Cloud Network for Personalized Medicine Data Exchange
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Solution Overview
Problem
Early diagnosis of Alzheimer's disease is often delayed due to inconsistent and non-standardized examination methods, and the lack of easy data sharing between primary care physicians and specialists, leading to unnecessary tests and increased costs.
Innovation Solution
A cloud-based social network architecture for personalized medicine that enables secure, HIPAA-compliant exchange of health information, allowing primary care physicians to refer patients to specialists and utilize a data analytics unit for optimized diagnostics and treatment planning, improving diagnostic certainty and reducing unnecessary exams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If primary care physicians perform examinations independently without standardized data sharing, then each physician can conduct their own assessment, but diagnostic delays occur and unnecessary tests increase costs
Solution Approach 1:
The patent merges examination data from multiple physicians into a single standardized digital record that can be accessed by all involved providers. This consolidation eliminates redundant testing and accelerates diagnosis by ensuring all physicians work from the same comprehensive information base, directly addressing both the time loss from delays and information loss from poor data sharing.
Solution Approach 2:
The examination record is designed with universal accessibility, allowing any authorized physician in the network to access and contribute to the same standardized record regardless of their specialization or location. This multi-functional approach enables seamless collaboration between primary care physicians and specialists, reducing both diagnostic delays and unnecessary重复 testing.
2Reliability
If multiple examinations are performed without standardized data access, then comprehensive diagnostic information can be gathered, but data quality issues and lack of standardization reduce effectiveness
Solution Approach 1:
The patent transforms examination data from varied, non-standardized formats into a unified standardized digital format with consistent parameters and structures. This parameter standardization ensures that data from different sources and providers maintains uniform quality and reliability, enabling accurate aggregation of comprehensive diagnostic information without sacrificing data precision.
3Speed
If specialists are consulted later in the process, then primary care physicians can perform initial screening, but early diagnosis is delayed by several years
Solution Approach 1:
The patent introduces a standardized digital examination record as an intermediary that seamlessly connects primary care physicians and specialists. This intermediary enables real-time data exchange and collaboration without requiring complex manual referral processes, significantly accelerating the speed of diagnosis while keeping the system architecture manageable through standardization.
4Measurement precision
If costly PET scans are ordered early without step-wise diagnostic staging, then early disease detection might be achieved, but costs increase unnecessarily
Solution Approach 1:
The patent enables preliminary standardized examinations and data aggregation before advancing to more costly diagnostic procedures. By establishing a structured step-wise diagnostic process where standardized data from initial screenings informs subsequent testing decisions, the system achieves high diagnostic accuracy while avoiding unnecessary expensive tests, thereby controlling medical costs effectively.
Data Source
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AI summary
According to an aspect of an embodiment, a method of delivering information- enabled personalized healthcare in a clinical, non-research setting may include capturing one or more data streams where each of the data streams relates to health care of a patient. The method may further include integrating the data streams to generate integrated diagnostic data and analyzing the integrated diagnostic data to generate analyzed diagnostic data. The method may further include curating the analyzed diagnostic data and generating an integrated report for presentation to a physician of the patient based on the curated analyzed diagnostic data.