Performance of an Open Source Facial Recognition System for Unique Patient Matching in a Resource-Limited Setting

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dc.contributor.authorKitayimbwa, John M.
dc.contributor.authorWere, Martin C.
dc.contributor.authorAmpamyaa, Sight
dc.date.accessioned2021-12-22T08:48:32Z
dc.date.available2021-12-22T08:48:32Z
dc.date.issued2020
dc.descriptionThis is a research article assesses the lack of unique patient identifiers is a challenge to patient care in developing countries.en_US
dc.description.abstractBackground: The lack of unique patient identifiers is a challenge to patient care in developing countries. Probabilistic and deterministic matching approaches remain sub-optimal. However, affordable and scalable biometric solutions have not been rigorously evaluated in these settings. Methods: We implemented and evaluated performance of an open-source facial recognition system, OpenFace, integrated within a nationally-endorsed electronic health record system in Western Kenya. Patients were first enrolled via facial images, and later matched via the system. Accuracy of facial recognition was evaluated using Sensitivity; False Acceptance Rate (FAR); False Rejection Rate (FRR); Failure to Capture Rate (FTC) and Failure to Enroll Rate (FTE). 103 patients (mean age 37.8, 49.5% female) were enrolled. Results: The system had a sensitivity of 99.0%, FAR<1%, FRR 0.00, FTC 0.00 and FTE 0.00. Wearing spectacles did not affect performance. Conclusion: An open source facial recognition system correctly and accurately identified almost all patients during the first match.en_US
dc.identifier.citationKitayimbwa. John M. 2020 Performance of an open source facial recognition system for unique patient matching in a resource-limited setting. International Journal of Medical Informatics Vol. 141 Elsevier https://doi.org/10.1016/j.ijmedinf.2020.104180en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11951/945
dc.language.isoenen_US
dc.publisherInternational Journal of Medical Informaticsen_US
dc.subjectBiometricsen_US
dc.subjectPatient matchingen_US
dc.subjectUnique patient identifieren_US
dc.subjectFacial identificationen_US
dc.titlePerformance of an Open Source Facial Recognition System for Unique Patient Matching in a Resource-Limited Settingen_US
dc.typeArticleen_US
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