Community Health Scoring System Data Integration
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Solution Overview
Problem
Existing healthcare systems face challenges in accessing and analyzing diverse data sources to effectively measure healthcare resource distribution and improve healthcare delivery, leading to a scarcity of useful data representations for decision-making in communities.
Innovation Solution
A system and method for measuring community healthcare attributes by storing healthcare data in electronic storage systems, correlating health outcomes with population attributes, and displaying community health measures through interactive tools, enabling efficient data access and representation for resource allocation and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If extensive efforts are made to identify and access diverse data sources, then the completeness of healthcare data increases, but the time and resources required for data access increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-establishing a standardized data collection framework that identifies and integrates multiple data sources in advance. The system pre-processes and standardizes data from various healthcare sources before analysis is needed, eliminating the need for extensive data sourcing efforts during each research project. This framework is set up once and then reused across multiple studies, significantly reducing repeated data access time while maintaining data completeness.
2Measurement precision
If repeated efforts are made to access different data sources for refined research, then the precision of healthcare analysis improves, but the productivity of research decreases
Solution Approach 1:
The patent implements universality by creating a multi-functional data platform that serves multiple research purposes simultaneously. The standardized data collection framework and integrated data warehouse can support various types of healthcare analyses (epidemiological studies, outcomes research, resource allocation analysis) using the same pre-established data infrastructure. This eliminates the need for repeated data access efforts for different research projects, maintaining analytical precision while significantly improving research productivity.
3Adaptability or versatility
If diverse data sources are integrated into a unified framework, then the versatility of healthcare measurements increases, but the complexity of the system increases
Solution Approach 1:
The patent applies parameter changes by transforming diverse data from different sources into a standardized set of parameters and metrics. The system defines specific measurement parameters (e.g., healthcare utilization rates, outcome measures, resource allocation metrics) that all data sources must conform to. By changing the data representation parameters to a common standard during ingestion, the system achieves versatile measurement capabilities across multiple data sources while managing complexity through parameter standardization rather than complex integration logic.
Data Source
AI summary
A system and method for scoring and comparing communities includes the development of community health measures by on combining and supplementing healthcare data and community data from numerous sources. The community health measures may be stored in a community health measures database and may be accessed by interactive tools to generate customized representations of healthcare measures for selected communities. The representations are automatically computed in response to interactive user selections. Geographic map representation, heat map representations and data tables may be automatically generated to identify correlations between health outcomes and population attributes in different communities.