Feasibility and acceptability of an iris biometric system for unique patient identification in routine HIV services in Kenya. (January 2020)

• Record Type: Journal Article
• Authors: Anne, Njoroge; Dunbar, Matthew D.; Abuna, Felix; Simpson, Peter; Macharia, Paul; Betz, Bourke; Cherutich, Peter; Bukusi, David; Carey, Farquhar
• Is Part Of: International journal of medical informatics. Volume 133(2020)
• Publication Date: 2020-01
• Subjects: Biometrics -- Patient identification -- HIV -- Implementation science -- Kenya -- Iris; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2019.104006
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: Biometric patient identification addresses patient misidentification inaccuracies. About 99% of participants accepted an iris scan, with 86% re-identified on a repeat visit. Iris biometric systems can be implemented within routine clinical care settings. Biometrics can be linked to electronic medical records for patient longitudinal follow-up. Abstract: Background: Use of routine HIV programme data for surveillance is often limited due to inaccuracies associated with patient misclassification which can be addressed by unique patient identification.We assessed the feasibility and acceptability of integrating an iris recognition biometric identification system into routine HIV care services at 4 sites in Kenya. Methods: Patients who had recently tested HIV-positive or were engaged in care were enrolled. Images of the iris were captured using a dual-iris camera connected to a laptop. A prototype iris biometric identification system networked across the sites, analysed the iris patterns; created a template from those patterns; and generated a 12-digit ID number based on the template. During subsequent visits, the patients' irises were re-scanned, and the pattern was matched to stored templates to retrieve the ID number. Results: Over 55 weeks 8, 614 (98%) of 8, 794 new patients were assigned a unique ID on their first visit. Among 6, 078 return visits, the system correctly re-identified patients' IDs 5, 234 times (86%). The false match rate (a new patient given the ID of another patient) was 0·5% while the generalized false reject rate (re-scans assigned a new ID) was 4·7%. Overall, 9 (0·1%) agreed to enrol but declined to have an iris scan. The most common reasons cited for declining an iris scan were concerns about privacy and confidentiality. Conclusion: Implementation of an iris recognition system in routine health information systems is feasible and highly acceptable as part of routine care in Kenya. Scale-up could improve unique patient identification and tracking, enhancing disease surveillance activities.