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      The impact of Ghana’s R3M programme on the provision of safe abortions and postabortion care

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          Abstract

          In 2006, in response to the high maternal mortality, driven largely by unsafe abortions, the government of Ghana, in partnership with other organizations, launched the reducing maternal mortality and morbidity (R3M) programme in seven districts in Greater Accra, Ashanti and Eastern, to improve comprehensive abortion care services. This article examines whether this intervention made a difference to the provision of safe abortion services and postabortion care (PAC). We also examine the role played by provider attitudes and knowledge of the abortion law, on providers with clinical training in service provision. Primary data on health care providers in Ghana, collected using a quasi-experimental design, were analysed using propensity score weighting. Apart from the treatment group, the sample included two controls: (1) Districts in Accra, Ashanti and Eastern, not exposed to the treatment; and (2) Districts from distant Brong Ahafo, also not exposed to the treatment. The findings show that providers in the treatment group are nearly 16 times as likely to provide safe abortions compared with their peers in Brong Ahafo, and ∼2.5 times as likely compared with providers in the other control group. R3M providers were also different from their peers in providing PAC. Associations between provider attitudes and knowledge of the law on both outcomes were either non-significant or inconsistent including for providers with clinical knowledge of abortion provision. Provider confidence however is strongly associated with service provision. We conclude that the R3M programme is helping safe abortion provision, with the differences being greater with control groups that are geographically distant, perhaps owing to lower contamination from movement of providers between facilities. Increasing provider confidence is key to improving both safe abortion provision and PAC.

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          Most cited references28

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          Safe abortion: technical and policy guidance for health systems

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            Editorial: can China master the guideline challenge?

            China is experiencing increased health care use and expenditures, without sufficient controls to ensure quality and value. Transparent, cost-conscious and patient-centered guidelines based on the best available evidence could help establishing these quality and practice measures. We examined how guidelines could support the Chinese health reform. Specifically, we summarized the current state of the art and related challenges in guideline development and explored possible solutions in the context of the Chinese health reform. China currently lacks capacity for evidence-based guideline development and coordination by a central agency. Most Chinese guideline users rely on recommendations developed by professional groups that lack demonstration of transparency (including conflict of interest management and evidence synthesis) and quality. These deficiencies appear larger than in other regions of the world. In addition, misperceptions about the role of guidelines in assisting practitioners as opposed to providing rules requiring adherence, and a perception that traditional Chinese medicine (TCM) cannot be appropriately incorporated in guidelines are present. China’s capacity could be strengthened by a central guideline agency to provide or coordinate evidence synthesis for guideline development and to oversee the work of guideline developers. China can build on what is known and work with the international community to develop methods to meet the challenges of evidence-based guideline development.
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              Weighting regressions by propensity scores.

              Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will increase the bias in estimated causal parameters. If investigators have a good causal model, it seems better just to fit the model without weights. If the causal model is improperly specified, there can be significant problems in retrieving the situation by weighting, although weighting may help under some circumstances.
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                Author and article information

                Journal
                Health Policy Plan
                Health Policy Plan
                heapol
                heapol
                Health Policy and Planning
                Oxford University Press
                0268-1080
                1460-2237
                October 2015
                25 September 2014
                25 September 2014
                : 30
                : 8
                : 1017-1031
                Affiliations
                1Research Division, Guttmacher Institute, New York, NY, USA, 2Centro de Estudios Demográfico, Urbanos y Ambientales, El Colegio de Méico, Mexico and 3Institute for Statistical, Social, and Economic Research, University of Ghana, Legon, Ghana
                Author notes
                *Corresponding author. Guttmacher Institute, 125 Maiden Lane, 7th Floor, New York, NY 10038, USA. E-mail: asundaram@ 123456guttmacher.org
                Article
                czu105
                10.1093/heapol/czu105
                4559115
                25261230
                390d8768-5e33-48eb-a328-2b1c1b173a38
                Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 19 August 2014
                Page count
                Pages: 15
                Categories
                Original Articles

                Social policy & Welfare
                abortion,ghana,programme evaluation,propensity score analysis
                Social policy & Welfare
                abortion, ghana, programme evaluation, propensity score analysis

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