Assessment of drone transport for biological samples: a real-world experience at a tertiary hospital
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Paula Calomarde-Pastor
Abstract
Objectives
Our aim is to determine whether drone transport introduces relevant variability in analytical results and to assess its suitability for integration into routine hospital laboratory operations.
Methods
A two-phase study was conducted. The stability phase involved three sets of samples from 31 healthy volunteers transported by drone, by road, and processed without transport. The pilot phase included paired samples from 104 primary care patients transported by drone and by road. A broad panel of 53 biochemical, hematological and urinary analytes was assessed. Analytical performance was evaluated using mean bias, comparison with reference change values (RCVs) and hemolysis grading.
Results
Most analytes showed minimal differences between transport methods. In the stability study, glucose and MCH in road-transported samples, and lactate dehydrogenase (LDH) and mean corpuscular hemoglobin (MCH) in drone-transported samples, exceeded their respective RCVs, with LDH likely affected by mild hemolysis. In the pilot study, statistically significant differences were observed between transport methods for potassium, exhibiting a bias of −1.7 % (−2.6 to −0.8 %). Hemolysis was slightly more frequent in drone samples during the stability study but comparable in the pilot study.
Conclusions
Drone transport preserved the analytical integrity of a comprehensive test panel and has the potential to reduce logistical constraints. These findings support its implementation as a reliable and sustainable alternative to conventional transport in clinical laboratory settings.
Acknowledgments
We would like to thank all the staff from CAP Sant Fost de Campsentelles, Pol Ayats and Daniel Castillo from BCN Drone Center, Francesc Pla from T-Systems Iberia, Lluís Sancliment from CTTI, Pau Gallinat from TIC Salut Social, Rafael Cáliz from Medical Emergency System of Catalonia, and M. Antonia Llopis and Norma Henríquez from ICS, for technical and organizational support.
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Research ethics: Research Ethics Committee approved the study (PI-24-233, 3 October 2024). This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Author contributions: P C-P and A P-A contributed equally to this work and share first authorship. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: AI was used to improve language.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/cclm-2025-1205).
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