15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The role of a decision-support smartphone application in enhancing community health volunteers’ effectiveness to improve maternal and newborn outcomes in Nairobi, Kenya: quasi-experimental research protocol

      protocol

      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

          Improving maternal and newborn survival remains major aspirations for many countries in the Global South. Slum settlements, a result of rapid urbanisation in many developing countries including Kenya, exhibit high levels of maternal and neonatal mortality. There are limited referral mechanisms for sick neonates and their mothers from the community to healthcare facilities with ability to provide adequate care. In this study, we specifically plan to develop and assess the added value of having community health volunteers (CHVs) use smartphones to identify and track mothers and children in a bid to reduce pregnancy-related complications and newborn deaths in the urban slums of Kamukunji subcounty in Nairobi, Kenya.

          Methods and analysis

          This is a quasi-experimental study. We are implementing an innovative, mHealth application known as mobile Partnership for Maternal, Newborn and Child Health (mPAMANECH) which uses dynamic mobile phone and web-portal solutions to enable CHVs make timely decisions on the best course of action in their management of mothers and newborns at community level. The application is based on existing guidelines and protocols in use by CHVs. Currently, CHVs conduct weekly home visits and make decisions from memory or using unwieldy manual tools, and thus prone to making errors. mPAMANECH has an in-built algorithm that makes it easier, faster and more likely for CHVs to make the right management decision. We are working with a network of selected CHVs and maternity centres to pilot test the tool. To measure the impact of the intervention, baseline and end-line surveys will be conducted. Data will be obtained through qualitative and quantitative methods.

          Ethics and dissemination

          Ethical approval for the study was obtained from the African Medical Research Foundation. Key messages from the results will be packaged and disseminated through meetings, conference presentations, reports, fact sheets and academic publications to facilitate uptake by policy-makers.

          Related collections

          Most cited references32

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          Global causes of maternal death: a WHO systematic analysis.

          Data for the causes of maternal deaths are needed to inform policies to improve maternal health. We developed and analysed global, regional, and subregional estimates of the causes of maternal death during 2003-09, with a novel method, updating the previous WHO systematic review. We searched specialised and general bibliographic databases for articles published between between Jan 1, 2003, and Dec 31, 2012, for research data, with no language restrictions, and the WHO mortality database for vital registration data. On the basis of prespecified inclusion criteria, we analysed causes of maternal death from datasets. We aggregated country level estimates to report estimates of causes of death by Millennium Development Goal regions and worldwide, for main and subcauses of death categories with a Bayesian hierarchical model. We identified 23 eligible studies (published 2003-12). We included 417 datasets from 115 countries comprising 60 799 deaths in the analysis. About 73% (1 771 000 of 2 443 000) of all maternal deaths between 2003 and 2009 were due to direct obstetric causes and deaths due to indirect causes accounted for 27·5% (672 000, 95% UI 19·7-37·5) of all deaths. Haemorrhage accounted for 27·1% (661 000, 19·9-36·2), hypertensive disorders 14·0% (343 000, 11·1-17·4), and sepsis 10·7% (261 000, 5·9-18·6) of maternal deaths. The rest of deaths were due to abortion (7·9% [193 000], 4·7-13·2), embolism (3·2% [78 000], 1·8-5·5), and all other direct causes of death (9·6% [235 000], 6·5-14·3). Regional estimates varied substantially. Between 2003 and 2009, haemorrhage, hypertensive disorders, and sepsis were responsible for more than half of maternal deaths worldwide. More than a quarter of deaths were attributable to indirect causes. These analyses should inform the prioritisation of health policies, programmes, and funding to reduce maternal deaths at regional and global levels. Further efforts are needed to improve the availability and quality of data related to maternal mortality. © 2014 World Health Organization; licensee Elsevier. This is an Open Access article published without any waiver of WHO's privileges and immunities under international law, convention, or agreement. This article should not be reproduced for use in association with the promotion of commercial products, services, or any legal entity. There should be no suggestion that WHO endorses any specific organisation or products. The use of the WHO logo is not permitted. This notice should be preserved along with the article's original URL.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

            Developers of health care software have attributed improvements in patient care to these applications. As with any health care intervention, such claims require confirmation in clinical trials. To review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting benefit. We updated our earlier reviews by searching the MEDLINE, EMBASE, Cochrane Library, Inspec, and ISI databases and consulting reference lists through September 2004. Authors of 64 primary studies confirmed data or provided additional information. We included randomized and nonrandomized controlled trials that evaluated the effect of a CDSS compared with care provided without a CDSS on practitioner performance or patient outcomes. Teams of 2 reviewers independently abstracted data on methods, setting, CDSS and patient characteristics, and outcomes. One hundred studies met our inclusion criteria. The number and methodologic quality of studies improved over time. The CDSS improved practitioner performance in 62 (64%) of the 97 studies assessing this outcome, including 4 (40%) of 10 diagnostic systems, 16 (76%) of 21 reminder systems, 23 (62%) of 37 disease management systems, and 19 (66%) of 29 drug-dosing or prescribing systems. Fifty-two trials assessed 1 or more patient outcomes, of which 7 trials (13%) reported improvements. Improved practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system (success in 73% of trials vs 47%; P = .02) and studies in which the authors also developed the CDSS software compared with studies in which the authors were not the developers (74% success vs 28%; respectively, P = .001). Many CDSSs improve practitioner performance. To date, the effects on patient outcomes remain understudied and, when studied, inconsistent.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000.

              Information about the distribution of causes of and time trends for child mortality should be periodically updated. We report the latest estimates of causes of child mortality in 2010 with time trends since 2000. Updated total numbers of deaths in children aged 0-27 days and 1-59 months were applied to the corresponding country-specific distribution of deaths by cause. We did the following to derive the number of deaths in children aged 1-59 months: we used vital registration data for countries with an adequate vital registration system; we applied a multinomial logistic regression model to vital registration data for low-mortality countries without adequate vital registration; we used a similar multinomial logistic regression with verbal autopsy data for high-mortality countries; for India and China, we developed national models. We aggregated country results to generate regional and global estimates. Of 7·6 million deaths in children younger than 5 years in 2010, 64·0% (4·879 million) were attributable to infectious causes and 40·3% (3·072 million) occurred in neonates. Preterm birth complications (14·1%; 1·078 million, uncertainty range [UR] 0·916-1·325), intrapartum-related complications (9·4%; 0·717 million, 0·610-0·876), and sepsis or meningitis (5·2%; 0·393 million, 0·252-0·552) were the leading causes of neonatal death. In older children, pneumonia (14·1%; 1·071 million, 0·977-1·176), diarrhoea (9·9%; 0·751 million, 0·538-1·031), and malaria (7·4%; 0·564 million, 0·432-0·709) claimed the most lives. Despite tremendous efforts to identify relevant data, the causes of only 2·7% (0·205 million) of deaths in children younger than 5 years were medically certified in 2010. Between 2000 and 2010, the global burden of deaths in children younger than 5 years decreased by 2 million, of which pneumonia, measles, and diarrhoea contributed the most to the overall reduction (0·451 million [0·339-0·547], 0·363 million [0·283-0·419], and 0·359 million [0·215-0·476], respectively). However, only tetanus, measles, AIDS, and malaria (in Africa) decreased at an annual rate sufficient to attain the Millennium Development Goal 4. Child survival strategies should direct resources toward the leading causes of child mortality, with attention focusing on infectious and neonatal causes. More rapid decreases from 2010-15 will need accelerated reduction for the most common causes of death, notably pneumonia and preterm birth complications. Continued efforts to gather high-quality data and enhance estimation methods are essential for the improvement of future estimates. The Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
                Bookmark

                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2017
                20 July 2017
                : 7
                : 7
                : e014896
                Affiliations
                [1] departmentHealth Challenges and Systems Research Program , African Population and Health Research Center , Nairobi, Kenya
                Author notes
                [Correspondence to ] Dr Pauline Bakibinga; paulabak80@ 123456gmail.com
                Article
                bmjopen-2016-014896
                10.1136/bmjopen-2016-014896
                5642658
                28729309
                a2fdab76-b6df-4af8-919c-66ba9c2c4ace
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 25 October 2016
                : 05 May 2017
                : 19 May 2017
                Categories
                Health Services Research
                Protocol
                1506
                1704
                Custom metadata
                unlocked

                Medicine
                decision-support,community health volunteers,maternal and newborn health,slums,kenya
                Medicine
                decision-support, community health volunteers, maternal and newborn health, slums, kenya

                Comments

                Comment on this article