Interoperability Engine for Irregular EHR Workflow Mapping
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Solution Overview
Problem
Inconsistent and erratic clinical workflows across different electronic health record (EHR) systems lead to interoperability issues, increasing manual intervention, errors, and costs, and posing risks in medical procedures.
Innovation Solution
A processor-implemented method processes clinical workflows by mapping indeterminate data streams from disparate EHR systems to known workflows using clinical workflow management files, industry standards, and general parsing models, facilitating compliance assessments and data normalization for surgical platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different EHR systems implement different protocols and data exchange formats, then each system can be optimized for its specific clinical workflow, but interoperability between systems deteriorates
Solution Approach 1:
The patent introduces an intermediary translation layer that receives data from multiple EHR systems using their native protocols and formats, translates these diverse inputs into a standardized internal representation, and enables consistent processing. This mediator approach allows each EHR system to maintain its optimized workflow while achieving reliable interoperability through the translation layer that handles protocol conversion and data normalization.
2Productivity
If data exchange timing and formats vary between EHR systems, then each system can operate independently with its own clinical workflow, but consistency and error rates deteriorate
Solution Approach 1:
The system performs preliminary actions by implementing a standardized data reception and validation framework that prepares incoming data from various EHR systems before processing. The translation layer pre-norms data formats, validates required fields, and standardizes timing protocols in advance, ensuring data consistency is established before clinical workflows execute independently, thereby preventing errors rather than correcting them later.
3Measurement precision
If manual intervention is increased to handle interoperability issues, then data accuracy can be maintained, but efficiency and cost effectiveness deteriorate
Solution Approach 1:
The system implements self-service capabilities through automated translation and validation mechanisms that handle interoperability issues without human intervention. The translation layer automatically detects data format variations, applies appropriate conversion rules, validates data completeness, and corrects common formatting errors autonomously, maintaining data accuracy while eliminating the need for manual intervention and thereby preserving operational efficiency.
Data Source
AI summary
A healthcare system accommodates spasmodic clinical workflows for populating a records database associated with a surgical platform or other digital healthcare platform. An interoperability engine receives data streams including events from various electronic health records systems that provide data events according to varying format, order, and timing dependent on their corresponding clinical workflows. The interoperability engine maps indeterminate events to expected events associated with a clinical workflow based on a clinical workflow management file, an industry standard model, a general parsing model, or a combination thereof. The interoperability engine may furthermore detect non-compliance of received events and may generate feedback indicative of a compliance assessment.