Do interoperable national information systems enhance availability of data to assess the effect of scale-up of HIV services on health workforce deployment in resource-limited countries?

• Published in: Studies in health technology and informatics Vol. 216; p. 677
• Main Authors: Oluoch, Tom, Muturi, David, Kiriinya, Rose, Waruru, Anthony, Lanyo, Kevin, Nguni, Robert, Ojwang, James, Waters, Keith P, Richards, Janise
• Format: Journal Article
• Language: English
• Published: Netherlands 2015
• Subjects: Africa South of the Sahara; Developing Countries; Efficiency, Organizational; Health Information Exchange - supply & distribution; Health Information Systems - supply & distribution; Health Manpower - utilization; Health Services Accessibility - statistics & numerical data; HIV Infections - diagnosis; HIV Infections - epidemiology; HIV Infections - therapy; Humans; Kenya; Medical Record Linkage - methods; Systems Integration; Utilization Review
• ISSN: 0926-9630
• DOI: 10.3233/978-1-61499-564-7-677

Sub-Saharan Africa (SSA) bears the heaviest burden of the HIV epidemic. Health workers play a critical role in the scale-up of HIV programs. SSA also has the weakest information and communication technology (ICT) infrastructure globally. Implementing interoperable national health information systems (HIS) is a challenge, even in developed countries. Countries in resource-limited settings have yet to demonstrate that interoperable systems can be achieved, and can improve quality of healthcare through enhanced data availability and use in the deployment of the health workforce. We established interoperable HIS integrating a Master Facility List (MFL), District Health Information Software (DHIS2), and Human Resources Information Systems (HRIS) through application programmers interfaces (API). We abstracted data on HIV care, health workers deployment, and health facilities geo-coordinates. Over 95% of data elements were exchanged between the MFL-DHIS and HRIS-DHIS. The correlation between the number of HIV-positive clients and nurses and clinical officers in 2013 was R2=0.251 and R2=0.261 respectively. Wrong MFL codes, data type mis-match and hyphens in legacy data were key causes of data transmission errors. Lack of information exchange standards for aggregate data made programming time-consuming.