May 2014
Dykki Settle, Michael Webba Lwetabe, Amanda Puckett, and Carl Leitner, IntraHealth International
Over the last nine years, the USAID-funded CapacityPlus global project and its predecessor, the Capacity Project, have worked with countries to adapt and implement human resources information systems (HRIS) to better track and support their health workforces. HRIS are only valuable, however, to the extent that stakeholders use them for policy and management decisions, and can only be deemed successful if the decisions in turn lead to better health care. Both criteria wholly depend on the quality of data in the system.
In the context of HRIS, data quality is best defined as how well the data represent the real world (Brown 2011). Poor data quality can adversely affect support for—and even the livelihoods of—the very health workers we want the systems to benefit. Low-quality data can also influence organizational, project, or donor indicators. A national HRIS typically involves numerous data collection and entry steps and many users countrywide, all of which pose challenges to ensuring data quality (Wakibi 2008). As countries move ahead with HRIS scale-up efforts, it is important to establish and use standards (organizational, national, and international) to align and and harmonize the collection, aggregation, and analysis of human resources for health (HRH) data.
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