Malaria Journal (Jun 2018)

The role of the Deki Reader™ in malaria diagnosis, treatment and reporting: findings from an Africare pilot project in Nigeria

  • Patrick Adah,
  • Omosivie Maduka,
  • Obinna Obasi,
  • Orode Doherty,
  • Susana Oguntoye,
  • Kayla Seadon,
  • Oren Jalon,
  • Nora Zwingerman,
  • Perpetua Uhomoibhi

DOI
https://doi.org/10.1186/s12936-018-2356-8
Journal volume & issue
Vol. 17, no. 1
pp. 1 – 10

Abstract

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Abstract Background The Deki Reader is a diagnostic device used with rapid diagnostic tests (RDTs) and linked to an online database for real-time uploads of patient information and results. This is in contrast to visual interpretation of malaria RDTs recorded on the District Health Information System (DHIS). This paper compares records for use of the Deki Reader with DHIS records of visual interpretation of RDTs. Results A total of 4063 patient encounters/tests were recorded on the Deki Reader database between June 1st and December 31st, 2016. These tests were for 2629 persons who presented with fever and had RDT done. In comparison, data from DHIS 2.0 for same period recorded 7201 persons presenting with fever. 2421 out of the 2629 persons (92.1%), received RDT using Deki Reader compared to 6535 out of 7201 persons (90.4%) recorded on DHIS (p = 0.04). From DHIS records, malaria positivity rate was 51.6% (3375 out of 6535 persons) compared to Deki Reader records of 23.6% (572 out of 2421 persons). The difference between these two rates was significant (p < 0.001). The odds ratio (95% CI) for the association between use of Deki Reader and having a positive malaria result was 0.29 (0.26–0.32). DHIS showed that 4008 persons received Artemisinin-based combination therapy (ACT) while 3989 persons tested positive with RDT or microscopy, compared to 691 out of 705 persons (98.0%) using Deki Reader. Finally, Deki Reader identified 618 processing and manufacturers errors with an error rate of 15.3%. Conclusion The Deki Reader is likely a useful tool for malaria diagnosis, treatment, and real-time data management. It potentially improves diagnostic quality, reduces wastage in ACT administration and improves data quality.