administering standardized mental health assessments to patients and automatically analyzing the results. This creates a closed-loop system where treatment efficacy is measured objectively through standardized tests, and results are fed back to clinicians to adjust treatment regimens, thereby accelerating the measurement of treatment efficacy and reducing the time to manifest results.
Solution Approach 2:
The patent replaces manual, subjective clinical assessments with automated computer-based standardized testing and algorithmic analysis. The system uses automated data collection, standardized test administration, and computational analysis to substitute the traditional manual evaluation process, significantly reducing the time required to measure and manifest treatment results.
2Adaptability or versatility
If traditional mental health treatment methods are used, then treatment can be provided to patients, but the ability to optimize resource allocation is limited
Solution Approach 1:
The system serves multiple functions within a single integrated platform: it administers standardized assessments, collects and stores patient data, analyzes treatment efficacy, generates reports, and provides resource allocation recommendations. This multi-functional system enables comprehensive resource allocation optimization without requiring separate complex systems for each function.
Solution Approach 2:
The system automatically performs data collection, analysis, and resource allocation recommendations without requiring manual intervention for each task. The automated generation of treatment efficacy reports and resource allocation suggestions enables the system to serve itself in optimizing resource distribution across patient populations.
3Measurement precision
If traditional mental health treatment methods are used, then treatment can be provided to patients, but the ability to measure treatment efficacy effectively is limited
Solution Approach 1:
The system segments the measurement of treatment efficacy into distinct standardized assessment components that evaluate specific mental health conditions independently. By dividing the overall assessment into condition-specific modules, the system achieves precise measurement of treatment efficacy for each condition while maintaining manageable system complexity through standardized, recognized assessment tools.
Data Source
AI summary
A computer implemented method for allocating resources in mental health treatment includes the steps of: retrieving individual patient's mental health assessment data mapped to assessed mental conditions; computing a wellness score of the mapped assessed mental conditions; determining an overall treatment efficacy progress with a statistically analyzed gradient of the wellness scores; aggregating over a pool of patients population with similar conditions, a distribution of the gradient of the computed wellness scores of an overall treatment efficacy progress; sampling over a defined range of the distribution of the gradient of the computed wellness scores to determine a correlation coefficient of fixed factors and variable factors; using correlated coefficient of fixed factors and variable factors to assess efficacy of mental health treatment regimens for adjusting available mental health treatment resources to determine a next mental health treatment regimen; and communicating the next mental health treatment regimen to a healthcare provider.