Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2023

Open Access 01-12-2023 | Human Immunodeficiency Virus | Database

Leveraging electronic medical records for HIV testing, care, and treatment programming in Kenya—the national data warehouse project

Authors: Margaret Ndisha, Amin S. Hassan, Faith Ngari, Evans Munene, Mary Gikura, Koske Kimutai, Kennedy Muthoka, Lisa Amai Murie, Herman Tolentino, Jacob Odhiambo, Pascal Mwele, Lydia Odero, Kate Mbaire, Gonza Omoro, Davies O. Kimanga

Published in: BMC Medical Informatics and Decision Making | Issue 1/2023

Login to get access

Abstract

Background

Aggregate electronic data repositories and population-level cross-sectional surveys play a critical role in HIV programme monitoring and surveillance for data-driven decision-making. However, these data sources have inherent limitations including inability to respond to public health priorities in real-time and to longitudinally follow up clients for ascertainment of long-term outcomes. Electronic medical records (EMRs) have tremendous potential to bridge these gaps when harnessed into a centralised data repository. We describe the evolution of EMRs and the development of a centralised national data warehouse (NDW) repository. Further, we describe the distribution and representativeness of data from the NDW and explore its potential for population-level surveillance of HIV testing, care and treatment in Kenya.

Main body

Health information systems in Kenya have evolved from simple paper records to web-based EMRs with features that support data transmission to the NDW. The NDW design includes four layers: data warehouse application programming interface (DWAPI), central staging, integration service, and data visualization application. The number of health facilities uploading individual-level data to the NDW increased from 666 in 2016 to 1,516 in 2020, covering 41 of 47 counties in Kenya. By the end of 2020, the NDW hosted longitudinal data from 1,928,458 individuals ever started on antiretroviral therapy (ART). In 2020, there were 936,869 individuals who were active on ART in the NDW, compared to 1,219,276 individuals on ART reported in the aggregate-level Kenya Health Information System (KHIS), suggesting 77% coverage. The proportional distribution of individuals on ART by counties in the NDW was consistent with that from KHIS, suggesting representativeness and generalizability at the population level.

Conclusion

The NDW presents opportunities for individual-level HIV programme monitoring and surveillance because of its longitudinal design and its ability to respond to public health priorities in real-time. A comparison with estimates from KHIS demonstrates that the NDW has high coverage and that the data maybe representative and generalizable at the population-level. The NDW is therefore a unique and complementary resource for HIV programme monitoring and surveillance with potential to strengthen timely data driven decision-making towards HIV epidemic control in Kenya.
Literature
1.
2.
3.
Assefa Y, Gilks CF. Ending the epidemic of HIV/AIDS by 2030: Will there be an endgame to HIV, or an endemic HIV requiring an integrated health systems response in many countries? Int J Infect Dis. 2020;100:273–7.CrossRefPubMed
4.
Harries AD, Suthar AB, Takarinda KC, Tweya H, Kyaw NT, Tayler-Smith K, et al. Ending the HIV/AIDS epidemic in low- and middle-income countries by 2030: is it possible? F1000Res. 2016;5:2328.CrossRefPubMedPubMedCentral
5.
Tange HJ. The paper-based patient record: is it really so bad? Comput Methods Programs Biomed. 1995;48(1–2):127–31.CrossRefPubMed
6.
Dehnavieh R, Haghdoost A, Khosravi A, Hoseinabadi F, Rahimi H, Poursheikhali A, et al. The District Health Information System (DHIS2): a literature review and meta-synthesis of its strengths and operational challenges based on the experiences of 11 countries. Health Inf Manag. 2019;48(2):62–75.PubMed
7.
8.
9.
10.
11.
12.
13.
14.
Achwoka D, Mandala J, Muriithi M, Zeng Y, Chen M, Dirks R, et al. Progress toward elimination of perinatal HIV transmission in Kenya: analysis of early infant diagnosis data. Int J STD AIDS. 2018;29(7):632–40.CrossRefPubMed
15.
Mwau M, Syeunda CA, Adhiambo M, Bwana P, Kithinji L, Mwende J, et al. Scale-up of Kenya’s national HIV viral load program: findings and lessons learned. PLoS One. 2018;13(1):e0190659.CrossRefPubMedPubMedCentral
16.
17.
18.
19.
20.
Kang’a S, Puttkammer N, Wanyee S, Kimanga D, Madrano J, Muthee V, et al. A national standards-based assessment on functionality of electronic medical records systems used in Kenyan public-Sector health facilities. Int J Med Inform. 2017;97:68–75.CrossRefPubMed
21.
22.
23.
Waruru A, Natukunda A, Nyagah LM, Kellogg TA, Zielinski-Gutierrez E, Waruiru W, et al. Where no universal health care identifier exists: comparison and determination of the utility of score-based persons matching algorithms using demographic data. JMIR Public Health Surveill. 2018;4(4):e10436.CrossRefPubMedPubMedCentral
24.
25.
26.
27.
Metadata
Title
Leveraging electronic medical records for HIV testing, care, and treatment programming in Kenya—the national data warehouse project
Authors
Margaret Ndisha
Amin S. Hassan
Faith Ngari
Evans Munene
Mary Gikura
Koske Kimutai
Kennedy Muthoka
Lisa Amai Murie
Herman Tolentino
Jacob Odhiambo
Pascal Mwele
Lydia Odero
Kate Mbaire
Gonza Omoro
Davies O. Kimanga
Publication date
01-12-2023
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2023
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-023-02265-6

Other articles of this Issue 1/2023

BMC Medical Informatics and Decision Making 1/2023 Go to the issue

Research

Validation of the Swedish Quality Register for Ear Surgery – SwedEar

Research

Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital

Research

Automatic medical specialty classification based on patients’ description of their symptoms

Research

Computer-aided autism diagnosis using visual attention models and eye-tracking: replication and improvement proposal

Research

Updating mortality risk estimation in intensive care units from high-dimensional electronic health records with incomplete data

Research

Machine learning prediction for COVID-19 disease severity at hospital admission