Automated IOL Selection with Biometry–EMR Data Matching
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Solution Overview
Problem
Cataract surgery planning is complex due to numerous options and complications, requiring significant surgeon input and access to various intraocular lens (IOL) calculators, which can be limited by their availability and the need for manual data entry, especially in optimizing refractive outcomes and managing premium lenses.
Innovation Solution
A web-based surgical planning system that electronically interfaces with diagnostic data stores and electronic medical records to generate personalized surgery plans by weighing diagnostic and patient data, recommending IOL types and post-operative refractive targets with minimal doctor input, and providing alerts for data inconsistencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple IOL calculators and diagnostic data sources are integrated to improve surgical planning accuracy, then the precision of surgical outcomes is improved, but the complexity of the system increases
Solution Approach 1:
The patent combines multiple IOL calculators (Barrett Universal II, Holladay 2, Haigis, Hoffer Q, SRK/T) and various diagnostic data sources (biometry measurements, patient history, ocular surface analysis) into a single integrated web-based surgical planning system. This merging allows the system to process diverse data types through multiple calculation algorithms simultaneously, improving surgical planning accuracy while presenting a unified interface to the user.
Solution Approach 2:
The surgical planning system is designed as a universal platform that can handle multiple IOL types (monofocal, multifocal, EDOF, toric), accommodate various diagnostic data formats from different sources, and provide comprehensive surgical planning functions including IOL selection, power calculation, and outcome prediction. This multi-functionality allows a single system to replace multiple specialized tools.
2Productivity
If automated algorithms are used to reduce manual surgeon input, then productivity is improved, but the ease of operation may worsen due to the complexity of automated decision-making
Solution Approach 1:
The system automatically retrieves diagnostic data from connected devices and electronic medical records without requiring manual data entry by the surgeon. The automated algorithms process the retrieved data, perform IOL power calculations using multiple formulas, and generate surgical plans independently, significantly reducing the time and effort required for surgical planning while maintaining ease of use through automatic data population.
Solution Approach 2:
The system provides automated feedback to the surgeon by presenting calculated IOL power recommendations, confidence levels, and alternative options based on the processed diagnostic data. This feedback mechanism allows the automated system to communicate its decisions clearly, maintaining ease of operation by presenting results in an interpretable format that guides the surgeon's final decision-making.
3Reliability
If comprehensive diagnostic data is collected from multiple sources, then the reliability of surgical planning is improved, but the loss of time for data collection increases
Solution Approach 1:
The system performs preliminary automated retrieval and organization of diagnostic data from connected devices and electronic medical records before the surgical planning process begins. By automatically collecting and pre-processing data in advance, the system eliminates the time-consuming manual data gathering process while ensuring all necessary information is available for reliable surgical planning.
Solution Approach 2:
The web-based surgical planning system acts as an intermediary that automatically interfaces with diagnostic devices and electronic medical record systems to collect and integrate data from multiple sources. This intermediary function streamlines data collection by handling the communication and data aggregation processes automatically, reducing the time burden on the surgeon while comprehensively gathering necessary diagnostic information.
Data Source
AI summary
A surgery planning system obtains data from a doctor's questionnaire, patients questionnaire, EMR, and biometry unit. The data is weight-mapped to a plurality of electives in a plurality of options (categories). A surgery plan is generated based on the weights of the patients answers, EMR data, and biometry unit data.