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      Development and Validation of an Index to Measure the Quality of Facility-Based Labor and Delivery Care Processes in Sub-Saharan Africa

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          Abstract

          Background

          High quality care is crucial in ensuring that women and newborns receive interventions that may prevent and treat birth-related complications. As facility deliveries increase in developing countries, there are concerns about service quality. Observation is the gold standard for clinical quality assessment, but existing observation-based measures of obstetric quality of care are lengthy and difficult to administer. There is a lack of consensus on quality indicators for routine intrapartum and immediate postpartum care, including essential newborn care. This study identified key dimensions of the quality of the process of intrapartum and immediate postpartum care (QoPIIPC) in facility deliveries and developed a quality assessment measure representing these dimensions.

          Methods and Findings

          Global maternal and neonatal care experts identified key dimensions of QoPIIPC through a modified Delphi process. Experts also rated indicators of these dimensions from a comprehensive delivery observation checklist used in quality surveys in sub-Saharan African countries. Potential QoPIIPC indices were developed from combinations of highly-rated indicators. Face, content, and criterion validation of these indices was conducted using data from observations of 1,145 deliveries in Kenya, Madagascar, and Tanzania (including Zanzibar). A best-performing index was selected, composed of 20 indicators of intrapartum/immediate postpartum care, including essential newborn care. This index represented most dimensions of QoPIIPC and effectively discriminated between poorly and well-performed deliveries.

          Conclusions

          As facility deliveries increase and the global community pays greater attention to the role of care quality in achieving further maternal and newborn mortality reduction, the QoPIIPC index may be a valuable measure. This index complements and addresses gaps in currently used quality assessment tools. Further evaluation of index usability and reliability is needed. The availability of a streamlined, comprehensive, and validated index may enable ongoing and efficient observation-based assessment of care quality during labor and delivery in sub-Saharan Africa, facilitating targeted quality improvement.

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          Most cited references49

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            • Record: found
            • Abstract: found
            • Article: not found

            Understanding diagnostic tests 3: Receiver operating characteristic curves.

            The results of many clinical tests are quantitative and are provided on a continuous scale. To help decide the presence or absence of disease, a cut-off point for 'normal' or 'abnormal' is chosen. The sensitivity and specificity of a test vary according to the level that is chosen as the cut-off point. The receiver operating characteristic (ROC) curve, a graphical technique for describing and comparing the accuracy of diagnostic tests, is obtained by plotting the sensitivity of a test on the y axis against 1-specificity on the x axis. Two methods commonly used to establish the optimal cut-off point include the point on the ROC curve closest to (0, 1) and the Youden index. The area under the ROC curve provides a measure of the overall performance of a diagnostic test. In this paper, the author explains how the ROC curve can be used to select optimal cut-off points for a test result, to assess the diagnostic accuracy of a test, and to compare the usefulness of tests. The ROC curve is obtained by calculating the sensitivity and specificity of a test at every possible cut-off point, and plotting sensitivity against 1-specificity. The curve may be used to select optimal cut-off values for a test result, to assess the diagnostic accuracy of a test, and to compare the usefulness of different tests.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Defining and classifying clinical indicators for quality improvement.

              J Mainz (2003)
              This paper provides a brief review of definitions, characteristics, and categories of clinical indicators for quality improvement in health care. Clinical indicators assess particular health structures, processes, and outcomes. They can be rate- or mean-based, providing a quantitative basis for quality improvement, or sentinel, identifying incidents of care that trigger further investigation. They can assess aspects of the structure, process, or outcome of health care. Furthermore, indicators can be generic measures that are relevant for most patients or disease-specific, expressing the quality of care for patients with specific diagnoses. Monitoring health care quality is impossible without the use of clinical indicators. They create the basis for quality improvement and prioritization in the health care system. To ensure that reliable and valid clinical indicators are used, they must be designed, defined, and implemented with scientific rigour.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 June 2015
                2015
                : 10
                : 6
                : e0129491
                Affiliations
                [1 ]Department of Population, Family Planning, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
                [2 ]Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
                Shanghai 1st Maternity and Infant hospital of Tongji University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: VT. Performed the experiments: VT. Analyzed the data: VT. Contributed reagents/materials/analysis tools: LB. Wrote the paper: VT CS DS LB. provided substantive contributions to the study design: CS DS LB; oversaw data collection for the secondary data source: LB.

                [¤]

                Current address: EngenderHealth, New York, New York, United States of America.

                Article
                PONE-D-14-32054
                10.1371/journal.pone.0129491
                4479466
                26107655
                b022df0f-b70b-4b53-a7a4-753cff5851b2
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 16 August 2014
                : 8 May 2015
                Page count
                Figures: 4, Tables: 12, Pages: 29
                Funding
                This study was supported by USAID ( www.usaid.gov), through the MCHIP project ( www.mchip.net), USAID Award #GHS-A-00-08-00002-000. The funder had no role in study design, data collection and analysis, or decision to publish. Representatives of the funder were provided with a draft of this manuscript before submission for publication.
                Categories
                Research Article
                Custom metadata
                The data used in the secondary analysis described in this study were obtained from the Maternal and Child Integrated Program (MCHIP) implemented by Jhpiego and supported by the United States Agency for International Development (USAID). MCHIP conducted the Quality of Care (QoC) Assessment surveys described in the manuscript. The authors cannot make datasets available directly as manuscript supplemental files because the data were collected under an IRB-approved study protocol that included protection of the confidentiality of study facilities and providers, as described in the informed consent forms read and signed by facility in-charges. The datasets contain facility identifiers and names. However, datasets with facility names and other confidential information redacted can be made available through direct communication with QoC Assessment study team. Interested readers can contact Dr. Jim Ricca at jim.ricca@ 123456jhpiego.org .

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