Regional Resource Availability Scoring With Quantile G-Computation
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Solution Overview
Problem
Existing scoring methodologies fail to account for all social factors affecting health outcomes in communities, domain-level effects, and varying levels of factor impacts, hindering tailored resource distribution for improved health outcomes.
Innovation Solution
A computer-implemented method and system for determining a social health score by receiving and processing geographically-dependent data, applying feature-level and domain-level quantile g-computation to assign weights, and calculating region scores to assess resource access and impediments, using databases and modules for preprocessing, weighting, and scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing scoring methodologies are used to assess community health, then the scoring process is simple, but the scoring accuracy is insufficient because it does not account for all social factors, domain-level effects, and varying levels of factor impacts
Solution Approach 1:
The scoring methodology is segmented into multiple domains (e.g., education, economy, environment, health) with each domain containing specific social factors. This hierarchical segmentation allows comprehensive coverage of all social factors while organizing the complex assessment into manageable components, thereby improving scoring accuracy without overwhelming complexity
Solution Approach 2:
The patent applies domain-level weighting where different domains are assigned different weights based on their specific impact on health outcomes. This allows each domain to be evaluated with appropriate importance, capturing the varying levels of factor impacts across different social determinants, thus enhancing measurement precision
2Measurement precision
If comprehensive social factor data is collected for all communities, then the resource distribution accuracy is improved, but the data processing time and computational resources increase
Solution Approach 1:
The patent pre-calculates and stores domain weights and factor weights based on comprehensive social factor data before actual resource distribution assessments. This preliminary action allows the system to use pre-computed weights for subsequent assessments, maintaining high accuracy while significantly reducing processing time when evaluating resource access for specific communities
Solution Approach 2:
The system computes comprehensive weights for all domains and factors in advance (excessive action), but only applies the necessary subset of these pre-computed weights for each specific community assessment (partial action). This approach ensures accuracy is maintained while avoiding redundant computations for each individual assessment
Data Source
AI summary
A method for determining a social health score for a region includes (i) receiving first data for a geographical area including values for a plurality of features corresponding to a plurality of domains; (ii) for a first domain of the plurality of domains, selecting a first set of features that correspond to the first domain, and determining first feature weights for the first set of features based on a quantile g-computation of the values of the first data for the first set of features; (iii) receiving second data for the region including values for a subset of the plurality of features and the first domain, (iv) determining a first region domain score based on the second data and the first feature weights; and (v) determining a total score for the region based on the first region domain score indicating a level of resource access for a population of the region.