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Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System

Background: In 2014, a pilot study was conducted to test the feasibility of linking clinic attendance data for young adults at two health facilities to the population register of the Kilifi Health and Demographic Surveillance System (KHDSS). This was part of a cross-sectional survey of health proble...

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Autores principales: Nyundo, Christopher, Doyle, Aoife M., Walumbe, David, Otiende, Mark, Kinuthia, Michael, Amadi, David, Jibendi, Boniface, Mochamah, George, Kihuha, Norbert, Williams, Thomas N., Ross, David A., Bauni, Evasius
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7059845/
https://www.ncbi.nlm.nih.gov/pubmed/32175477
http://dx.doi.org/10.12688/wellcomeopenres.11302.2
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author Nyundo, Christopher
Doyle, Aoife M.
Walumbe, David
Otiende, Mark
Kinuthia, Michael
Amadi, David
Jibendi, Boniface
Mochamah, George
Kihuha, Norbert
Williams, Thomas N.
Ross, David A.
Bauni, Evasius
author_facet Nyundo, Christopher
Doyle, Aoife M.
Walumbe, David
Otiende, Mark
Kinuthia, Michael
Amadi, David
Jibendi, Boniface
Mochamah, George
Kihuha, Norbert
Williams, Thomas N.
Ross, David A.
Bauni, Evasius
author_sort Nyundo, Christopher
collection PubMed
description Background: In 2014, a pilot study was conducted to test the feasibility of linking clinic attendance data for young adults at two health facilities to the population register of the Kilifi Health and Demographic Surveillance System (KHDSS). This was part of a cross-sectional survey of health problems of young people, and we tested the feasibility of using the KHDSS platform for the monitoring of future interventions. Methods: Two facilities were used for this study. Clinical data from consenting participants aged 18-24 years were matched to KHDSS records. Data matching was achieved using national identity card numbers or otherwise using a matching algorithm based on names, sex, date of birth, location of residence and the names of other homestead members. A study form was administered to all matched patients to capture reasons for their visits and time taken to access the services. Distance to health facility from a participants’ homestead was also computed. Results: 628 participated in the study: 386 (61%) at Matsangoni Health Centre, and 242 (39%) at Pingilikani Dispensary. 610 (97%) records were matched to the KHDSS register. Most records (605; 96%) were matched within these health facilities, while 5 (1%) were matched during homestead follow-up visits.  463 (75.9%) of those matched were women. Antenatal care (25%), family planning (13%), respiratory infections (9%) and malaria (9%) were the main reasons for seeking care. Antenatal clinic visits (n=175) and malaria (n=27) were the commonest reasons among women and men, respectively. Participants took 1-1.5 hours to access the services; 490 (81.0%) participants lived within 5 kilometres of a facility. Conclusions: With a full-time research clerk at each health facility, linking health-facility attendance data to a longitudinal HDSS platform was feasible and could be used to monitor and evaluate the impact of health interventions on health care outcomes among young people.
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spelling pubmed-70598452020-03-12 Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System Nyundo, Christopher Doyle, Aoife M. Walumbe, David Otiende, Mark Kinuthia, Michael Amadi, David Jibendi, Boniface Mochamah, George Kihuha, Norbert Williams, Thomas N. Ross, David A. Bauni, Evasius Wellcome Open Res Research Article Background: In 2014, a pilot study was conducted to test the feasibility of linking clinic attendance data for young adults at two health facilities to the population register of the Kilifi Health and Demographic Surveillance System (KHDSS). This was part of a cross-sectional survey of health problems of young people, and we tested the feasibility of using the KHDSS platform for the monitoring of future interventions. Methods: Two facilities were used for this study. Clinical data from consenting participants aged 18-24 years were matched to KHDSS records. Data matching was achieved using national identity card numbers or otherwise using a matching algorithm based on names, sex, date of birth, location of residence and the names of other homestead members. A study form was administered to all matched patients to capture reasons for their visits and time taken to access the services. Distance to health facility from a participants’ homestead was also computed. Results: 628 participated in the study: 386 (61%) at Matsangoni Health Centre, and 242 (39%) at Pingilikani Dispensary. 610 (97%) records were matched to the KHDSS register. Most records (605; 96%) were matched within these health facilities, while 5 (1%) were matched during homestead follow-up visits.  463 (75.9%) of those matched were women. Antenatal care (25%), family planning (13%), respiratory infections (9%) and malaria (9%) were the main reasons for seeking care. Antenatal clinic visits (n=175) and malaria (n=27) were the commonest reasons among women and men, respectively. Participants took 1-1.5 hours to access the services; 490 (81.0%) participants lived within 5 kilometres of a facility. Conclusions: With a full-time research clerk at each health facility, linking health-facility attendance data to a longitudinal HDSS platform was feasible and could be used to monitor and evaluate the impact of health interventions on health care outcomes among young people. F1000 Research Limited 2020-02-27 /pmc/articles/PMC7059845/ /pubmed/32175477 http://dx.doi.org/10.12688/wellcomeopenres.11302.2 Text en Copyright: © 2020 Nyundo C et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Nyundo, Christopher
Doyle, Aoife M.
Walumbe, David
Otiende, Mark
Kinuthia, Michael
Amadi, David
Jibendi, Boniface
Mochamah, George
Kihuha, Norbert
Williams, Thomas N.
Ross, David A.
Bauni, Evasius
Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
title Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
title_full Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
title_fullStr Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
title_full_unstemmed Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
title_short Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
title_sort linking health facility data from young adults aged 18-24 years to longitudinal demographic data: experience from the kilifi health and demographic surveillance system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7059845/
https://www.ncbi.nlm.nih.gov/pubmed/32175477
http://dx.doi.org/10.12688/wellcomeopenres.11302.2
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