Patient State Objects for Centralized Health Data Management
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Solution Overview
Problem
The existing healthcare system faces challenges in consolidating and making accessible dispersed health data from multiple sources, leading to fragmented and often inaccessible information for patients and healthcare providers, which hinders effective care and research utilization.
Innovation Solution
A system comprising patient state objects that store and manage demographic, behavioral, and physiological data, with a state controller engine for updating and an action controller engine for determining actions based on this data, facilitating holistic patient views and actionable insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If health data is collected from multiple diverse sources (physicians, health maintenance technology, different health care institutions), then the quantity and comprehensiveness of health information increases, but the data becomes dispersed and inaccessible to physicians responsible for patient care
Solution Approach 1:
The patent merges dispersed health data from multiple sources (physicians, health maintenance technology, different health care institutions) into a unified centralized system. The system consolidates demographic data, physiological data, behavioral data, and health care event data into single accessible patient records that can be retrieved by any authorized physician, thereby maintaining data quantity while improving accessibility.
Solution Approach 2:
The patent introduces a centralized health information system as an intermediary between diverse data sources and physicians. This intermediary system collects, standardizes, stores, and manages health data from multiple sources, then provides unified access to authorized users through standardized interfaces, resolving the accessibility problem without losing data quantity.
2Adaptability or versatility
If health data is stored in diverse formats across different systems, then the system can accommodate various data sources, but the data cannot be readily accessed or processed by physicians
Solution Approach 1:
The patent segments health data into standardized categories (demographic data, physiological data, behavioral data, health care event data) with defined schemas for each type. This segmentation allows the system to accommodate diverse data sources by mapping them to standard categories while enabling easy access and processing through consistent data structures and retrieval mechanisms.
Solution Approach 2:
The patent transforms diverse health data from different sources into a standardized format by changing parameters such as data structure, organization, and representation. The system applies standardized schemas to demographic, physiological, and behavioral data, converting heterogeneous formats into homogeneous, easily accessible structures that maintain adaptability to various sources while improving ease of operation.
3Adaptability or versatility
If physicians treat patients episodically with different specialists for different conditions, then each specialist can provide focused care, but no single physician has access to the patient's complete health history
Solution Approach 1:
The patent creates a universal health information system that serves multiple specialists and physicians simultaneously. The centralized system stores complete patient health histories accessible to all authorized providers, enabling each specialist to access comprehensive information while maintaining their focused expertise, thus achieving both specialization and information completeness.
4Quantity of substance
If health data is dispersed among diverse systems and institutions, then data can be collected from multiple sources, but it cannot be easily assembled or processed for research purposes
Solution Approach 1:
The patent merges dispersed health data into a centralized system with standardized structures, enabling efficient assembly and processing for research. The unified system consolidates data from multiple sources while maintaining organized, queryable formats that significantly improve research productivity compared to manual assembly from scattered sources.
Data Source
AI summary
Using a centralized system, it is possible to allow multiple disparate health care providers to gain a complete view of data regarding a patient's health and health care. Data accessible through such a central system can also be made available for researchers after being de-identified. Data in such a central system can not only include data culled from traditional physical and electronic medical records, but can also include data from distributed diagnostic devices, such as fitness trackers and consumer diagnostic equipment. Such a central system could potentially be accessed through applications made available to patients and health care providers and, in implementations where they are present, such applications could also be used for other purposes, such as performing interactive health evaluations and making recommendations of actions to take to maintain or restore a user's health.