AI-Augmented Kidney Stone Composition Analysis with Auto-Release Improves Quality, Efficiency, Cost-Effectiveness, and Staff Satisfaction

AI-Augmented Kidney Stone Composition Analysis with Auto-Release Improves Quality, Efficiency, Cost-Effectiveness, and Staff Satisfaction

We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented kidney stone composition test system for potential improvements in test quality, efficiency, cost-effectiveness, and staff satisfaction. We compared quality, effici...

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Veröffentlicht in:The journal of applied laboratory medicine 2024-12
Hauptverfasser: Day, Patrick L, Rokke, Denise, Schneider, Laura, Abbott, Jillian, Holmen, Brenda, Johnson, Patrick, Wieczorek, Mikolaj A, Kunze, Katie L, Carter, Rickey E, Bornhorst, Joshua, Jannetto, Paul J
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container_title The journal of applied laboratory medicine
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creator Day, Patrick L
Rokke, Denise
Schneider, Laura
Abbott, Jillian
Holmen, Brenda
Johnson, Patrick
Wieczorek, Mikolaj A
Kunze, Katie L
Carter, Rickey E
Bornhorst, Joshua
Jannetto, Paul J
description We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented kidney stone composition test system for potential improvements in test quality, efficiency, cost-effectiveness, and staff satisfaction. We compared quality, efficiency, staff satisfaction, and financial data from the 6 months after the AI-augmented laboratory test system was deployed (test period) with data from the same 6-month period in the previous year (control period) to determine if AI-augmentation improved key performance indicators of this laboratory test. In the 6 months following the deployment (test period) of the AI-augmented kidney stone composition test system, 44 830 kidney stones were analyzed. Of these, 92% of kidney stones were eligible for AI-assisted interpretation. Out of these AI-eligible stones, 45% were able to be auto-released by the AI-augmented test system without human secondary review. Furthermore, the new AI-augmented kidney stone test system resulted in an apparent 40% reduction in incorrect laboratory results. Additionally, the new AI-augmented test system improved laboratory efficiency by 20%, improved staff satisfaction, and reduced the average analysis cost per kidney stone by $0.23. The AI-augmented test system improved test quality, efficiency, cost-effectiveness and staff satisfaction related to this kidney stone composition test.
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We compared quality, efficiency, staff satisfaction, and financial data from the 6 months after the AI-augmented laboratory test system was deployed (test period) with data from the same 6-month period in the previous year (control period) to determine if AI-augmentation improved key performance indicators of this laboratory test. In the 6 months following the deployment (test period) of the AI-augmented kidney stone composition test system, 44 830 kidney stones were analyzed. Of these, 92% of kidney stones were eligible for AI-assisted interpretation. Out of these AI-eligible stones, 45% were able to be auto-released by the AI-augmented test system without human secondary review. Furthermore, the new AI-augmented kidney stone test system resulted in an apparent 40% reduction in incorrect laboratory results. Additionally, the new AI-augmented test system improved laboratory efficiency by 20%, improved staff satisfaction, and reduced the average analysis cost per kidney stone by $0.23. 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source Oxford University Press Journals All Titles (1996-Current)
title AI-Augmented Kidney Stone Composition Analysis with Auto-Release Improves Quality, Efficiency, Cost-Effectiveness, and Staff Satisfaction
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