Blog
About

5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Advancing measurement and monitoring of reproductive, maternal, newborn and child health and nutrition: global and country perspectives

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction Aligned with the Sustainable Development Goals, the Global Strategy for Women’s, Children’s and Adolescents’ Health (2016–2030) represents an essential shift in prioritisation for actions designed to help families live healthy, secure lives and fulfil their economic potential.1 The reproductive, maternal, newborn, child and adolescent health and nutrition (RMNCAH-N) agenda is now both broader and more complex than was the case during the Millennium Development Goal era, creating a need for new data. To contribute to this need, Countdown to 2030 for Women’s, Children’s and Adolescents’ Health (Countdown), a multi-institutional network of academics from institutions around the world and representatives from United Nations agencies and civil society, aims to enhance monitoring and measurement of women’s, children’s and adolescents’ health globally and in countries.2 In 2018, Countdown organised a measurement conference in Stellenbosch, South Africa, that brought together 100 experts in multiple areas of RMNCAH-N, which resulted in the six papers in this supplement and an overall research agenda. The manuscripts in this collection represent the first developments of Countdown’s work to enhance measurement. They identify some of the persistent measurement and monitoring gaps in RMNCAH-N, for example, by reviewing the evidence on methods for generating effective coverage estimates and presenting actionable analytical methods to identify inequalities within and between countries. The collection also considers measurement advances for early childhood development and for nutrition. Further, it expands to analyse new priority issues, including using national surveys to analyse the impact of armed conflicts on RMNCAH-N;3 and describing the new data needed to better understand the social, political and contextual complexity of health system governance. Countdown will continue to extend this measurement improvement agenda. In some aspects, however, the measurement and monitoring of RMNCAH-N is more advanced than other health areas, such as infectious diseases, non-communicable diseases, injuries and mental health. Many indicators of service contact and mortality are collected through surveys and can be disaggregated by multiple dimensions of inequality. Indeed, the inequality component of the Universal Health Coverage service coverage index is almost entirely based on RMNCAH-N indicators.4 Major gaps remain, however, in terms of service quality and effective coverage, maternal mortality, morbidity and causes of deaths, cognitive development and multiple other indicators of child well-being, and multisectoral service provision. Beyond the technical detail of each field, the papers in the collection broadly share two common calls for measurement. First, the need for greater harmonisation of measurement standards, ideally underpinned by an authority such as WHO, as demonstrated by current endeavours in the field of maternal and newborn health, for example.5 Second, the need for investment in further development of measurement tools and methods. Both are plainly justified and align well with expert opinion.6 Consistent with Countdown’s commitment to situate more measurement work in countries and to help build domestic measurement expertise, harmonisation and investment have potential to advance agendas at both global and national levels. But, depending on perspective, there is the possibility of a tension between these two sets of needs. Harmonisation A common theme across the manuscripts is the need for a process to generate global consensus on a minimum core set of validated coverage indicators on high-impact interventions, with guidance for measurement by WHO, and incorporated into relevant measurement tools. The case is well made that without this the interpretation and comparability of data across time and place would be limited, opportunities for learning reduced and potential for influence diminished. The review by Amouzou et al demonstrates an urgent need for harmonisation of definition and methods if we are to progress quality-adjusted coverage measurement from specialist studies to standard practice.7 For early childhood development, the need for a measurement framework and indicators to enable cross-country comparison of progress and help sustain momentum is clearly made.8 And with only half of high-impact nutrition interventions being measured through large-scale surveys, it is evident that programmes addressing malnutrition need more and standardised data.9 Gillespie et al also make the important point about the possible tension between harmonisation of indicators for global measurement and the indicator definition that speaks to a specific country programme. When measurement is driven by country priorities, the ideal indicators for programme management will depend on the intended use of the data, on the level and frequency of measurement, and on the desire to track progress over time by aligning with past measures. Within countries, governments need to be able to track their own progress and so need a consistent approach to measurement within their own setting. Flexibility in coding and indicator definition is needed to ensure that data can be analysed to meet both global and country needs. This issue is currently prominent for antenatal care as WHO has increased the recommended number of pregnancy contacts from four to eight antenatal visits,10 but most countries are yet to action such a transition and will continue to need to track coverage of at least four visits for some time to come. Similarly, the global definition and measurement of skilled attendance at birth is becoming more precise as quality-of-care issues are more prominent; but, in the face of acute human resource shortages and task-shifting policies, there continues to be considerable variability between country level definitions of the cadres considered to provide skilled care.11 Investment Across multiple topics, investment is needed for better, validated indicators that are integrated in standardised data collection methods with sufficiently large sample sizes for multiple disaggregation, while strengthening country capacity in data analysis and use, to ultimately aid data-informed decision-making and implementation. Whether implicit or explicit, the language of this call for investment primarily focused on investment in better periodic survey data rather than routine health information or indeed qualitative data sources. For example, the agenda to increase the rate of progress in health by making sure that no one is left behind means that we need to be able to gain greater insight from data. This inevitably means larger household survey datasets with bigger sample sizes for more granular, disaggregated analysis. The analysis by Victora et al makes clear the added value of extending relative equity analysis from quintiles to deciles of households, or of examining intersectionality between categories of inequality, for example place of residence and socioeconomic status.12 This is important not least because of the positive evidence that slowly but surely inequities within and between countries are reducing—so that differences are becoming more subtle, more complex. In addition to gaining greater use from surveys, there is also an imperative to invest in the country health information systems. Acknowledged as having potential to contribute to data for decision-making, data from these sources are frequently dismissed because of well-justified concerns about data quality or because of the constraint of working with imperfect denominators. Nonetheless, there are essential reasons for both global and national actors to look for investment to improve on this. First, most country programmes want to base decision-making on their own data and are motivated to build capacity to manipulate their own data; this is well aligned with global actor ambitions to support more effective country-led data-driven decision-making for health. Second, routine data can be available in real time and analysed at macro, meso or micro levels of granularity depending on needs and therefore uniquely suitable for real-time monitoring and course correction,13 again providing alignment for the global community to promote and support implementation science to increase the rate of progress in health. And third, there are many things that surveys cannot reliably measure because the respondents do not know the answer to questions, for example, treatment for illness or measures of healthcare quality.14 For measurement of clinical care of this sort, facility data sources need to be strengthened. And this would be to the benefit of the global community’s need for data that can be analysed to better estimate the potential of health gain that can be derived from contacts with the health service.15 The Countdown to 2030 has shifted its focus on collaborating with country public health institutions and ministries of health to generate evidence and strengthen analytical capacity through regional initiatives. The goal is to further expand these collaborations and strengthen the links with countries’ own reviews of progress and performance of the strategies and plans for women’s, children’s and adolescents’ health. And finally, unpacking the drivers of health, as described by George et al, encourages reflection on the current framing of health and the information we use to inform our vision.16 For this, we need harmonised quantitative data that speak to a service delivery lens—be it survey or administrative—but also other types of data that speak to societal and systems lenses (eg, contextual data on organisational structures, social norms and the interdependence of actors). This agenda, defined and committed to by the Countdown community of measurement experts, needs new data and new combinations of disciplines working together, at global and national levels, to also capture and incorporate country-derived tacit knowledge.

          Related collections

          Most cited references 13

          • Record: found
          • Abstract: not found
          • Article: not found

          Monitoring universal health coverage within the Sustainable Development Goals: development and baseline data for an index of essential health services

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Using multi-country household surveys to understand who provides reproductive and maternal health services in low- and middle-income countries: a critical appraisal of the Demographic and Health Surveys

            Objective The Demographic and Health Surveys (DHS) are a vital data resource for cross-country comparative analyses. This study is part of a set of analyses assessing the types of providers being used for reproductive and maternal health care across 57 countries. Here, we examine some of the challenges encountered using DHS data for this purpose, present the provider classification we used, and provide recommendations to enable more detailed and accurate cross-country comparisons of healthcare provision. Methods We used the most recent DHS surveys between 2000 and 2012; 57 countries had data on family planning and delivery care providers and 47 countries had data on antenatal care. Every possible response option across the 57 countries was listed and categorised. We then developed a classification to group provider response options according to two key dimensions: clinical nature and profit motive. Results We classified the different types of maternal and reproductive healthcare providers, and the individuals providing care. Documented challenges encountered during this process were limitations inherent in household survey data based on respondents’ self-report; conflation of response options in the questionnaire or at the data processing stage; category errors of the place vs. professional for delivery; inability to determine whether care received at home is from the public or private sector; a large number of negligible response options; inconsistencies in coding and analysis of data sets; and the use of inconsistent headings. Conclusions To improve clarity, we recommend addressing issues such as conflation of response options, data on public vs. private provider, inconsistent coding and obtaining metadata. More systematic and standardised collection of data would aid international comparisons of progress towards improved financial protection, and allow us to better characterise the incentives and commercial nature of different providers. Objectif Les enquêtes démographiques et de santé (EDS) sont une ressource vitale de données pour des analyses comparatives entre les pays. Cet article fait partie d'une série d'analyses évaluant les types de prestataires utilisés pour les soins de santé reproductive et maternelle dans 57 pays. Ici, nous examinons certains des défis rencontrés, en utilisant les données EDS à cette fin, présentons la classification que nous avons utilisée pour les prestataires et fournissons des recommandations pour permettre des comparaisons plus détaillées et précises entre les pays sur la prestation des soins de santé. Méthodes Nous avons utilisé les plus récents relevés EDS entre 2000 et 2012; 57 pays avaient des données sur la planification familiale et les prestataires de soins d'accouchement et 47 pays avaient des données sur les soins prénatals. Chaque option de réponse possible dans les 57 pays a été répertoriée et classée. Nous avons ensuite développé une classification pour grouper les options de réponses des prestataires selon deux dimensions clés: la nature clinique et la recherche du profit. Résultats Nous avons classé les différents types de prestataires de soins de santé maternelle et reproductive, et les personnes qui fournissent des soins. Les défis documentées rencontrées durant ce processus étaient les limitations inhérentes aux données de l'enquête sur les ménages sur la base de l'auto-report des répondants, l'amalgame d'options de réponse dans le questionnaire ou à l’étape de traitement des données, les erreurs de catégories du lieu par rapport à la profession pour l'accouchement, l'incapacité à déterminer si les soins reçus à domicile étaient du secteur public ou privé, un grand nombre d'options de réponse négligeables, des incohérences dans le codage et l'analyse des ensembles de données, et l'utilisation de rubriques incompatibles. Conclusions Pour améliorer la clarté, nous recommandons de tacler les problèmes tels que l'amalgame d'options de réponses, les données sur les prestataires du public par rapport à ceux du privé, l'incohérence dans le codage et l'obtention de métadonnées. Plus de collecte systématique et standardisée des données aiderait les comparaisons internationales des progrès vers une meilleure protection financière et nous permettra de mieux caractériser les incitations et la nature commerciale des différents prestataires. Objetivo Las Encuestas Demográficas y de Salud (EDS) son una fuente de datos vitales para el análisis comparativo entre países. Este artículo es parte de un grupo de análisis que evalúan los tipos de proveedores de atención a la salud reproductiva y materna que están siendo utilizados en 57 países. Examinamos algunos de los retos encontrados al utilizar datos de EDS con este propósito, presentamos la clasificación de proveedores que hemos usado, y proveemos recomendaciones para permitir una comparación más detallada y más precisa de la prestación de servicios sanitarios en diferentes países. Métodos Hemos utilizado datos de las EDS más recientes, entre el 2000 y 2012; 57 países tenían datos sobre planeación familiar y proveedores de servicios durante el parto y 47 países tenían datos sobre cuidados prenatales. Cada opción posible de respuesta en los 57 países fue listada y categorizada. Después se desarrolló una clasificación para agrupar las opciones de respuesta según proveedor, siguiendo dos dimensiones clave: naturaleza clínica y afán de lucro. Resultados Hemos clasificado los diferentes tipos de proveedores de cuidados sanitarios en salud materna y reproductiva, y a los individuos que ofrecían los servicios. Los retos documentados durante este proceso fueron las limitaciones inherentes a los datos en las encuestas realizadas en los hogares basados en las auto-respuestas de los encuestados; fusión de las opciones de respuesta en el cuestionario o durante la etapa de procesamiento de datos; errores de categoría sobre el lugar versus profesional que atendió el parto; incapacidad para determinar si los cuidados recibidos en el hogar eran del sector público o privado; un gran número de opciones de respuesta insignificantes; inconsistencias en la codificación y el análisis del conjunto de datos; y uso de encabezamientos inconsistentes. Conclusiones Para mejorar la claridad, recomendamos abordar cuestiones tales como la fusión de opciones de respuesta, datos sobre el proveedor público versus privado, codificación inconsistente, y la obtención de metadatos. Una recolección de datos más sistemática y estandarizada facilitaría las comparaciones internacionales del progreso hacia una protección financiera mejorada, y nos permitiría una mejor caracterización de las iniciativas y de la naturaleza comercial de los diferentes proveedores.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Maternal, newborn, and child health and the Sustainable Development Goals--a call for sustained and improved measurement.

                Bookmark

                Author and article information

                Journal
                BMJ Glob Health
                BMJ Glob Health
                bmjgh
                bmjgh
                BMJ Global Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2059-7908
                2019
                24 June 2019
                : 4
                : Suppl 4 , Measurement of reproductive, maternal, newborn and child health and nutrition
                Affiliations
                [1 ] departmentDepartment of Disease Control , London School of Hygiene & Tropical Medicine , London, UK
                [2 ] departmentSick Kids , University of Toronto , Toronto, Ontario, Canada
                [3 ] Aga Khan University , Karachi, Pakistan
                [4 ] departmentInstitute for International Programs , Johns Hopkins Bloomberg School of Public Health , Baltimore, Maryland, USA
                [5 ] World Health Organization , Geneva, Switzerland
                [6 ] African Population and Health Research Centre , Nairobi, Kenya
                [7 ] departmentUNICEF , Health Section, Programme Division , New York City, New York, USA
                Author notes
                [Correspondence to ] Dr Tanya Marchant; Tanya.Marchant@ 123456lshtm.ac.uk
                Article
                bmjgh-2019-001512
                10.1136/bmjgh-2019-001512
                6590963
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

                Product
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
                Categories
                Editorial
                1506
                Custom metadata
                unlocked

                epidemiology, public health

                Comments

                Comment on this article