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Comparison of a palm-based biometric solution with a name-based identification system in rural Bangladesh

BACKGROUND: Unique identifiers are not universal in low- and middle-income countries. Biometric solutions have the potential to augment existing name-based searches used for identification in these settings. This paper describes a comparison of the searching accuracy of a palm-based biometric soluti...

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Detalles Bibliográficos
Autores principales: Khatun, Fatema, Distler, Rebecca, Rahman, Monjur, O’Donnell, Brian, Gachuhi, Noni, Alwani, Manoj, Wang, Yang, Rahman, Anisur, Frøen, J Frederik, Friberg, Ingrid K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8967207/
https://www.ncbi.nlm.nih.gov/pubmed/35343885
http://dx.doi.org/10.1080/16549716.2022.2045769
Descripción
Sumario:BACKGROUND: Unique identifiers are not universal in low- and middle-income countries. Biometric solutions have the potential to augment existing name-based searches used for identification in these settings. This paper describes a comparison of the searching accuracy of a palm-based biometric solution with a name-based database. OBJECTIVE: To compare the identification of individuals between a palm-based biometric solution to a name-based District Health Information Software 2 (DHIS2) Android application, in a low-resource setting. METHODS: The study was conducted in Chandpur district, Bangladesh. Trained data collectors enrolled 150 women of reproductive age into two android applications – i) a name-based DHIS2 application, and ii) a palm-based biometric solution – both run on tablets. One week after enrollment, a different research team member attempted to re-identify each enrolled woman using both systems. A single image or text-based name was used for searching at the time of re-identification. We interviewed data collectors at the end of the study. RESULTS: Significantly more women were successfully identified on the first attempt with a palm-based biometric application (84%) compared with the name-based DHIS2 application (61%). The proportion of identifications that required three or more attempts was similar between name-based (7%, CI 3.7–12.3) and palm-based biometric system (5%, CI: 1.9–9.4). However, the total number of attempts needed was significantly lower with the palm-based solution (mean 1.2 vs. 1.5, p < 0.001). In a group discussion, data collectors reported that the palm-based biometric identification system was both accurate and easy to use. CONCLUSION: A palm-based biometric identification system on mobile devices was found to be an easy-to-use and accurate technology for the unique identification of individuals compared to an existing name-based application. Our findings imply that palm-based biometrics on mobile devices may be the next step in establishing unique identifiers in remote and rural settings where they are currently absent.