Automated Process for Monitoring of Amiodarone Treatment: Development and Evaluation
Journal article, 2025
Background: Amiodarone treatment requires repeated laboratory evaluations of thyroid and liver function due to potential side effects. Robotic process automation uses software robots to automate repetitive and routine tasks, and their use may be extended to clinical settings. Objective: Thus, this study aimed to develop a robot using a diagnostic classification algorithm to automate repetitive laboratory evaluations for amiodarone follow-up. Methods: We designed a robot and clinical decision support system based on expert clinical advice and current best practices in thyroid and liver disease management. The robot provided recommendations on the time interval to follow-up laboratory testing and management suggestions, while the final decision rested with a physician, acting as a human-in-the-loop. The performance of the robot was compared to the existing real-world manual follow-up routine for amiodarone treatment. Results: Following iterative technical improvements, a robot prototype was validated against physician orders (n=390 paired orders). The robot recommended a mean follow-up time interval of 4.5 (SD 2.4) months compared to the 3.1 (SD 1.4) months ordered by physicians (P<.001). For normal laboratory values, the robot recommended a 6-month follow-up in 281 (72.1%) of cases, whereas physicians did so in only 38 (9.7%) of cases, favoring a 3- to 4-month follow-up (n=227, 58.2%). All patients diagnosed with new side effects (n=12) were correctly detected by the robot, whereas only 8 were by the physician. Conclusions: An automated process, using a software robot and a diagnostic classification algorithm, is a technically and medically reliable alternative for amiodarone follow-up. It may reduce manual labor, decrease the frequency of laboratory testing, and improve the detection of side effects, thereby reducing costs and enhancing patient value.
ventricular tachycardia
ventricular fibrillation
decision support
anti-arrhythmic medication
clinical decision support system
amiodarone treatment
robotics
side effects
thyroid function
heart
monitoring
follow-up studies
anti-arrhythmic
automated process
automation
algorithm
disease management
thyroid gland
robot
cardiac dysrhythmias
thyroid
liver
arrhythmia
evaluation
development
atrial fibrillation
Author
Birgitta Johansson
University of Gothenburg
Sahlgrenska University Hospital
Jonas Landahl
Sahlgrenska University Hospital
Karin Tammelin
University of Gothenburg
Sahlgrenska University Hospital
Erik Aerts
Chalmers, Computer Science and Engineering (Chalmers), Functional Programming
Christina E. Lundberg
University of Gothenburg
Martin Adiels
University of Gothenburg
Martin Lindgren
Sahlgrenska University Hospital
University of Gothenburg
Annika Rosengren
Sahlgrenska University Hospital
University of Gothenburg
Nikolaos Papachrysos
University of Gothenburg
Sahlgrenska University Hospital
Helena Filipsson Nyström
University of Gothenburg
Sahlgrenska University Hospital
Helen Sjöland
University of Gothenburg
Sahlgrenska University Hospital
Journal of Medical Internet Research
14388871 (eISSN)
Vol. 27 e65473Subject Categories (SSIF 2025)
Robotics and automation
DOI
10.2196/65473