"Re-Materialized" Medical Data: Paper-Based Transmission of Structured Medical Data Using QR-Code, for Medical Imaging Reports. Lauriot Dit Prevost, A., Bentegeac, R., Dequesnes, A., Billiau, A., Baudelet, E., Legleye, R., Hubaut, M., Cassagnou, M., Puech, P., Besson, R., & Chazard, E. Studies in Health Technology and Informatics, 290:210–214, June, 2022. doi abstract bibtex Although paper-based transmission of medical information might seem outdated, it has proven efficient, and remains structurally safe from massive data leaks. As part of the ICIPEMIR project for improving medical imaging report, we explored the idea of structured data storage within a medical report, by embedding the data themselves in a QR-Code (and no URL-to-the-data). Three different datasets from ICIPEMIR were serialized, then encoded in a QR-Code. We compared 4 compression algorithms to reduce file size before QR-Encoding. YAML was the most concise format (character sparing), and allowed for embedding of a 2633-character serialized file within a QR-Code. The best compression rate was obtained with gzip, with a compression ratio of 2.32 in 15.7ms. Data were easily extracted and decompressed from a digital QR-Code using a simple command line. YAML file was also successfully recovered from the printed QR-Code with both Android and iOS smartphone. Minimal detected size was 3*3cm.
@article{lauriot_dit_prevost_re-materialized_2022,
title = {"{Re}-{Materialized}" {Medical} {Data}: {Paper}-{Based} {Transmission} of {Structured} {Medical} {Data} {Using} {QR}-{Code}, for {Medical} {Imaging} {Reports}},
volume = {290},
issn = {1879-8365},
shorttitle = {"{Re}-{Materialized}" {Medical} {Data}},
doi = {10.3233/SHTI220063},
abstract = {Although paper-based transmission of medical information might seem outdated, it has proven efficient, and remains structurally safe from massive data leaks. As part of the ICIPEMIR project for improving medical imaging report, we explored the idea of structured data storage within a medical report, by embedding the data themselves in a QR-Code (and no URL-to-the-data). Three different datasets from ICIPEMIR were serialized, then encoded in a QR-Code. We compared 4 compression algorithms to reduce file size before QR-Encoding. YAML was the most concise format (character sparing), and allowed for embedding of a 2633-character serialized file within a QR-Code. The best compression rate was obtained with gzip, with a compression ratio of 2.32 in 15.7ms. Data were easily extracted and decompressed from a digital QR-Code using a simple command line. YAML file was also successfully recovered from the printed QR-Code with both Android and iOS smartphone. Minimal detected size was 3*3cm.},
language = {eng},
journal = {Studies in Health Technology and Informatics},
author = {Lauriot Dit Prevost, Arthur and Bentegeac, Raphaël and Dequesnes, Audrey and Billiau, Adrien and Baudelet, Emmanuel and Legleye, Rémi and Hubaut, Marc-Antoine and Cassagnou, Michel and Puech, Philippe and Besson, Rémi and Chazard, Emmanuel},
month = jun,
year = {2022},
pmid = {35673002},
keywords = {Data Collection, Data Compression, Health Information Exchange},
pages = {210--214},
}
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