Biometric linkage of longitudinally collected electronic case report forms and confirmation of subject identity: an open framework for ODK and related tools

Frontiers in Digital Health

Digital Health

Chrissy h. Roberts¹  Sham Lal¹  Michael Marks²  Zain Chaudhry³  Marianne Shawe-Taylor³  Callum Stott⁴ 

[1] Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom;Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom;Hospital for Tropical Diseases, University College London Hospitals NHS Trust, London, United Kingdom;Division of Infection and Immunity, University College London, London, United Kingdom;Hospital for Tropical Diseases, University College London Hospitals NHS Trust, London, United Kingdom;OPC Industries Ltd, Edinburgh, United Kingdom;

关键词: fingerprints;    biometrics;    clinical trials;    patient identification;    electronic data collection;    KoBoToolbox;    ODK;    open source;   

DOI  :  10.3389/fdgth.2023.1072331

 received in 2022-10-17, accepted in 2023-07-25,  发布年份 2023

来源: Frontiers

【 摘 要 】

The availability of low-cost biometric hardware sensors and software makes it possible to rapidly, affordably and securely sample and store a unique and invariant biological signature (or biometric “template”) for the purposes of identification. This has applications in research and trials, particularly for purposes of consent, linkage of case reporting forms collected at different times, and in the confirmation of participant identity for purposes of safety monitoring and adherence to international data laws. More broadly, these methods are applicable to the needs of the billion people who live in resource-restricted settings without identification credentials. The use of mobile electronic data collection software has recently become commonplace in clinical trials, research and actions for public good. A raft of tools based on the open-source ODK project now provide diverse options for data management that work consistently in resource-restricted settings, but none have built-in functionality for capturing biometric templates. In this study, we report the development and validation of a novel open-source app and associated method for capturing and matching biometric fingerprint templates during data collection with the popular data platforms ODK, KoBoToolbox, SurveyCTO, Ona and CommCare. Using data from more than 1,000 fingers, we show that fingerprint templates can be used to link data records with high accuracy. The accuracy of this process increases through the linkage of multiple fingerprints to each data record. By focussing on publishing open-source code and documentation, and by using an affordable (<£50) and mass-produced model of fingerprint sensor, we are able to make this platform freely available to the large global user community that utilises ODK and related data collection systems.

【 授权许可】

Unknown   
© 2023 Roberts, Stott, Shawe-Taylor, Chaudhry, Lal and Marks.

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