A method and system for handling missing items in a geriatric assessment scale

By aligning multi-source data and classifying missing item types, a confidence level is generated, enabling adaptive scheduling of comprehensive assessments for the elderly. This solves the problems of multi-source data alignment and scale missing item handling, and improves the confidence and efficiency of the assessment.

CN122364680APending Publication Date: 2026-07-10SHANGHAI NINTH PEOPLES HOSPITAL SHANGHAI JIAO TONG UNIV SCHOOL OF MEDICINE
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Patent Information

Application Number
CN202610765718.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-29
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies often suffer from difficulties in aligning multi-source data, lack of grading mechanisms for handling missing scales, inability to quantify the uncertainty of assessment conclusions, and a lack of adaptive convergence capabilities in the assessment process. These issues result in insufficient data integrity and reliability, increasing the workload for clinicians.

Method used

By aligning multi-source data using a unified primary key, time window, and field mapping table, missing entries are identified and categorized into types that can be automatically completed, can be retained tolerably, require manual entry, and require re-evaluation. A credibility level is generated, and adaptive evaluation and scheduling are performed based on a key item priority strategy.

Benefits of technology

It improves the integrity and traceability of assessment data, quantifies the credibility of assessment results, facilitates the identification of reliability under different data integrity conditions, and reduces the number of times unnecessary assessment items are scheduled.

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Abstract

The application relates to the technical field of comprehensive evaluation of geriatrics, and discloses a scale missing item processing method and system for comprehensive evaluation of the elderly, which comprises the following steps: acquiring multi-source evaluation related data, aligning the multi-source evaluation related data to preset items of a comprehensive evaluation scale for the elderly, identifying missing items in the scale, dividing the missing items into multiple types, performing hierarchical completion according to the divided types, constructing a confidence level calculation model, and generating a confidence level of an evaluation conclusion; based on a preset key item set and an expansion condition, performing adaptive evaluation scheduling, preferentially completing key item evaluation, and only when the expansion condition is met, triggering non-key item evaluation or reevaluation suggestion; through the above method, automatic identification, hierarchical completion, confidence level labeling and adaptive scheduling of missing items in the comprehensive evaluation scale for the elderly are realized, the number of triggering times of unnecessary evaluation items is reduced, and the traceability of the missing processing result is improved.
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