Evaluating quality of obstetric care in low-resource settings: Building on the literature to design tailor-made evaluation instruments - an illustration in Burkina Faso

<p>Abstract</p> <p>Background</p> <p>There are many instruments available freely for evaluating obstetric care quality in low-resource settings. However, this profusion can be confusing; moreover, evaluation instruments need to be adapted to local issues. In this article, we present tools we developed to guide the choice of instruments and describe how we used them in Burkina Faso to facilitate the participative development of a locally adapted instrument.</p> <p>Methods</p> <p>Based on a literature review, we developed two tools: a conceptual framework and an analysis grid of existing evaluation instruments. Subsequently, we facilitated several sessions with evaluation stakeholders in Burkina Faso. They used the tools to develop a locally adapted evaluation instrument that was subsequently tested in six healthcare facilities.</p> <p>Results</p> <p>Three outputs emerged from this process:</p> <p>1) A comprehensive conceptual framework for the quality of obstetric care, each component of which is a potential criterion for evaluation.</p> <p>2) A grid analyzing 37 instruments for evaluating the quality of obstetric care in low-resource settings. We highlight their key characteristics and describe how the grid can be used to prepare a new evaluation.</p> <p>3) An evaluation instrument adapted to Burkina Faso. We describe the experience of the Burkinabé stakeholders in developing this instrument using the conceptual framework and the analysis grid, while taking into account local realities.</p> <p>Conclusions</p> <p>This experience demonstrates how drawing upon existing instruments can inspire and rationalize the process of developing a new, tailor-made instrument. Two tools that came out of this experience can be useful to other teams: a conceptual framework for the quality of obstetric care and an analysis grid of existing evaluation instruments. These provide an easily accessible synthesis of the literature and are useful in integrating it with the context-specific knowledge of local actors, resulting in evaluation instruments that have both scientific and local legitimacy.</p

Estimating background rates of Guillain-Barré Syndrome in Ontario in order to respond to safety concerns during pandemic H1N1/09 immunization campaign

Abstract Background The province of Ontario, Canada initiated mass immunization clinics with adjuvanted pandemic H1N1 influenza vaccine in October 2009. Due to the scale of the campaign, temporal associations with Guillain-Barré syndrome (GBS) and vaccination were expected. The objectives of this analysis were to estimate the number of background GBS cases expected to occur in the projected vaccinated population and to estimate the number of additional GBS cases which would be expected if an association with vaccination existed. The number of influenza-associated GBS cases was also determined. Methods Baseline incidence rates of GBS were determined from published Canadian studies and applied to projected vaccine coverage data to estimate the expected number of GBS cases in the vaccinated population. Assuming an association with vaccine existed, the number of additional cases of GBS expected was determined by applying the rates observed during the 1976 Swine Flu and 1992/1994 seasonal influenza campaigns in the United States. The number of influenza-associated GBS cases expected to occur during the vaccination campaign was determined based on risk estimates of GBS after influenza infection and provincial influenza infection rates using a combination of laboratory-confirmed cases and data from a seroprevalence study. Results The overall provincial vaccine coverage was estimated to be between 32% and 38%. Assuming 38% coverage, between 6 and 13 background cases of GBS were expected within this projected vaccinated cohort (assuming 32% coverage yielded between 5-11 background cases). An additional 6 or 42 cases would be expected if an association between GBS and influenza vaccine was observed (assuming 32% coverage yielded 5 or 35 additional cases); while up to 31 influenza-associated GBS cases could be expected to occur. In comparison, during the same period, only 7 cases of GBS were reported among vaccinated persons. Conclusions Our analyses do not suggest an increased number of GBS cases due to the vaccine. Awareness of expected rates of GBS is crucial when assessing adverse events following influenza immunization. Furthermore, since individuals with influenza infection are also at risk of developing GBS, they must be considered in such analyses, particularly if the vaccine campaign and disease are occurring concurrently