Medical Event Tracking System for Interoperability
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Solution Overview
Problem
Current electronic health record (EHR) systems lack interoperability, leading to inefficiencies and inaccuracies in medical data sharing between healthcare providers, which can result in incomplete treatment plans and increased malpractice claims.
Innovation Solution
A medical event tracking system that assigns unique tracking numbers to medical events, enabling seamless communication and coordination between EHR systems, lab information systems, and radiology systems, ensuring that all stakeholders are informed of diagnosis, recommendations, and follow-up actions in a timely manner through a Quality Assurance Module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If EHR systems use different file formats and storage methods for each vendor, then each system can store patient data locally, but interoperability between systems is lost
Solution Approach 1:
The patent introduces a Quality Assurance Module as an intermediary system that interfaces between different EHR vendors and laboratory information systems. This module receives data from various EHR systems using their native formats, standardizes the data through a common interface layer, and forwards it to the laboratory system. The intermediary resolves the interoperability problem by allowing each vendor to maintain their own storage methods while ensuring consistent data exchange through the standardized module.
Solution Approach 2:
The patent changes the data representation parameters by converting different EHR vendor-specific formats into a unified standardized format within the Quality Assurance Module. This parameter transformation enables different systems to communicate effectively without requiring changes to their underlying storage architectures, thus improving interoperability while maintaining system complexity at acceptable levels.
2Loss of information
If medical data is stored in EHR systems with unique patient files, then patient records can be accessed individually, but tracking medical events and recommendations across different providers is difficult
Solution Approach 1:
The patent implements a feedback mechanism through the Quality Assurance Module that tracks the status of medical recommendations and referrals. The system receives data from EHR systems, processes it through the standardized interface, and provides feedback about the completion status of recommendations to both the laboratory system and the ordering physicians. This feedback loop ensures information completeness by tracking whether recommendations are fulfilled, while improving productivity by automating the tracking process.
Solution Approach 2:
The Quality Assurance Module serves multiple functions: it acts as a data standardization layer, a tracking system for medical events, a communication hub between EHR systems and laboratories, and a quality assurance mechanism. This multi-functionality consolidates what would otherwise require multiple separate systems into a single unified platform, improving data sharing efficiency while maintaining comprehensive information tracking.
3Reliability
If EHR systems focus on storing patient data, then patient records are maintained, but monitoring completion of treatment plans and recommendations is insufficient
Solution Approach 1:
The patent applies preliminary action by establishing the Quality Assurance Module before the complete treatment cycle is finished. The module proactively tracks recommendations and referrals from the outset, monitoring their completion status throughout the care process. This preliminary setup enables continuous quality assurance without requiring complex manual monitoring processes, as the automated system is already in place to detect and report on treatment plan completion.
4Reliability
If medical professionals manually track recommendations and referrals, then individual cases can be monitored, but time consumption and error rates increase
Solution Approach 1:
The Quality Assurance Module performs self-service by automatically tracking, processing, and monitoring medical events, recommendations, and referrals without requiring manual intervention from healthcare professionals. The system autonomously receives data from EHR systems, processes it through standardized interfaces, tracks completion status, and generates quality assurance reports. This automation dramatically reduces the time professionals would spend on manual tracking while improving accuracy by eliminating human error in the tracking process.
Data Source
AI summary
Medical event tracking and quality assurance systems and techniques described provide a quality assurance module that interfaces between patient information systems (e.g. Electronic Health Record systems) and lab information systems. The systems and techniques provide for tracking respective medical events such as a patient's pathology specimen etc., based on a unique medical event tracking number throughout the diagnosis and treatment associated with that specimen. The system and technique enable medical event based tracking in a manner that substantially improves medical care by facilitating “closing-the-loop” between the many medical service providers and the laboratories that may be involved in a particular diagnosis and treatment.