Cargando…

Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2

Introduction:Developing countries are increasingly strengthening national health information systems (HIS) for evidence-based decision-making. However, the inability to report indicator data automatically from electronic medical record systems (EMR) hinders this process. Data are often printed and m...

Descripción completa

Detalles Bibliográficos
Autores principales: Kariuki, James M., Manders, Eric-Jan, Richards, Janise, Oluoch, Tom, Kimanga, Davies, Wanyee, Steve, Kwach, James O., Santas, Xenophon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: University of Illinois at Chicago Library 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5266757/
https://www.ncbi.nlm.nih.gov/pubmed/28149444
http://dx.doi.org/10.5210/ojphi.v8i2.6722
_version_ 1782500506737836032
author Kariuki, James M.
Manders, Eric-Jan
Richards, Janise
Oluoch, Tom
Kimanga, Davies
Wanyee, Steve
Kwach, James O.
Santas, Xenophon
author_facet Kariuki, James M.
Manders, Eric-Jan
Richards, Janise
Oluoch, Tom
Kimanga, Davies
Wanyee, Steve
Kwach, James O.
Santas, Xenophon
author_sort Kariuki, James M.
collection PubMed
description Introduction:Developing countries are increasingly strengthening national health information systems (HIS) for evidence-based decision-making. However, the inability to report indicator data automatically from electronic medical record systems (EMR) hinders this process. Data are often printed and manually re-entered into aggregate reporting systems. This affects data completeness, accuracy, reporting timeliness, and burdens staff who support routine indicator reporting from patient-level data. Method: After conducting a feasibility test to exchange indicator data from Open Medical Records System (OpenMRS) to District Health Information System version 2 (DHIS2), we conducted a field test at a health facility in Kenya. We configured a field-test DHIS2 instance, similar to the Kenya Ministry of Health (MOH) DHIS2, to receive HIV care and treatment indicator data and the KenyaEMR, a customized version of OpenMRS, to generate and transmit the data from a health facility. After training facility staff how to send data using DHIS2 reporting module, we compared completeness, accuracy and timeliness of automated indicator reporting with facility monthly reports manually entered into MOH DHIS2. Results: All 45 data values in the automated reporting process were 100% complete and accurate while in manual entry process, data completeness ranged from 66.7% to 100% and accuracy ranged from 33.3% to 95.6% for seven months (July 2013-January 2014). Manual tally and entry process required at least one person to perform each of the five reporting activities, generating data from EMR and manual entry required at least one person to perform each of the three reporting activities, while automated reporting process had one activity performed by one person. Manual tally and entry observed in October 2013 took 375 minutes. Average time to generate data and manually enter into DHIS2 was over half an hour (M=32.35 mins, SD=0.29) compared to less than a minute for automated submission (M=0.19 mins, SD=0.15). Discussion and Conclusion: The results indicate that indicator data sent electronically from OpenMRS-based EMR at a health facility to DHIS2 improves data completeness, eliminates transcription errors and delays in reporting, and reduces the reporting burden on human resources. This increases availability of quality indicator data using available resources to facilitate monitoring service delivery and measuring progress towards set goals.
format Online
Article
Text
id pubmed-5266757
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher University of Illinois at Chicago Library
record_format MEDLINE/PubMed
spelling pubmed-52667572017-02-01 Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2 Kariuki, James M. Manders, Eric-Jan Richards, Janise Oluoch, Tom Kimanga, Davies Wanyee, Steve Kwach, James O. Santas, Xenophon Online J Public Health Inform Research Article Introduction:Developing countries are increasingly strengthening national health information systems (HIS) for evidence-based decision-making. However, the inability to report indicator data automatically from electronic medical record systems (EMR) hinders this process. Data are often printed and manually re-entered into aggregate reporting systems. This affects data completeness, accuracy, reporting timeliness, and burdens staff who support routine indicator reporting from patient-level data. Method: After conducting a feasibility test to exchange indicator data from Open Medical Records System (OpenMRS) to District Health Information System version 2 (DHIS2), we conducted a field test at a health facility in Kenya. We configured a field-test DHIS2 instance, similar to the Kenya Ministry of Health (MOH) DHIS2, to receive HIV care and treatment indicator data and the KenyaEMR, a customized version of OpenMRS, to generate and transmit the data from a health facility. After training facility staff how to send data using DHIS2 reporting module, we compared completeness, accuracy and timeliness of automated indicator reporting with facility monthly reports manually entered into MOH DHIS2. Results: All 45 data values in the automated reporting process were 100% complete and accurate while in manual entry process, data completeness ranged from 66.7% to 100% and accuracy ranged from 33.3% to 95.6% for seven months (July 2013-January 2014). Manual tally and entry process required at least one person to perform each of the five reporting activities, generating data from EMR and manual entry required at least one person to perform each of the three reporting activities, while automated reporting process had one activity performed by one person. Manual tally and entry observed in October 2013 took 375 minutes. Average time to generate data and manually enter into DHIS2 was over half an hour (M=32.35 mins, SD=0.29) compared to less than a minute for automated submission (M=0.19 mins, SD=0.15). Discussion and Conclusion: The results indicate that indicator data sent electronically from OpenMRS-based EMR at a health facility to DHIS2 improves data completeness, eliminates transcription errors and delays in reporting, and reduces the reporting burden on human resources. This increases availability of quality indicator data using available resources to facilitate monitoring service delivery and measuring progress towards set goals. University of Illinois at Chicago Library 2016-09-15 /pmc/articles/PMC5266757/ /pubmed/28149444 http://dx.doi.org/10.5210/ojphi.v8i2.6722 Text en This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
spellingShingle Research Article
Kariuki, James M.
Manders, Eric-Jan
Richards, Janise
Oluoch, Tom
Kimanga, Davies
Wanyee, Steve
Kwach, James O.
Santas, Xenophon
Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2
title Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2
title_full Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2
title_fullStr Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2
title_full_unstemmed Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2
title_short Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2
title_sort automating indicator data reporting from health facility emr to a national aggregate data system in kenya: an interoperability field-test using openmrs and dhis2
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5266757/
https://www.ncbi.nlm.nih.gov/pubmed/28149444
http://dx.doi.org/10.5210/ojphi.v8i2.6722
work_keys_str_mv AT kariukijamesm automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT mandersericjan automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT richardsjanise automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT oluochtom automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT kimangadavies automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT wanyeesteve automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT kwachjameso automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2
AT santasxenophon automatingindicatordatareportingfromhealthfacilityemrtoanationalaggregatedatasysteminkenyaaninteroperabilityfieldtestusingopenmrsanddhis2