Patient-Specific Orthopedic Implant Planning With Third-Party Data

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Solution Overview

Problem

Conventional technologies in orthopedics lack the capability to draw upon large data sets to generate and optimize patient-specific treatments and implant designs, as they do not actively collect and analyze third-party data relevant to the patient.

Innovation Solution

A system and method for designing patient-specific treatments and implants that includes automated protocols for collecting and analyzing third-party data, using machine learning and artificial intelligence to integrate this data into patient treatment plans and implant designs, and allowing user interaction for modification and approval.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional technologies are used for patient treatment planning, then the treatment process is simple and quick, but the data utilization is limited and treatment optimization is insufficient

Engineering Contradiction:

Improvetreatment outcome optimizationVSAvoiddata collection and analysis system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments data collection from multiple sources (electronic health records, imaging systems, wearables, third-party databases) and processes them through separate modules including data acquisition, cleaning, integration, and analysis components, allowing complex data handling to be divided into manageable functional units

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary data processing platform that acts as a mediator between various data sources and the treatment planning system. This platform includes data integration modules, cleaning algorithms, and integration with third-party databases, serving as an intermediate layer that transforms raw data into actionable insights without requiring direct complex connections between all system components

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of information

If patient data from limited sources is used, then the data collection process is simple, but the data correlation and relevance to particular patients is insufficient

Engineering Contradiction:

Improvepatient data completenessVSAvoidmulti-source data integration system

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system implements a universal data integration platform capable of handling multiple data types and sources through common processing mechanisms. The data cleaning module, integration algorithms, and analysis components serve multiple functions across different data sources including electronic health records, imaging systems, wearables, and third-party databases, reducing overall system complexity despite handling diverse inputs

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system incorporates feedback mechanisms where treatment outcomes and patient responses are continuously monitored and fed back into the data repository. This feedback loop allows the system to learn from actual treatment results and improve future treatment planning by adjusting data weighting and correlation algorithms based on proven effective patterns

Inventive Principle:

Principle #23Feedback

3Productivity

If historical outcome data is not actively analyzed, then the treatment planning process is straightforward, but the ability to generate optimized patient-specific treatments is limited

Engineering Contradiction:

Improvetreatment plan generation efficiencyVSAvoiddata analysis and processing platform

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by pre-processing and storing historical outcome data in structured formats before treatment planning is needed. Data cleaning, normalization, and initial analysis are conducted in advance, creating ready-to-use datasets that can be quickly queried and applied during treatment planning without requiring intensive real-time processing

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces manual mechanical analysis methods with automated computational algorithms for data processing and treatment optimization. Machine learning models and automated analysis algorithms substitute for traditional manual review of historical data, enabling rapid processing of large datasets and generation of optimized treatment recommendations without proportional increases in human labor

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12622786B2Patient-specific implant design, manufacture and platform with clinical and third-party data acquisition

Publication Date: 2026.05.12 CARLSMED INC

AI summary

Systems and methods for designing patient-specific orthopedic implants. The systems and methods can include automated collection protocols for available third-party data to use to generate surgical plans or patient-specific orthopedic implant designs. The system can identify triggers for collecting third-party data. The system can determine a confidence score for the collected third-party data based on the type of data, the source of the data, and the similarity of the data to patient data. The system can select parameters in the third-party data to integrate into designing a patient-specific implant or patient treatment.