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Data guardian south africa1/1/2024 Growing interest in using them for evaluations. 1 used data from an integrated management of childhood illness (IMCI) database toĮvaluate under-5 mortality and the timing of IMCI implementation in 213 districts in Egypt.īennett et al. 3 used data collected from nine roadside wellness centers in South Africa to evaluate the 2 used data from Zambia’s RHIS to evaluate an insecticide-treated net program andĬonfirmed outpatient malaria incidence. Services accessed by long-distance truck drivers and the drivers’ sociodemographicĬharacteristics. 4 used data from the National Health Service (NHS) in Leicester to assess hospital cost Some researchers are optimistic about this underutilized data source. 5 discussed how certain evaluation designs, such as interrupted time series analysis, areīetter suited to routine data than to population-based surveys. 2 argued that RHIS data cannot be used for rigorous program evaluation without complex 6 expressed ‘concerns over internal validity, completeness and potential bias inĮstimates of program and intervention impact’, and Bennett et al. From these, we have insights not yet mentioned in the MEASURE Evaluation used RHIS data to conduct several process and outcome evaluations in low-Īnd middle-income countries (LMIC). Literature on several topics: RHIS data access, quality, and relevance. Furthermore, systems themselves may be housed on Often, though, nongovernmental actors are credentialed to build National RHIS belong to national governments, to monitor and evaluate health serviceĭelivery, health system outcomes, and health outcomes and to improve lives. ![]() Servers paid for by nongovernmental partners. Governments have the right to control what isĬollected, used, and shared 7 and to whom they give access. Important for national security, such as birth and death registrations) and the research 8ĭepending on the type of data (sensitive, such as HIV status or patient-level records, or Patients in some countries, like the United Kingdom, canĬhoose whether their health records are used for evaluation. Purpose, the levels of approval can be numerous, complex, and time-consuming. ![]() ![]() Yet, theseĮlements of a data system and data sharing should not be perceived as mere procedural hurdles. They reflect the ethical integrity of the system and processes.Ī central concern of using routine data for research and evaluations is whether the data canīe trusted and whether the data systems and the data stewards are trustworthy. The most common metrics – accuracy, completeness, and timeliness – contribute Data quality 9 comprises accuracy, reliability, precision, completeness, timeliness, integrity, andĬonfidentiality. Well-established routine data systems such as the NHS, patient privacy, data security, and Significantly to whether reliable conclusions can be drawn from the data. 8 The NHS with its large, consistent, and clean data has been called a ‘goldmine’ forĮntities interested in voluminous data for pharmaceutical research and machine learning.
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