Decentralized Imaging Platform for Physician Selection and Cost Reduction
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Solution Overview
Problem
The diagnostics industry faces challenges including a critical shortage of specialists, rising interpretation costs, workflow inefficiencies, quality issues, and a lack of consolidated diagnostics data to advance AI analytics, necessitating a platform to improve patient care at lower costs with higher quality.
Innovation Solution
A decentralized platform utilizing blockchain technology and smart contracts to facilitate the selection and payment of qualified physicians for imaging study interpretations, allowing healthcare facilities to choose physicians based on criteria such as licensing, expertise, and availability, while enabling AI companies to access anonymized data for improved analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If more radiologists are hired to meet increased demand, then interpretation capacity increases, but costs rise and quality may deteriorate due to fatigue and burnout
Solution Approach 1:
The patent segments the radiologist workforce into multiple independent practitioners who can be dynamically assigned to different imaging studies based on their specialized credentials and availability. This segmentation allows the system to distribute workload across many providers rather than overworking fewer radiologists, thereby maintaining quality while increasing capacity.
Solution Approach 2:
The platform creates a universal marketplace that connects multiple types of healthcare providers (radiologists, cardiologists, other specialists) with diverse credentials to various imaging study types. This multi-functionality allows the system to match any provider with appropriate credentials to any study type, increasing overall interpretation capacity without compromising quality through specialized matching.
2Speed
If radiology companies provide substantial additional capacity to meet turn-around time requirements, then service level improves, but interpretation costs increase
Solution Approach 1:
The patent implements a dynamic assignment system where radiologist assignments and pricing are adjusted in real-time based on current workload, availability, and turn-around time requirements. This dynamic approach allows the system to optimize cost-efficiency while meeting service level agreements, rather than maintaining static overcapacity that drives up costs.
Solution Approach 2:
The platform enables parameter changes in provider compensation and assignment based on multiple factors including turn-around time requirements, study complexity, and provider credentials. By dynamically adjusting these parameters, the system can meet accelerated turn-around requirements without proportionally increasing costs, as providers are compensated based on actual service delivery rather than fixed capacity provisioning.
3Productivity
If strict turn-around time requirements are imposed, then patient care efficiency improves, but radiologist workload increases leading to fatigue and burnout
Solution Approach 1:
The patent segments imaging studies into smaller units that can be distributed across multiple radiologists simultaneously. Rather than requiring each radiologist to complete entire complex cases alone within strict deadlines, the system can divide workload into manageable segments assigned to different providers, reducing individual duration of action while maintaining overall productivity.
Solution Approach 2:
The platform enables multiple radiologists to review and interpret the same imaging study independently, creating parallel processing capability. This copying approach allows the system to meet strict turn-around requirements by having multiple providers work on the same case simultaneously, thereby reducing the time burden on any single radiologist while maintaining patient care efficiency.
4Measurement precision
If specialized radiologists are assigned to complex studies, then interpretation accuracy improves, but matching complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the system learns from successful matching patterns and provider performance data to automatically refine credential-study matching algorithms. This feedback loop reduces matching complexity over time as the system becomes more proficient at identifying optimal provider-study pairings based on accumulated experience and performance metrics.
Solution Approach 2:
Radiologists maintain updated profiles of their own credentials, specialties, and expertise areas, enabling them to self-identify suitable imaging studies for their skills. This self-service approach reduces the administrative complexity of matching by allowing providers to actively participate in the matching process rather than requiring complex centralized coordination.
Data Source
AI summary
A method for facilitating selection, by a healthcare facility, of a physician from a plurality of physicians to provide interpretation of an imaging study, is provided. The method includes receiving physician credentials from at least one physician, receiving, from the healthcare facility, an imaging study and a request for interpretation of the imaging study, the request including physician selection criteria, providing access to the imaging study and the request for interpretation to qualified physicians whose credentials match the physician selection criteria, receiving an interpretation of the imaging study from those qualified physicians that have accepted the request for interpretation, comparing the physician credentials to the physician selection criteria, and selecting an imaging study interpretation from the received imaging study interpretations based on the comparing of the physician credentials to the physician selection criteria.