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Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya

BACKGROUND: Kenya has since independence struggled to restructure its health system to provide services to its entire population especially in outbreak responses. The last decade has seen the country witness disease outbreaks across the country i.e. Rift Valley fever in June 2018, and Chikungunya an...

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Autores principales: Omondi, Athanasio Japheth, Ochieng, Otieno George, Eliud, Khayo, Yoos, Alison, Kavilo, Muli Rafael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The East African Health Research Commission 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279160/
https://www.ncbi.nlm.nih.gov/pubmed/34308238
http://dx.doi.org/10.24248/eahrj.v4i2.644
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author Omondi, Athanasio Japheth
Ochieng, Otieno George
Eliud, Khayo
Yoos, Alison
Kavilo, Muli Rafael
author_facet Omondi, Athanasio Japheth
Ochieng, Otieno George
Eliud, Khayo
Yoos, Alison
Kavilo, Muli Rafael
author_sort Omondi, Athanasio Japheth
collection PubMed
description BACKGROUND: Kenya has since independence struggled to restructure its health system to provide services to its entire population especially in outbreak responses. The last decade has seen the country witness disease outbreaks across the country i.e. Rift Valley fever in June 2018, and Chikungunya and Dengue fever in Mombasa in February 2018. This exposed the country's lack of preparedness in handling outbreaks at grass root level. Outbreak incidences tend to prevail at community level before a public health action is established, with the situation becoming dire in the lower tier health facilities. OBJECTIVE: The purpose of the study was to assess the uptake of Integrated Disease Surveillance Response (IDSR) health data and utilisation at community level health systems in the six sub counties within Nairobi County of Kenya. METHODOLOGY: The study used cross-sectional descriptive research design on a target population of 1840 community health workers. The study used Yamane formula to calculate the sample size of 371 respondents, selected using stratified sampling and simple random sampling methods. The logistic regression model was used to assess the benefits of Integrated Data Surveillance and Response data in health facilities across Nairobi County. Data was collected using questionnaires, analysis done using Statistical Packages for Social Sciences, and findings presented in form of tables and bar graphs. RESULTS: The study had 315 questionnaires were duly filled and returned, representing 85% response rate. The findings showed that 268(85%) Healthcare Workers lacked training on using disease surveillance data; 236(75%) cited lack of tools for disease surveillance in facilities, while 173(55%)cited lack of timely IDSR data as hindrance to IDSR data uptake. The regression findings showed that training of healthcare workers on IDSR, installation of disease surveillance system tools, and timely collection and dissemination of surveillance data increases the likelihood of IDSR data uptake in community health facilities. CONCLUSION: The study concluded that IDSR system tools should be installed in community health facilities across the six sub counties in Nairobi County. Training should be emphasised to ensure all health care workers have the required skills to use the IDSR data. There is need to ensure IDSR data is collected and disseminated on time to make it available for interpretation and use by health care workers in their respective facilities.
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spelling pubmed-82791602021-07-22 Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya Omondi, Athanasio Japheth Ochieng, Otieno George Eliud, Khayo Yoos, Alison Kavilo, Muli Rafael East Afr Health Res J Original Articles BACKGROUND: Kenya has since independence struggled to restructure its health system to provide services to its entire population especially in outbreak responses. The last decade has seen the country witness disease outbreaks across the country i.e. Rift Valley fever in June 2018, and Chikungunya and Dengue fever in Mombasa in February 2018. This exposed the country's lack of preparedness in handling outbreaks at grass root level. Outbreak incidences tend to prevail at community level before a public health action is established, with the situation becoming dire in the lower tier health facilities. OBJECTIVE: The purpose of the study was to assess the uptake of Integrated Disease Surveillance Response (IDSR) health data and utilisation at community level health systems in the six sub counties within Nairobi County of Kenya. METHODOLOGY: The study used cross-sectional descriptive research design on a target population of 1840 community health workers. The study used Yamane formula to calculate the sample size of 371 respondents, selected using stratified sampling and simple random sampling methods. The logistic regression model was used to assess the benefits of Integrated Data Surveillance and Response data in health facilities across Nairobi County. Data was collected using questionnaires, analysis done using Statistical Packages for Social Sciences, and findings presented in form of tables and bar graphs. RESULTS: The study had 315 questionnaires were duly filled and returned, representing 85% response rate. The findings showed that 268(85%) Healthcare Workers lacked training on using disease surveillance data; 236(75%) cited lack of tools for disease surveillance in facilities, while 173(55%)cited lack of timely IDSR data as hindrance to IDSR data uptake. The regression findings showed that training of healthcare workers on IDSR, installation of disease surveillance system tools, and timely collection and dissemination of surveillance data increases the likelihood of IDSR data uptake in community health facilities. CONCLUSION: The study concluded that IDSR system tools should be installed in community health facilities across the six sub counties in Nairobi County. Training should be emphasised to ensure all health care workers have the required skills to use the IDSR data. There is need to ensure IDSR data is collected and disseminated on time to make it available for interpretation and use by health care workers in their respective facilities. The East African Health Research Commission 2020 2020-11-26 /pmc/articles/PMC8279160/ /pubmed/34308238 http://dx.doi.org/10.24248/eahrj.v4i2.644 Text en © The East African Health Research Commission 2020 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. To view a copy of the license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Articles
Omondi, Athanasio Japheth
Ochieng, Otieno George
Eliud, Khayo
Yoos, Alison
Kavilo, Muli Rafael
Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya
title Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya
title_full Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya
title_fullStr Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya
title_full_unstemmed Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya
title_short Assessment of Integrated Disease Surveillance Data Uptake in Community Health Systems within Nairobi County, Kenya
title_sort assessment of integrated disease surveillance data uptake in community health systems within nairobi county, kenya
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279160/
https://www.ncbi.nlm.nih.gov/pubmed/34308238
http://dx.doi.org/10.24248/eahrj.v4i2.644
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