TY - JOUR
T1 - Connected diagnostics to improve accurate diagnosis, treatment, and conditional payment of malaria services in Kenya
AU - van Duijn, Shannen M. C.
AU - Siteyi, Angela K.
AU - Smith, Sherzel
AU - Milimo, Emmanuel
AU - Stijvers, Leon
AU - Oguttu, Monica
AU - Amollo, Michael O.
AU - Okeyo, Edward O.
AU - Dayo, Lilyana
AU - Kwambai, Titus
AU - Onyango, Dickens
AU - Rinke de Wit, Tobias F.
N1 - Funding Information: This study was supported by seed funding from the Joep Lange Institute as well as funding from the Ministry of Foreign Affairs of the Netherlands. The funders of this work had no role further in the study. Their funds were solely used for the implementation of Connected Diagnostics as a digital innovation as part of PharmAccess operations in Kenya. Funding Information: The authors would like to express gratitude to all clinicians, nurses, lab technicians, and M-TIBA agents who were involved in the field work of this study, and the respondents who participated in the interviews. We would also like to thank the Kisumu Department of Health for its permission and cooperation to execute this study. Seed funding for this project was generously provided by the Joep Lange Institute. This work was also largely supported by the Netherlands Ministry of Foreign Affairs through a core-grant to PharmAccess Foundation. Funding Information: The authors would like to express gratitude to all clinicians, nurses, lab technicians, and M-TIBA agents who were involved in the field work of this study, and the respondents who participated in the interviews. We would also like to thank the Kisumu Department of Health for its permission and cooperation to execute this study. Seed funding for this project was generously provided by the Joep Lange Institute. This work was also largely supported by the Netherlands Ministry of Foreign Affairs through a core-grant to PharmAccess Foundation. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/12/1
Y1 - 2021/12/1
N2 - Background: In sub-Saharan Africa, the material and human capacity to diagnose patients reporting with fever to healthcare providers is largely insufficient. Febrile patients are typically treated presumptively with antimalarials and/or antibiotics. Such over-prescription can lead to drug resistance and involves unnecessary costs to the health system. International funding for malaria is currently not sufficient to control malaria. Transition to domestic funding is challenged by UHC efforts and recent COVID-19 outbreak. Herewith we present a digital approach to improve efficiencies in diagnosis and treatment of malaria in endemic Kisumu, Kenya: Connected Diagnostics. The objective of this study is to evaluate the feasibility, user experience and clinical performance of this approach in Kisumu. Methods: Our intervention was performed Oct 2017–Dec 2018 across five private providers in Kisumu. Patients were enrolled on M-TIBA platform, diagnostic test results digitized, and only positive patients were digitally entitled to malaria treatment. Data on socio-demographics, healthcare transactions and medical outcomes were analysed using standard descriptive quantitative statistics. Provider perspectives were gathered by 19 semi-structured interviews. Results: In total 11,689 febrile patients were digitally tested through five private providers. Malaria positivity ranged from 7.4 to 30.2% between providers, significantly more amongst the poor (p < 0.05). Prescription of antimalarials was substantially aberrant from National Guidelines, with 28% over-prescription (4.6–63.3% per provider) and prescription of branded versus generic antimalarials differing amongst facilities and correlating with the socioeconomic status of clients. Challenges were encountered transitioning from microscopy to RDT. Conclusion: We provide full proof-of-concept of innovative Connected Diagnostics to use digitized malaria diagnostics to earmark digital entitlements for correct malaria treatment of patients. This approach has large cost-saving and quality improvement potential.
AB - Background: In sub-Saharan Africa, the material and human capacity to diagnose patients reporting with fever to healthcare providers is largely insufficient. Febrile patients are typically treated presumptively with antimalarials and/or antibiotics. Such over-prescription can lead to drug resistance and involves unnecessary costs to the health system. International funding for malaria is currently not sufficient to control malaria. Transition to domestic funding is challenged by UHC efforts and recent COVID-19 outbreak. Herewith we present a digital approach to improve efficiencies in diagnosis and treatment of malaria in endemic Kisumu, Kenya: Connected Diagnostics. The objective of this study is to evaluate the feasibility, user experience and clinical performance of this approach in Kisumu. Methods: Our intervention was performed Oct 2017–Dec 2018 across five private providers in Kisumu. Patients were enrolled on M-TIBA platform, diagnostic test results digitized, and only positive patients were digitally entitled to malaria treatment. Data on socio-demographics, healthcare transactions and medical outcomes were analysed using standard descriptive quantitative statistics. Provider perspectives were gathered by 19 semi-structured interviews. Results: In total 11,689 febrile patients were digitally tested through five private providers. Malaria positivity ranged from 7.4 to 30.2% between providers, significantly more amongst the poor (p < 0.05). Prescription of antimalarials was substantially aberrant from National Guidelines, with 28% over-prescription (4.6–63.3% per provider) and prescription of branded versus generic antimalarials differing amongst facilities and correlating with the socioeconomic status of clients. Challenges were encountered transitioning from microscopy to RDT. Conclusion: We provide full proof-of-concept of innovative Connected Diagnostics to use digitized malaria diagnostics to earmark digital entitlements for correct malaria treatment of patients. This approach has large cost-saving and quality improvement potential.
KW - Conditional payments
KW - Connected diagnostics
KW - Diagnosis
KW - Kenya
KW - Malaria
KW - Treatment
UR - http://www.scopus.com/inward/record.url?scp=85111991052&partnerID=8YFLogxK
U2 - https://doi.org/10.1186/s12911-021-01600-z
DO - https://doi.org/10.1186/s12911-021-01600-z
M3 - Article
C2 - 34348696
SN - 1472-6947
VL - 21
JO - BMC medical informatics and decision making
JF - BMC medical informatics and decision making
IS - 1
M1 - 233
ER -