Evidence map›Paper›PMID 34941557›Full record

ArticleJournal of medical Internet research2021

Implementation of Fingerprint Technology for Unique Patient Matching and Identification at an HIV Care and Treatment Facility in Western Kenya: Cross-sectional Study.

Noah Kasiiti Jaafa, Benard Mokaya, Simon Muhindi Savai, Ada Yeung, Abraham Mosigisi Siika, Martin Were

Abstract read
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Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Noah Kasiiti Jaafa *Institute of Biomedical Informatics, Moi University, Eldoret, Kenya.ORCID 0000-0001-8556-4523
Benard Mokaya *Institute of Biomedical Informatics, Moi University, Eldoret, Kenya.ORCID 0000-0002-7178-7109
Simon Muhindi Savai *Institute of Biomedical Informatics, Moi University, Eldoret, Kenya.ORCID 0000-0001-6353-0904
Ada YeungVanderbilt Institute for Global Health, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0002-2803-3061
Abraham Mosigisi SiikaDepartment of Medicine, School of Medicine, Moi University, Eldoret, Kenya.ORCID 0000-0001-7669-6612
Martin Were *Department of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0002-6182-093X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnique patient identification remains a challenge in many health care settings in low- and middle-income countries (LMICs). Without national-level unique identifiers for whole populations, countries rely on demographic-based approaches that have proven suboptimal. Affordable biometrics-based approaches, implemented with consideration of contextual ethical, legal, and social implications, have the potential to address this challenge and improve patient safety and reporting accuracy. However, limited studies exist to evaluate the actual performance of biometric approaches and perceptions of these systems in LMICs.

objectiveThe aim of this study is to evaluate the performance and acceptability of fingerprint technology for unique patient matching and identification in the LMIC setting of Kenya.

methodsIn this cross-sectional study conducted at an HIV care and treatment facility in Western Kenya, an open source fingerprint application was integrated within an implementation of the Open Medical Record System, an open source electronic medical record system (EMRS) that is nationally endorsed and deployed for HIV care in Kenya and in more than 40 other countries; hence, it has potential to translate the findings across multiple countries. Participants aged >18 years were conveniently sampled and enrolled into the study. Participants' left thumbprints were captured and later used to retrieve and match records. The technology's performance was evaluated using standard measures: sensitivity, false acceptance rate, false rejection rate, and failure to enroll rate. The Wald test was used to compare the accuracy of the technology with the probabilistic patient-matching technique of the EMRS. Time to retrieval and matching of records were compared using the independent samples 2-tailed t test. A survey was administered to evaluate patient acceptance and satisfaction with use of the technology.

resultsIn all, 300 participants were enrolled; their mean age was 36.3 (SD 12.2) years, and 58% (174/300) were women. The relevant values for the technology's performance were sensitivity 89.3%, false acceptance rate 0%, false rejection rate 11%, and failure to enroll rate 2.3%. The technology's mean record retrieval speed was 3.2 (SD 1.1) seconds versus 9.5 (SD 1.9) seconds with demographic-based record retrieval in the EMRS (P<.001). The survey results revealed that 96.3% (289/300) of the participants were comfortable with the technology and 90.3% (271/300) were willing to use it. Participants who had previously used fingerprint biometric systems for identification were estimated to have more than thrice increased odds of accepting the technology (odds ratio 3.57, 95% CI 1.0-11.92).

conclusionsFingerprint technology performed very well in identifying adult patients in an LMIC setting. Patients reported a high level of satisfaction and acceptance. Serious considerations need to be given to the use of fingerprint technology for patient identification in LMICs, but this has to be done with strong consideration of ethical, legal, and social implications as well as security issues.

Indexed as

HIV InfectionsTechnologyAdultCross-Sectional StudiesFemaleHumansKenyaSurveys and Questionnairesbiometricselectronic medical record systemsfingerprintslow- and middle-income countries (LMICs)patient matchingunique patient identification

Identifiers

PMID34941557
PMCPMC8734934

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.