Development and Implementation of an AI System for Generating Clinical Urine Drug Test Sign-Outs - Report - MDSpire

Development and Implementation of an AI System for Generating Clinical Urine Drug Test Sign-Outs

  • By

  • Nathan Laha

  • Michael Keebaugh

  • Hsuan-Chieh Liao

  • Bright Amankwaa

  • Olumuyiwa Adesoye

  • Abed Pablo

  • William S. Phipps

  • Andrew N. Hoofnagle

  • Geoffrey S. Baird

  • Patrick C. Mathias

  • Brody H. Foy

  • June 23, 2026

  • 0 min

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Clinical Report: Creation and Deployment of an AI Tool for UDTs

Overview

This study investigates the development and validation of an AI tool designed to enhance the interpretation of urine drug tests (UDTs) by generating preliminary textual interpretations.

Background

Urine drug tests are essential in various clinical settings, particularly for monitoring patients with substance use disorders. Accurate interpretation of UDT results can be complex, often requiring expert consultation, which can be time-consuming and costly. The integration of AI tools into clinical workflows has the potential to streamline this process and improve efficiency.

Data Highlights

No numerical data or trial data was provided in the source material.

Key Findings

  • The study followed the TRIPOD+AI reporting guideline for transparency.
  • Clinical data labeling and evaluation were conducted by trained members of the clinical chemistry team.
  • The AI interpretation tool is intended for use by trained clinical chemistry clinicians only.

Clinical Implications

The AI tool is intended to assist clinical chemistry clinicians in interpreting UDT results.

Conclusion

The study demonstrates a practical framework for integrating AI into clinical workflows for urine drug testing, enhancing both accuracy and efficiency.

Related Resources & Content

  1. ADLM Guidance Document on Laboratory Testing for Drugs of Misuse to Support the Emergency Department - PubMed
  2. LCD - Urine Drug Testing (L36029)
  3. AI Drafts Cut Radiograph Reporting Time
  4. Creation of Image-Centric Decision Support Systems Leveraging Data from Radiological Free-Text Report Databases Using Text-Based Transformers
  5. Assessing the Effectiveness of Artificial Intelligence in Urology: An In-Depth Examination of Kidney Stone-Related Inquiries
  6. Determining the detection of 216 fentanyl analogs and synthetic opioids and predicting epitopes using four commercial immunoassays
  7. npj Digital Medicine — Improving Ophthalmic Ultrasound Analysis through Grounded Report Generation with Vision-Language Segmentation Models
  8. ADLM Guidance Document on Laboratory Testing for Drugs of Misuse to Support the Emergency Department - PubMed
  9. LCD - Urine Drug Testing (L36029)
  10. Determining the detection of 216 fentanyl analogs and synthetic opioids and predicting epitopes using four commercial immunoassays - ScienceDirect

Original Source(s)

Development and Implementation of an AI System for Generating Clinical Urine Drug Test Sign-Outs

  • by Nathan Laha, Michael Keebaugh, Hsuan-Chieh Liao, Bright Amankwaa, Olumuyiwa Adesoye, Abed Pablo, William S. Phipps, Andrew N. Hoofnagle, Geoffrey S. Baird, Patrick C. Mathias, Brody H. Foy

  • June 23, 2026

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