Lesion Tracking System Missing Measurement Detection
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Solution Overview
Problem
Current lesion tracking systems are hindered by missing measurements, which diminish their utility due to the lack of practical data entry requirements and system integration issues across organizations, leading to incomplete longitudinal tracking computations.
Innovation Solution
A longitudinal tracking system that includes a lesion tracking unit and a display device, which constructs and displays characteristic information for tracked lesions and indicates missing measurements, using a method that parses radiology reports to find and update missing data, ensuring more complete information for healthcare practitioners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data entry requirements are enforced to ensure complete measurements, then measurement completeness is improved, but system complexity and multi-organizational support requirements increase
Solution Approach 1:
The system automatically retrieves measurements from radiology reports and populates the lesion tracking database without requiring manual data entry by healthcare practitioners. The automated data retrieval process includes parsing unstructured report text, extracting measurement values, and matching them to the appropriate patients and lesions, thereby eliminating the need for enforced data entry requirements while maintaining measurement completeness.
2Measurement precision
If manual data entry is required for complete longitudinal tracking, then tracking accuracy is improved, but time consumption and productivity decrease
Solution Approach 1:
The system replaces the manual mechanical process of data entry with an automated information processing system. The automated system retrieves radiology reports, parses unstructured text to extract measurement data, validates the extracted information, and populates the lesion tracking database automatically. This substitution eliminates manual data entry while maintaining tracking accuracy through automated validation and error checking processes.
3Extent of automation
If ETL programs are used for data loading, then data processing automation is improved, but data quality and professional review decrease
Solution Approach 1:
The system incorporates a validation process that reviews extracted measurement data before inserting it into the lesion tracking database. The validation process checks for data quality issues, ensures measurements are properly matched to patients and lesions, and provides opportunities for correction or verification. This feedback mechanism maintains data quality while preserving the automation benefits of the ETL process.
Data Source
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AI summary
A longitudinal tracking system (10) includes a lesion tracking unit (28) and a display device (24). In response to a received patient identifier, the lesion tracking unit (28) constructs (102) a display of characteristic information for at least one longitudinally tracked lesion retrieved according to the patient identifier, and an identifier of at least one missing measurement determined by comparing a temporal identifier of retrieved reports with the characteristic information, and each report includes a narrative with measurements of at least one reported lesion for the patient identifier. The display device (24) displays the constructed display of the characteristic information for each longitudinally tracked lesion, and the identifier of the at least one missing measurement.