The Consistency and Concurrency Between the Kenya HIV/AIDS Program Monitoring System (KePMs) and the National Reporting System (DHIS2), 2012

Raphael Pundo, Ayub Shisia Manya, Erastus Mburu, Jørn Braa

Abstract


Background and Purpose: Kenya implemented the use of District Health Information Software (DHIS2) countrywide in 2011.  The successful roll out of DHIS as the national reporting system provided a strong foundation for the development of “One unified and integrated, country owned, country led, National Health Information System (NHIS).” In order to achieve this, there was need to transition all existing parallel reporting systems into the DHIS. The Kenya HIV/AIDS Program Monitoring System (KePMs) was one of the major parallel reporting systems that were targeted for integration. KePMs is a computerized database for the management and analysis of the President's Emergency Plan for AIDS Relief Care (PEPFAR), treatment and prevention indicators required by United States of America Government program managers. This paper examines the current status of the implementation of the DHIS2 for use as the national health information system in order to inform transition from KePMs to DHIS2. It examines the consistency and concurrency between the DHIS2 data and KePMs data using selected indicators.

Methods: In order to assess the concurrency of data between KePMs and DHIS2, data from sampled facilities and sampled indicators (in HIV Testing and Counselling (HTC), Prevention of Mother to Child Transmission (PMTCT) and Care and Treatment (CT)) were analysed by comparing datasets from the two databases (i.e. DHIS2 and KePMs).

Indicator selection was purposive as determined from an indicator matrix developed in previous meetings. The PEPFAR 2012 data set on KePMs was considered as the sampling frame for facilities in both the KePMs and DHIS2. The data for September 2012 were used. Data were received from one reporting tool (dataset); the MOH711. A convenient sample size of 141 facilities (comprising three facilities per county) was determined.

Descriptive data analysis was done using Microsoft Excel package. The analysis involved computing the concurrency and consistency between the data reported in DHIS2 and KePMs for the period of September 2012.  During the analysis of these data, concurrency was only looking at the sites that had reported data while consistency checked through all the 134 health facilities sampled.

Results: On average, data in the selected indicators showed a consistency rate of 79.5% in both systems. The consistency rate was above 75% in all indicators except in the indicator; “Number of individual tested and received results through Provider Initiated Testing and Counselling (DTC/PITC)” which had 63%. The average concurency rate was 69%. Concurrency rates varied amongst the various indicators with DTC/PITC achieving the highest concurrency rate of 97%. The lowest concurency rate was for “couples testing for HIV” at 34%. In general 74% of data in both systems had no variance.

Conclusions: The main reason for developing parallel system was the absence of a reliable national system. The results show a very high consistency rate between the two systems. Minor differences in data were attributed to data entry and poor data validation rules. It is recommended that with minor improvements, the DHIS is in a position to provide the necessary data to cater for all stakeholders and hence become the National reporting system.

Keywords: Health Information Systems, District Health Information Software, Service delivery Indicators


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References


Braa J. A data warehouse approach can manage multiple data sets. Bull World Health Organ 2005; 83: 638-9 pmid: 16184286.

Manya, Ayub, Jørn Braa, Lars Helge Øverland, Ola Hodne Titlestad, Jeremiah Mumo, and Charles Nzioka. 2012. “National Roll Out of District Health Information Software (DHIS 2) in Kenya, 2011 – Central Server and Cloud Based Infrastructure.” IST-Africa 2012 Conference Proceedings.

DHIS2 Website, accessed on 1st June, 2013. http://dhis2.org/

http://snisnet.net/KePMS.php. Accessed on 30th July, 2013




DOI: http://dx.doi.org/10.12856/JHIA-2013-v1-i1-56

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