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      Effectiveness of mHealth interventions for maternal, newborn and child health in low– and middle–income countries: Systematic review and meta–analysis

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          Abstract

          Objective

          To assess the effectiveness of mHealth interventions for maternal, newborn and child health (MNCH) in low– and middle–income countries (LMIC).

          Methods

          16 online international databases were searched to identify studies evaluating the impact of mHealth interventions on MNCH outcomes in LMIC, between January 1990 and May 2014. Comparable studies were included in a random–effects meta–analysis.

          Findings

          Of 8593 unique references screened after de–duplication, 15 research articles and two conference abstracts met inclusion criteria, including 12 intervention and three observational studies. Only two studies were graded at low risk of bias. Only one study demonstrated an improvement in morbidity or mortality, specifically decreased risk of perinatal death in children of mothers who received SMS support during pregnancy, compared with routine prenatal care. Meta–analysis of three studies on infant feeding showed that prenatal interventions using SMS/cell phone (vs routine care) improved rates of breastfeeding (BF) within one hour after birth (odds ratio (OR) 2.01, 95% confidence interval (CI) 1.27–2.75, I 2 = 80.9%) and exclusive BF for three/four months (OR 1.88, 95% CI 1.26–2.50, I 2 = 52.8%) and for six months (OR 2.57, 95% CI 1.46–3.68, I 2 = 0.0%). Included studies encompassed interventions designed for health information delivery (n = 6); reminders (n = 3); communication (n = 2); data collection (n = 2); test result turnaround (n = 2); peer group support (n = 2) and psychological intervention (n = 1).

          Conclusions

          Most studies of mHealth for MNCH in LMIC are of poor methodological quality and few have evaluated impacts on patient outcomes. Improvements in intermediate outcomes have nevertheless been reported in many studies and there is modest evidence that interventions delivered via SMS messaging can improve infant feeding. Ambiguous descriptions of interventions and their mechanisms of impact present difficulties for interpretation and replication. Rigorous studies with potential to offer clearer evidence are underway.

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          Most cited references38

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement

          Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Terminology The terminology used to describe a systematic review and meta-analysis has evolved over time. One reason for changing the name from QUOROM to PRISMA was the desire to encompass both systematic reviews and meta-analyses. We have adopted the definitions used by the Cochrane Collaboration.9 A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review. Statistical methods (meta-analysis) may or may not be used to analyze and summarize the results of the included studies. Meta-analysis refers to the use of statistical techniques in a systematic review to integrate the results of included studies. Developing the PRISMA Statement A 3-day meeting was held in Ottawa, Canada, in June 2005 with 29 participants, including review authors, methodologists, clinicians, medical editors, and a consumer. The objective of the Ottawa meeting was to revise and expand the QUOROM checklist and flow diagram, as needed. The executive committee completed the following tasks, prior to the meeting: a systematic review of studies examining the quality of reporting of systematic reviews, and a comprehensive literature search to identify methodological and other articles that might inform the meeting, especially in relation to modifying checklist items. An international survey of review authors, consumers, and groups commissioning or using systematic reviews and meta-analyses was completed, including the International Network of Agencies for Health Technology Assessment (INAHTA) and the Guidelines International Network (GIN). The survey aimed to ascertain views of QUOROM, including the merits of the existing checklist items. The results of these activities were presented during the meeting and are summarized on the PRISMA Website. Only items deemed essential were retained or added to the checklist. Some additional items are nevertheless desirable, and review authors should include these, if relevant.10 For example, it is useful to indicate whether the systematic review is an update11 of a previous review, and to describe any changes in procedures from those described in the original protocol. Shortly after the meeting a draft of the PRISMA checklist was circulated to the group, including those invited to the meeting but unable to attend. A disposition file was created containing comments and revisions from each respondent, and the checklist was subsequently revised 11 times. The group approved the checklist, flow diagram, and this summary paper. Although no direct evidence was found to support retaining or adding some items, evidence from other domains was believed to be relevant. For example, Item 5 asks authors to provide registration information about the systematic review, including a registration number, if available. Although systematic review registration is not yet widely available,12,13 the participating journals of the International Committee of Medical Journal Editors (ICMJE)14 now require all clinical trials to be registered in an effort to increase transparency and accountability.15 Those aspects are also likely to benefit systematic reviewers, possibly reducing the risk of an excessive number of reviews addressing the same question16,17 and providing greater transparency when updating systematic reviews. The PRISMA Statement The PRISMA Statement consists of a 27-item checklist (Table 1; see also Text S1 for a downloadable template for researchers to re-use) and a 4-phase flow diagram (Figure 1; see also Figure S1 for a downloadable template for researchers to re-use). The aim of the PRISMA Statement is to help authors improve the reporting of systematic reviews and meta-analyses. We have focused on randomized trials, but PRISMA can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews. However, the PRISMA checklist is not a quality assessment instrument to gauge the quality of a systematic review. Box 1 Conceptual issues in the evolution from QUOROM to PRISMA Figure 1 Flow of information through the different phases of a systematic review Table 1 Checklist of items to include when reporting a systematic review or meta-analysis From QUOROM to PRISMA The new PRISMA checklist differs in several respects from the QUOROM checklist, and the substantive specific changes are highlighted in Table 2. Generally, the PRISMA checklist “decouples” several items present in the QUOROM checklist and, where applicable, several checklist items are linked to improve consistency across the systematic review report. Table 2 Substantive specific changes between the QUOROM checklist and the PRISMA checklist (a tick indicates the presence of the topic in QUOROM or PRISMA) The flow diagram has also been modified. Before including studies and providing reasons for excluding others, the review team must first search the literature. This search results in records. Once these records have been screened and eligibility criteria applied, a smaller number of articles will remain. The number of included articles might be smaller (or larger) than the number of studies, because articles may report on multiple studies and results from a particular study may be published in several articles. To capture this information, the PRISMA flow diagram now requests information on these phases of the review process. Endorsement The PRISMA Statement should replace the QUOROM Statement for those journals that have endorsed QUOROM. We hope that other journals will support PRISMA; they can do so by registering on the PRISMA Website. To underscore to authors, and others, the importance of transparent reporting of systematic reviews, we encourage supporting journals to reference the PRISMA Statement and include the PRISMA web address in their Instructions to Authors. We also invite editorial organizations to consider endorsing PRISMA and encourage authors to adhere to its principles. The PRISMA Explanation and Elaboration Paper In addition to the PRISMA Statement, a supporting Explanation and Elaboration document has been produced18 following the style used for other reporting guidelines.19-21 The process of completing this document included developing a large database of exemplars to highlight how best to report each checklist item, and identifying a comprehensive evidence base to support the inclusion of each checklist item. The Explanation and Elaboration document was completed after several face-to-face meetings and numerous iterations among several meeting participants, after which it was shared with the whole group for additional revisions and final approval. Finally, the group formed a dissemination subcommittee to help disseminate and implement PRISMA. Discussion The quality of reporting of systematic reviews is still not optimal.22-27 In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias,22 even though there is overwhelming evidence both for its existence28 and its impact on the results of systematic reviews.29 Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or interpreted it appropriately.30 Although the absence of reporting such an assessment does not necessarily indicate that it was not done, reporting an assessment of possible publication bias is likely to be a marker of the thoroughness of the conduct of the systematic review. Several approaches have been developed to conduct systematic reviews on a broader array of questions. For example, systematic reviews are now conducted to investigate cost-effectiveness,31 diagnostic32 or prognostic questions,33 genetic associations,34 and policy-making.35 The general concepts and topics covered by PRISMA are all relevant to any systematic review, not just those whose objective is to summarize the benefits and harms of a health care intervention. However, some modifications of the checklist items or flow diagram will be necessary in particular circumstances. For example, assessing the risk of bias is a key concept, but the items used to assess this in a diagnostic review are likely to focus on issues such as the spectrum of patients and the verification of disease status, which differ from reviews of interventions. The flow diagram will also need adjustments when reporting individual patient data meta-analysis.36 We have developed an explanatory document18 to increase the usefulness of PRISMA. For each checklist item, this document contains an example of good reporting, a rationale for its inclusion, and supporting evidence, including references, whenever possible. We believe this document will also serve as a useful resource for those teaching systematic review methodology. We encourage journals to include reference to the explanatory document in their Instructions to Authors. Like any evidence-based endeavour, PRISMA is a living document. To this end we invite readers to comment on the revised version, particularly the new checklist and flow diagram, through the PRISMA website. We will use such information to inform PRISMA's continued development. Note: To encourage dissemination of the PRISMA Statement, this article is freely accessible on the Open Medicine website and the PLoS Medicine website and is also published in the Annals of Internal Medicine, BMJ, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. For details on further use, see the PRISMA website. The PRISMA Explanation and Elaboration Paper is available at the PLoS Medicine website. Supporting Information Figure S1 Flow of information through the different phases of a systematic review (downloadable template document for researchers to re-use) Text S1 Checklist of items to include when reporting a systematic review or meta-analysis (downloadable template document for researchers to re-use)
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            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.
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              mHealth innovations as health system strengthening tools: 12 common applications and a visual framework

              The rapid proliferation of mHealth projects—albeit mainly pilot efforts—has generated considerable enthusiasm among governments, donors, and implementers of health programs. 1 In many instances, these pilot projects have demonstrated conceptually how mHealth can alleviate specific health system constraints that hinder effective coverage of health interventions. Large-scale implementation or integration of these mHealth innovations into health programs has been limited, however, by a shortage of empirical evidence supporting their value in terms of cost, performance, and health outcomes. 1 - 4 Governments in low- and middle-income countries face numerous challenges and competing priorities, impeding their ability to adopt innovations. 2 Thus, they need robust, credible evidence about mHealth projects in order to consider mHealth alongside essential health interventions, and guidance about which mHealth solutions they should consider to achieve broader health system goals. 2 Their tolerance for system instability or failure can be low, even when the status quo may be equally, or more, unreliable. Current larger-scale effectiveness and implementation research initiatives are working to address the evidence gaps and to demonstrate the impact of mHealth investments on health system targets. 1 Other efforts are underway to synthesize such findings. 5 MHEALTH AS A HEALTH SYSTEMS STRENGTHENING TOOL Recent mHealth reviews have proposed that innovators focus on the public health principles underlying mHealth initiatives, rather than on specific mHealth technologies. 6 International agencies and research organizations have also endeavored to frame mHealth interventions within the broader context of health system goals or health outcomes. 2 The term “health system” includes all activities in which the primary purpose is to promote, restore, or maintain health. 7 Some elements of a framework for evaluating health systems performance by relating the goals of the health system to its essential functions have been proposed previously, which we believe can serve as a model for articulating and justifying mHealth initiatives and investments. 7 Applying a health systems lens to the evaluation of mHealth initiatives requires different indicators and methodologies, shifting the assessment from whether the mHealth initiative “works” to process evaluation or proxy indicators of the health outcome(s) of interest. This new way of thinking would facilitate selection of mHealth tools that are appropriate for identified challenges. In other words, it would drive people to first identify the key obstacles, or constraints, to delivering proven health interventions effectively, and to then apply appropriate mHealth strategies that could overcome these health system constraints. 8 Presenting mHealth as a range of tools for overcoming known health system constraints, as a health systems “catalyst,” may also improve communication between mHealth innovators and health program implementers. Communicating mHealth technologies as tools that can enhance delivery of life-saving interventions through improvements in health systems performance, such as coverage, quality, equity, or efficiency, will resonate with health decision-makers. 7 Hence, rather than being perceived as siloed, stand-alone solutions, mHealth strategies should be viewed as integrable systems that should fit into existing health system functions and complement the health system goals of: health service provision; a well-performing health workforce; a functioning health information system; cost-effective use of medical products, vaccines, and technologies; and accountability and governance. 9 mHealth should be integrated into existing health system functions, rather than as stand-alone solutions. A SHARED FRAMEWORK TO EXPLAIN MHEALTH INNOVATIONS The absence of a shared language and approach to describe mHealth interventions will continue to hinder efforts to identify, catalog, and synthesize evidence across this complex landscape. The lack of a common framework also makes it hard to explain mHealth innovations to mainstream health-sector stakeholders. mHealth researchers and implementers at the World Health Organization (WHO), the Johns Hopkins University Global mHealth Initiative, the United Nations Children's Fund (UNICEF), and frog Design have jointly developed the “mHealth and ICT Framework” to describe mHealth innovations in the reproductive, maternal, newborn, and child health (RMNCH) field, in which mobile health technologies have been broadly implemented over the last decade across the developing world. The framework builds on prior efforts to describe types and uses of mHealth generally, such as in the WHO global survey on eHealth 2 and in the mHealth Alliance's typology for mHealth services in the maternal and newborn health field. 10 These previous efforts, however, have focused more explicitly on the type of actor (client, provider, or health system) and location of the mHealth activity (community, facility, or health information system). Some of these descriptions provide details about the use of specific mobile functions (such as toll-free help lines) to accomplish particular health goals, although other functions could have been used to accomplish the same goals and, over time, the functions described could be superseded by newer technologies. Furthermore, their classification approaches have not provided stakeholders with the tools to enable them to understand the diverse ways in which specific mobile functions could be employed for a particular health purpose. Our framework is constructed around standard health system goals and places intended users and beneficiaries in central focus, against the context of the proposed mHealth service package (Figure 1). By describing a specific mHealth strategy or approach, the framework visually depicts the when, for whom, what is being done to alleviate which constraints, and the how of the strategy. The framework comprises 2 key components: A place to depict the specifics of the mHealth intervention, described as one or more common mHealth or information and communications technology (ICT) applications used to target specific health system challenges or constraints within specific areas of the RMNCH continuum of care (Figure 1, upper section). A visual depiction of mHealth implementation through the concept of “touch points,” or points of contact, which describe the specific mHealth interactions across health system actors (for example, clients, providers), locations (such as clinics or hospitals), and timings of interactions and data exchange (Figure 1, lower section). Figure 1. The mHealth and ICT Framework for RMNCH Abbreviations: CHW, community health worker; ICT, information and communications technology; PMTCT, prevention of mother-to-child transmission of HIV; RMNCH, reproductive, maternal, newborn, and child health. 12 COMMON MHEALTH AND ICT APPLICATIONS The first part of the framework aims to address a previously identified challenge in mHealth: to systematically describe the constituent parts of an mHealth strategy or platform. 11 To do this, we define relationships between common applications of mHealth and ICT and the health systems constraints that they address. 2 , 12 - 13 Our list of 12 common mHealth applications has been vetted, through multiple iterations, by a wide group of mHealth stakeholders and thought leaders, ranging from academic researchers to program and policy implementers. Although a few mHealth projects deploy a single application, most comprise a package of 2 or more applications (Figure 2). In addition, mHealth projects employ 1 or more mobile phone functions—such as short message service (SMS), interactive voice response (IVR)—to accomplish the common applications (Table 1). Figure 2. Twelve Common mHealth and ICT Applications Table 1. Examples of Mobile Phone Functions Used in Common mHealth and ICT Applications Common mHealth and ICT Applications Examples of Mobile Phone Functions 1 Client education and behavior change communication (BCC) • Short Message Service (SMS) • Multimedia Messaging Service (MMS) • Interactive Voice Response (IVR) • Voice communication/Audio clips • Video clips • Images 2 Sensors and point-of-care diagnostics • Mobile phone camera • Tethered accessory sensors, devices • Built-in accelerometer 3 Registries and vital events tracking • Short Message Service (SMS) • Voice communication • Digital forms 4 Data collection and reporting • Short Message Service (SMS) • Digital forms • Voice communication 5 Electronic health records • Digital forms • Mobile web (WAP/GPRS) 6 Electronic decision support (information, protocols, algorithms, checklists) • Mobile web (WAP/GPRS) • Stored information “apps” • Interactive Voice Response (IVR) 7 Provider-to-provider communication (user groups, consultation) • Short Message Service (SMS) • Multimedia Messaging Service (MMS) • Mobile phone camera 8 Provider work planning and scheduling • Interactive electronic client lists • Short Message Service (SMS) alerts • Mobile phone calendar 9 Provider training and education • Short Message Service (SMS) • Multimedia Messaging Service (MMS) • Interactive Voice Response (IVR) • Voice communication • Audio or video clips, images 10 Human resource management • Web-based performance dashboards • Global Positioning Service (GPS) • Voice communication • Short Message Service (SMS) 11 Supply chain management • Web-based supply dashboards • Global Positioning Service (GPS) • Digital forms • Short Message Service (SMS) 12 Financial transactions and incentives • Mobile money transfers and banking services • Transfer of airtime minutes Abbreviations: GPRS, General Packet Radio Service; WAP, Wireless Application Protocol. 1. Client Education and Behavior Change Communication This series of mHealth strategies focuses largely on the client, offering a novel channel to deliver content intended to improve people's knowledge, modify their attitudes, and change their behavior. Targeted, timely health education and actionable health information—delivered through SMS, IVR, audio, and/or videos that engage 1 or more actors (such as a pregnant woman, a husband, family, community)—influences health behaviors, such as adherence to medication or use of health services. 3 , 14 The Mobile Alliance for Maternal Action (MAMA) is an example of an mHealth service package that provides gestational age-appropriate health information to pregnant women and new mothers on their family's mobile phone. 15 Most mHealth interventions in this category capitalize on people's ubiquitous access to mobile phones to increase their exposure to, and reinforce, health messages. In some instances, these types of interventions also enable clients to seek more information based on their interest in a particular message—for example, through a higher level of engagement with a call-center counselor. 4 Other mHealth interventions use mobile functions such as voice, video or audio clips, and images to enhance the effectiveness of in-person counseling, which is of particular value among low-literacy populations. Such examples include the BBC World Trust Mobile Kunji project 16 and Dimagi's CommCare Health Worker systems. 17 - 18 2. Sensors and Point-of-Care Diagnostics Harnessing the inherent computing power of mobile phones or linking mobile phones to a connected, but independent, external device can facilitate remote monitoring of clients, extending the reach of health facilities into the community and into clients' homes. Novel sensors and technologies are being developed to conduct, store, transmit, and evaluate diagnostic tests through mobile phones, from relatively simple tests, such as blood glucose measurements for diabetes management, to sophisticated assays, such as electrocardiograms (ECGs), in situations where the patient and provider are far removed from one another. These technologies also can store frequent longitudinal measures for later review during a patient-provider visit and monitor a patient's vital signs continuously and automatically, triggering a response when the device detects anomalous signals. Examples of such mHealth initiatives include the “ubiquitous health care” service in South Korea 19 that uses sensor technology to monitor patient health remotely and AliveCor, 20 a clinical grade, 2-lead ECG running on a mobile phone, recently approved by the U.S. Food and Drug Administration (FDA), that allows physicians to view and assess cardiac health at the point-of-care. These kinds of interventions are increasingly common in high-income settings but are less common in resource-limited contexts. New tests are being developed and evaluated to allow diagnostics to be conducted through mobile phones, from simple blood glucose tests to sophisticated electrocardiograms. 3. Registries and Vital Events Tracking Mobile phone-based registration systems facilitate the identification and enumeration of eligible clients for specific services, not only to increase accountability of programs for providing complete and timely care but also to understand and overcome disparities in health outcomes. 21 These are most often used for registering pregnancy and birth but also can be used for tracking individuals with specific health conditions, by age groups or other characteristics. Tracking vital events (births and deaths) supports the maintenance of population registries and determination of key development indicators, such as maternal and neonatal mortality. Such mobile registries issue and track unique identifiers and common indicators, link to electronic medical records, and enable longitudinal population information systems and health reporting. One such registry is the Mother and Child Tracking System (MCTS) in India 22 that registers pregnant women, using customized mobile phone-based applications, to help strengthen accountability for eligible clients to receive all scheduled health services (for example, 3–4 antenatal checkups, postnatal visits, and childhood vaccinations); both frontline health workers and their clients receive SMS reminders about scheduled services. Another example is UNICEF's birth registration system in Uganda, which uses RapidSMS to maintain a central electronic database of new births, updated using information transmitted via SMS, to overcome obstacles with the previously inefficient paper-based system. 23 - 24 4. Data Collection and Reporting Among the earliest global mHealth projects were those that allowed frontline workers and health systems to move from paper-based systems of ledgers, rosters, and aggregated reports to the near-instantaneous reporting of survey or patient data. Aggregation of information can occur at the server to analyze health system or disease statistics, by time, geographic area, or worker. In addition to optimizing the primary research or program monitoring and evaluation efforts of researchers, these types of mHealth initiatives reduce the turnaround time for reporting district-, local-, state-, or national-level data, which is useful for supervisors and policy makers. Countries such as Bangladesh, Rwanda, and Uganda are developing and enforcing national health information technology policies to improve the standardization and interoperability of public health data collection systems across government agencies and nongovernmental organizations (NGOs). Among the earliest mHealth projects were those that allowed collection of survey or patient data through mobile phones. Platforms commonly used to develop data collection systems include Open Data Kit (ODK) and FrontlineSMS. 25 - 26 The Formhub platform makes it easy for developers to use Microsoft Excel to create electronic forms, which can be deployed via Web forms or Android phones, with sophisticated server-side facilities for data aggregation, sharing, and visualization. 27 A large number of commercial systems exist for the range of mobile operating systems (iOS, Android, HTML5), and they often present user-friendly interfaces, such as Magpi, 28 that allow people to easily design mobile questionnaires. In Formhub and Magpi, forms can be shared with mobile data collectors and the data visualized in real time on a map, as the data are collected. National-level systems have also been developed for widespread use, such as the open-source District Health Information Software 2 (DHIS2) system, currently used in a number of countries for routine health collection and reporting. 29 In addition to being integrated into national health information systems, DHIS2 accepts data from authorized mobile devices and can allow management of data at the individual (such as district) or aggregate (national) levels. 29 5. Electronic Health Records Electronic health records (EHRs) used to be connected only to the facilities they served, allowing clinical staff to access patient records through fixed desktop computers. But the advent of mHealth has redefined the boundaries of the EHR; now, health workers can electronically register the services they provide and submit point-of-care test results through mHealth systems to update patient histories from the field. Rural health workers at the point-of-care (for example, in rural clinics or in the patient's home) can access and contribute to longitudinal health records, allowing continuity of care that was previously impossible in non-hospital-based settings. 30 Server-side algorithms to identify care gaps or trends in key indicators, such as weight loss or blood-glucose fluctuations, shift the onerous burden of identifying patterns and generating cues-to-action away from human reviewers. OpenMRS, a popular mHealth-enhanced EHR, allows frontline health workers to access information from a patient's health record using a mobile device and to contribute information into the health record—for example, about field-based tuberculosis (TB) treatment. 30 Other systems, such as RapidSMS or ChildCount+, might not be linked to a clinical file but still can maintain longitudinal client histories, such as antenatal care documentation, infant and child growth records, and digital vaccine records. 23 , 31 - 32 6. Electronic Decision Support: Information, Protocols, Algorithms, Checklists Ensuring providers' adherence to protocols is a paramount challenge to implementing complex care guidelines. In particular, shifting tasks, such as screening responsibilities, from clinicians to frontline health workers often entails adapting procedures designed for clinical workers to cadres with limited formal training. mHealth initiatives that incorporate point-of-care decision support tools with automated algorithm- or rule-based instructions help ensure quality of care in these task-shifting scenarios by prompting frontline health workers to follow defined guidelines. Point-of-care decision support tools through mobile phones can help ensure quality of care. Electronic decision support tools also can be used to identify and prioritize high-risk clients for health care, targeting interventions in resource-limited contexts. e-IMCI (electronic-Integrated Management of Childhood Illnesses), for example, provides community health workers with mobile phone-based, step-by-step support to triage and treat children according to WHO protocols for the diagnosis and treatment of common childhood diseases. 33 - 34 In addition, several groups are developing mobile phone-based checklists to help reduce clinical errors or to ensure quality of care at the point of service delivery. 35 7. Provider-to-Provider Communication: User Groups, Consultation Voice communication—one of the simplest technical functions of mobile phones—is among the most transformative applications in an mHealth service package, allowing providers to communicate with one another or across hierarchies of technical expertise. Once a key feature of telemedicine strategies, provider-to-provider communication by mobile phone can be used to coordinate care and provide expert assistance to health staff, when and where it is needed. Furthermore, communication is not limited to voice only; mobile phones allow the exchange of images or even sounds (for example, through digital auscultation, extending the reach of the traditional stethoscope) for immediate remote consultation. Providers can use simple voice communication through mobile phones to coordinate care and provide expert assistance. Current examples of provider-to-provider communication include the establishment of “Closed User Group” networks in Ghana, Liberia, and Tanzania by the NGO Switchboard, by which members of each mobile phone group can communicate with one another at heavily discounted rates, or for free. 36 - 37 In Nigeria, an mHealth feedback loop between rural clinics and diagnostic laboratories reduces the turnaround time between HIV testing and result reporting to facilitate prompt care and referral. 38 8. Provider Work Planning and Scheduling Work planning and scheduling tools help keep health care workers informed through active reminders of upcoming or due/overdue services, and they promote accountability by prioritizing provider follow-up. In low-resource settings, there often is a shortage of providers, making it a challenge to provide systematic population follow-up using traditional paper-based methods. mHealth systems can facilitate the scheduling of individuals listed in population registries (described in application number 3) for household-based outreach visits. Examples of this application include scheduling antenatal and postnatal care visits; alerting providers or supervisors about missed vaccinations or reduced adherence to medication regimens; and following up about medical procedures, such as circumcision or long-acting and permanent family planning methods. Provider work planning tools are common in many mHealth service packages, such as the scheduling functions of TxtAlert 39 and the MoTech “Mobile Midwife Service” that alerts nurses about clients who are due or overdue for care, to prevent missed appointments and delays in service provision. 40 9. Provider Training and Education Continuing medical education has been a mainstay of quality of care in high-income settings. Now, mobile devices are being used to provide continued training support to frontline and remote providers, through access to educational videos, informational messages, and interactive exercises that reinforce skills provided during in-person training. They also allow for continued clinical education and skills monitoring—for example, through quizzes and case-based learning. Applications for provider training include eMOCHA, 41 - 42 a platform that allows frontline health workers in rural Uganda to select streaming video content as part of continuing education. eMOCHA recently released “TB Detect,” a free application for Android devices in the Google Play Store, allowing providers to access continually updated educational content about tuberculosis prevention, detection, and care. 10. Human Resource Management Community health workers often work among rural populations, with only sporadic contact with supervisory staff. Web-based dashboards allow supervisors to track the performance of community health workers individually or at the district/regional/national level, either by noting the volume of digital productivity or by real-time GPS tracking of workers as they perform their field activities. This enables supportive supervision to those workers who may be lagging in their performance, while also enabling the recognition and reward of exceptional field staff. These approaches are embedded within a number of mHealth service packages, such as Rwanda's mUbuzima, which helps supervisors monitor community health worker performance and provide performance-based incentives, 43 - 44 and UNICEF's RapidSMS in Rwanda, which enables supervisors to monitor exchange of SMS messages between community health workers and a central server, thereby measuring service accountability and responsiveness of community health workers. 24 , 45 11. Supply Chain Management mHealth tools to track and manage stocks and supplies of essential commodities have received significant global attention. Relatively simple technologies that allow remote clinics or pharmacies to report daily stock levels of drugs and supplies, or to request additional materials electronically, have been implemented in a number of countries. Many countries use mHealth tools to track and manage stocks of health commodities. In Tanzania, at least 130 clinics are using the SMS for Life mHealth supply chain system to prevent stockouts of essential malaria drugs. 46 - 48 Pharmacists and other service providers are trained to send their district-level supervisors a structured text message at the end of each week to report stock levels of key commodities including anti-malarials. The supervisors can then take necessary actions to redistribute supplies, circumventing a potential crisis. In addition, a number of projects have developed mHealth strategies to reduce the risk of purchasing counterfeit drugs in countries where this is a major public health threat. 49 Companies such as Sproxil have partnered with drug manufacturers to provide mHealth authentication services to the purchasing public. 49 These strategies may help improve supply chain transparency and bolster a system's ability to be proactive and responsive to supply needs, with district or national-level visibility of performance. 12. Financial Transactions and Incentives mHealth and mFinance are converging rapidly in the domain of financial transactions to pay for health care, supplies, or drugs, or to make demand- or supply-side incentive schemes easier to deploy and scale. These strategies focus on decreasing financial barriers to care for clients, and they are testing novel ways of motivating providers to adhere to guidelines and/or provide higher quality care. Mobile financial transactions are becoming increasingly common. For example, a single African network operator, MTN, estimated having 7.3 million mobile money clients in mid-2012. 50 Thus, providing incentives to clients to use particular areas of health services will be increasingly attractive (for example, for institutional deliveries or vaccines, vouchers to subsidize health services, universal health insurance schemes, and mobile banking for access to resources for health services 51 ). Mobile-based cash vouchers have also been used where mobile money is not standard, as illustrated by the use of conditional cash transfers in Pakistan to provide families with an incentive to immunize their infants. 52 - 53 PLACING THE 12 APPLICATIONS WITHIN THE RMNCH FRAMEWORK One illustration of the application of component parts of our framework is the display of mHealth projects working within the RMNCH continuum to improve health systems functions. Specifically, the common mHealth applications capture the core uses of mobile technology and their contribution toward meeting health system needs. Health system challenges and constraints in the framework embrace and draw from concepts articulated in the WHO building blocks of health systems (service delivery, health workforce, health information systems, access to essential medicines, financing, and leadership/governance). 54 The framework's intended audience ranges from mHealth projects—to help locate their work within a broader context of mHealth in the RMNCH landscape—to stakeholders in government, implementation, or donor communities. In brief, the framework begins with the RMNCH continuum of care for women of reproductive age and their children to establish “when” during the reproductive life cycle the mHealth project will focus. 55 In other words, it identifies the beneficiary targets of the mHealth strategy, such as adolescents or pregnant women, as well as the intended users of the system, such as community health workers or district supervisors. Next, the framework identifies which RMNCH essential interventions (including preventive and curative care for improved maternal and child health outcomes) the mHealth approach will target, such as pregnancy registration or management of childhood illnesses. 56 - 57 This helps maintain focus on the needs of the health system and on the intervention that the mHealth approach is facilitating, 7 rather than on the technology being used. Rather than focus on technology, our new mHealth framework places emphasis on addressing health system needs. The common mHealth and ICT applications used by the project are indicated by horizontal, colored bars running across the RMNCH continuum of care, from adolescence to pregnancy and birth to childhood. The framework also incorporates space (to the right of the colored bars) to succinctly describe the specific health system constraints that the project is addressing (for example, “delayed reporting of events”). The framework includes categories of common health system challenges, such as information, availability, and cost. Finally, the “touch points” layer in the lower portion of the framework allows for mapping the mHealth-facilitated interactions among health system actors (for example, client, provider, manager, hospital, national health system). 58 See Figure 3 for an illustrative example of the fictional “Project Vaccinate.” Figure 3. Sample Application of the mHealth and ICT Framework for RMNCH Abbreviations: CHW, community health worker; ICT, information and communications technology; RMNCH, reproductive, maternal, newborn, and child health. The fictional “Project Vaccinate” is an mHealth system that integrates 5 of the 12 common mHealth applications to identify newborns and support families and community health workers in ensuring timely and complete vaccination. A detailed description of the components and use of the framework are beyond the scope of this commentary. In the near future, we will provide an updated framework and user guide as web-based, online tools that mHealth innovators and other stakeholders can use. Thus, the framework would serve to map and catalog mHealth service packages used across the RMNCH continuum, describing their work using a common language. As mHealth stakeholders begin to use this tool and employ this common language to describe their mHealth innovations, we expect to foster improved understanding between mHealth innovators and mainstream health system program and policy planners. This framework not only helps individual projects articulate their mHealth strategies through a shared tool but also facilitates identification of gaps in innovation, solutions, and implementation activity by overlaying multiple projects onto a single visualization. Any remaining blank spaces in the central area of the framework will signal areas of the continuum where future mHealth attention and investment may be warranted. This would also help identify common mHealth applications not yet utilized to target particular health system constraints. The new mHealth framework will help identify gaps in mHealth innovation. Ultimately, we hope these initial efforts at building consensus around a common taxonomy and framework will help overcome misgivings that mHealth innovations are the new “verticals” of this decade. Innovations in this space should be viewed not as independent, disconnected strategies but as vehicles to overcome persistent health system constraints. mHealth applications in this framework largely serve to catalyze the effective coverage of proven health interventions. Although shared frameworks are critical to communicating value, continued efforts to evaluate and generate evidence of mHealth impact are also necessary to sustain growth and mainstreaming of these solutions. These efforts should be complementary to improving the quality of deployments through end-user engagement, stakeholder inclusion, and designing for scale. 59
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                Author and article information

                Journal
                J Glob Health
                J Glob Health
                JGH
                Journal of Global Health
                Edinburgh University Global Health Society
                2047-2978
                2047-2986
                June 2016
                08 November 2015
                : 6
                : 1
                : 010401
                Affiliations
                [1 ]eHealth Research Group, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh, UK
                [2 ]Edinburgh Health Services Research Unit, Edinburgh, UK
                [3 ]Edinburgh Global Health Academy, The University of Edinburgh Medical School, Edinburgh, UK
                Author notes
                Correspondence to:
Dr. Claudia Pagliari
eHealth Research Group
Usher Institute of Population Health Sciences and Informatics
The University of Edinburgh Medical School
Teviot Place
Edinburgh EH8 9AG, UK
 claudia.pagliari@ 123456ed.ac.uk
                Article
                jogh-06-010401
                10.7189/jogh.06.010401
                4643860
                26649177
                b8ef562e-a9f0-429b-a683-77413e9ec2f5
                Copyright © 2016 by the Journal of Global Health. All rights reserved.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Public health

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