Surgical Tray Rationalization via Usage Data Analysis

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Solution Overview

Problem

Current systems for managing surgical instrument trays lack comprehensive data collection and rationalization using empiric usage data, leading to suboptimal time and expense in managing surgical trays and inventory.

Innovation Solution

A computer-implemented method for collecting and rationalizing instrument trays within a healthcare environment, utilizing data on equipment and disposable supplies to determine optimal tray configurations based on usage frequency, with a consolidation engine reducing the number of trays and inventory levels through machine learning and data analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If comprehensive data collection and tray rationalization utilizing empiric usage data are implemented, then inventory levels and operational expenses are reduced, but system complexity and implementation cost increase

Engineering Contradiction:

Improveinventory levelsVSAvoidsystem complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The system performs self-service by automatically collecting usage data from surgical procedures and using machine learning algorithms to autonomously determine optimized tray configurations. The consolidation engine continuously learns from empirical data and automatically updates tray rationalization recommendations without requiring manual intervention, thereby reducing inventory levels while managing system complexity through automation.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical processes of tray assembly and inventory management with automated computational systems. Machine learning algorithms substitute for human analysts in processing usage data and determining optimized tray configurations, reducing the need for manual data collection and analysis while achieving comprehensive tray rationalization.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Quantity of substance

If the number of instruments and trays is reduced, then operative expenses and inventory levels decrease, but the risk of instrument unavailability increases

Engineering Contradiction:

Improvenumber of instrumentsVSAvoidinstrument availability

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system implements continuous feedback loops by collecting actual usage data from surgical procedures and comparing it against predicted usage patterns. The consolidation engine uses this feedback to continuously refine and update tray configurations, ensuring that reduced instrument inventories are optimized based on real-world performance data. This feedback mechanism maintains instrument availability by adapting tray compositions to actual surgical needs while minimizing excess inventory.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent applies dynamics by making tray configurations adaptable and changeable based on evolving usage patterns. Rather than using static tray compositions, the system continuously updates tray rationalization recommendations based on accumulated empirical data, allowing the instrument inventory to dynamically respond to changing surgical practices and preferences, thereby maintaining reliability while reducing overall inventory levels.

Inventive Principle:

Principle #15Dynamics

3Device complexity

If manual data collection and tray rationalization are performed, then implementation cost is lower, but time consumption and labor requirements increase

Engineering Contradiction:

Improveimplementation costVSAvoidtime consumption

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

The system ensures continuity of useful action by automatically and continuously collecting usage data from surgical procedures without interruption. The machine learning algorithms continuously process this data and update tray rationalization recommendations in real-time, eliminating the need for periodic manual data collection cycles. This continuous automated operation reduces time consumption and labor requirements while the incremental cost of the automated system is offset by the significant time savings and improved decision-making accuracy.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS20240105322A1Software application to standardize access to surgical procedure inventory benchmarks and data collection and implementation of surgical procedure benchmarks for tray rationalization and supply optimization

Publication Date: 2024.03.28 WOOD BENJAMIN CHADWICK

AI summary

The subject matter disclosed herein includes a computerized method that supports the process of data collection for analysis and rationalization of instrument trays within a healthcare environment. The method, performed using a processor, includes for receiving instrument usage information related to instrument trays for use in the healthcare environment. Information related to preference card instrumentation, equipment, and disposable articles is stored within a database. A tray configuration is provided for a determined procedure. Instrument usage information is received, where the instrument suage information is related to instrument trays after use in the healthcare environment. It is determined, based on the received instrument usage after use in the healthcare environment, whether articles placed within an instrument tray are being used at a frequency below a predetermined threshold. Preference card information and tray configuration are updated for the determined procedure based on the determination.