First experiences in the implementation of biometric technology to link data from Health and Demographic Surveillance Systems with health facility data

BACKGROUND: In developing countries, Health and Demographic Surveillance Systems (HDSSs) provide a framework for tracking demographic and health dynamics over time in a defined geographical area. Many HDSSs co-exist with facility-based data sources in the form of Health Management Information Systems (HMIS). Integrating both data sources through reliable record linkage could provide both numerator and denominator populations to estimate disease prevalence and incidence rates in the population and enable determination of accurate health service coverage. OBJECTIVE: To measure the acceptability and performance of fingerprint biometrics to identify individuals in demographic surveillance populations and those attending health care facilities serving the surveillance populations. METHODOLOGY: Two HDSS sites used fingerprint biometrics for patient and/or surveillance population participant identification. The proportion of individuals for whom a fingerprint could be successfully enrolled were characterised in terms of age and sex. RESULTS: Adult (18-65 years) fingerprint enrolment rates varied between 94.1% (95% CI 93.6-94.5) for facility-based fingerprint data collection at the Africa Centre site to 96.7% (95% CI 95.9-97.6) for population-based fingerprint data collection at the Agincourt site. Fingerprint enrolment rates in children under 1 year old (Africa Centre site) were only 55.1% (95% CI 52.7-57.4). By age 5, child fingerprint enrolment rates were comparable to those of adults. CONCLUSION: This work demonstrates the feasibility of fingerprint-based individual identification for population-based research in developing countries. Record linkage between demographic surveillance population databases and health care facility data based on biometric identification systems would allow for a more comprehensive evaluation of population health, including the ability to study health service utilisation from a population perspective, rather than the more restrictive health service perspective

Using a fingerprint recognition system in a vaccine trial to avoid misclassification.

PROBLEM: The potential for misidentification of trial participants, leading to misclassification, is a threat to the integrity of randomized controlled trials. The correct identification of study subjects in large trials over prolonged periods is of vital importance to those conducting clinical trials. Currently used means of identifying study participants, such as identity cards and records of name, address, name of household head and demographic characteristics, require large numbers of well-trained personnel, and still leave room for uncertainty. APPROACH: We used fingerprint recognition technology for the identification of trial participants. This technology is already widely used in security and commercial contexts but not so far in clinical trials. LOCAL SETTING: A phase 2 cholera vaccine trial in SonLa, Viet Nam. RELEVANT CHANGES: An optical sensor was used to scan fingerprints. The fingerprint template of each participant was used to verify his or her identity during each of eight follow-up visits. LESSONS LEARNED: A system consisting of a laptop computer and sensor is small in size, requires minimal training and on average six seconds for scanning and recognition. All participants' identities were verified in the trial. Fingerprint recognition should become the standard technology for identification of participants in field trials. Fears exist, however, regarding the potential for invasion of privacy. It will therefore be necessary to convince not only trial participants but also investigators that templates of fingerprints stored in databases are less likely to be subject to abuse than currently used information databases