The Helping Babies Survive (HBS) initiative features a suite of evidence-based curricula and simulation-based training programs designed to provide health workers in low- and middle-income countries (LMICs) with the knowledge, skills, and competencies to prevent, recognize, and manage leading causes of newborn morbidity and mortality. Global scale-up of HBS initiatives has been rapid. As HBS initiatives rolled out across LMIC settings, numerous bottlenecks, gaps, and barriers to the effective, consistent dissemination and implementation of the programs, across both the pre- and in-service continuums, emerged. Within the first decade of expansive scale-up of HBS programs, mobile phone ownership and access to cellular networks have also concomitantly surged in LMICs. In this article, we describe a number of HBS digital health innovations and resources that have been developed from 2010 to 2020 to support education and training, data collection for monitoring and evaluation, clinical decision support, and quality improvement. Helping Babies Survive partners and stakeholders can potentially integrate the described digital tools with HBS dissemination and implementation efforts in a myriad of ways to support low-dose high-frequency skills practice, in-person refresher courses, continuing medical and nursing education, on-the-job training, or peer-to-peer learning, and strengthen data collection for key newborn care and quality improvement indicators and outcomes. Thoughtful integration of purpose-built digital health tools, innovations, and resources may assist HBS practitioners to more effectively disseminate and implement newborn care programs in LMICs, and facilitate progress toward the achievement of Sustainable Development Goal health goals, targets, and objectives.

The Helping Babies Survive (HBS) initiative features a suite of evidence-based curricula and simulation-based training programs designed to provide health workers in low- and middle-income countries (LMICs) with the knowledge, skills, and competencies to prevent, recognize, and manage leading causes of newborn morbidity and mortality. HBS was built on the success of its flagship program, Helping Babies Breathe (HBB), a global initiative launched in 2010 to educate and train LMIC health care providers (HCPs) in knowledge, skills, and competencies for basic neonatal resuscitation.14  In addition to HBB, HBS includes Essential Care for Every Baby (ECEB),5  essential newborn care from birth through 24 hours postnatal,6,7  and Essential Care for Small Babies (ECSB),8  essential care for the small well infant.9 

The scale-up of HBS programs has been explosive; during the initial 5 years after the global launch, HBB was disseminated in >80 countries, many at a national scale.10  As HBS initiatives rolled out across LMIC settings, numerous bottlenecks, gaps, and barriers to the effective, consistent dissemination and implementation of the programs emerged. These educational, data collection, and quality improvement (QI) challenges were detected across both the pre- and in-service continuums and emerged at multiple points throughout the HBS training cascade, including before, during, and after training.1113  For example, although HBS training is successful at initially improving knowledge, skills, and competencies among HCPs,14  HBB 1-day training courses, on their own, are often insufficient in leading to sustained translation of knowledge and skills into clinical practice.15  Also, even when knowledge and skills are robustly acquired initially, if not supported by subsequent in-person refresher courses,16  peer learning, or low-dose high-frequency training,17  competencies rapidly decay over time.18,19 

Another key challenge that emerged, as HBS programs rapidly scaled, was reliance on paper-based methods for data collection and reporting. As compared to digitized data collection systems, paper-based efforts are often plagued by a higher rate of data entry errors and are difficult to search.20  Thus, although paper-based systems can be easy to use for initial data collection, this can create bottlenecks in the subsequent collation and extraction of crucial information, which, in turn, can then impede integrated and timely documentation efforts, underlie time lags in reporting, and hamper effective monitoring, evaluation, and QI efforts.21,22  Thoughtfully designed digital health interventions may help to ameliorate educational and training gaps, barriers, and bottlenecks identified within the HBS dissemination and implementation cascade or that are created by reliance on paper-based data collection systems.2327 

Within the first decade of expansive scale-up of HBS programs, mobile phone ownership and access to cellular networks has concomitantly surged in LMICs.2831  In 2018, there were 5.135 billion mobile phone users, and two-thirds of the world’s population of 7.6 billion people owned a mobile phone; half of these devices were “smart” (ie, enabled with Internet access, data storage, and other computing capabilities). Globally, Internet penetration also continues to rise, with an estimated 53% of global citizens (4.021 billion) with access in 2018.32  Acceptance of, and access to, a wide variety of digital health interventions has also skyrocketed, among a wide range of stakeholders, including HCPs.3338  Implementation of mobile health and digital tools in LMICs has been demonstrated to have numerous benefits, including improving access to care for patients,39,40  increasing knowledge retention and competencies among community health workers,41,42  and improving training outcomes, confidence and satisfaction, and reporting of key indicators among health providers.35,4346 

Over the past decade, a number of digital resources and innovations have been developed to augment HBS initiatives. Below, we describe some of these. This article does not serve as an exhaustive systematic review of all digital tools or educational repositories that have been reported during 2010–2020. Rather, the interventions selected have been designed and developed in collaboration with partners of the former Survive and Thrive Global Development Alliance (2012–2017),47  and as such, have received significant input from a broad coalition of local, national, and international stakeholders for specific alignment with evidence-based HBS curriculum and training content. The featured digital resources and innovations are organized according to their primary function(s). Broadly, we describe HBS digital innovations that support (1) education and training, (2) data collection for monitoring and evaluation, (3) clinical decision support, and (4) QI. Some of the innovations described in this article have multiple, overlapping functions (Table 1). Additional digital health tools of potential interest to HBS practitioners are shown in Table 2.

TABLE 1

Digital Tools To Support HBS Programs

Digital ToolDeveloperBrief DescriptionHBS ContentFunctionsWeb Site
GHMP Video Repository GHMP Live-action videos of evidence-based practices with patients and HCPs in clinical settings in LMICs HBB, ECEB, ESCB Education and training https://globalhealthmedia.org/ 
AIIMS ECEB app AIIMS Digital reference for ECEB curriculum with scenarios for role playing and evaluation of knowledge through case exercises ECEB Education and training; clinical decision support https://play.google.com/store/apps/details?id=com.eceb 
AIIMS ECSB app AIIMS Digital reference for ECSB curriculum with scenarios for role playing and evaluation of knowledge through case exercises ECSB Education and training; clinical decision support https://play.google.com/store/apps/details?id=com.ecsb 
LIFE (VR and mobile) KEMRI Oxford University Mobile VR simulation for neonatal resuscitation HBB Education and training https://play.google.com/store/apps/details?id=uk.ac.ox.NDM.LIFE 
eHBB VR and eHBB mobile apps University of Washington and Oxford LIFE team Mobile VR simulation for neonatal resuscitation HBB Education and training https://play.google.com/store/search?q=ehbb 
Liveborn Laerdal Global Health, UNC SOM Audit-feedback app for observer documentation of timing of resuscitation actions; gives automated feedback that is based on the HBB algorithm HBB Data collection for monitoring and evaluation; QI https://play.google.com/store/apps/details?id=com.laerdalglobalhealth.neobeatbirthregistration.newborn_ventilation_tool 
mHBS-DHIS272,91,92,94: Trainer module Indiana University School of Medicine, IUPUI School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital Digitalized curricula, such as the provider’s guide; access to educational and VR training videos (ie, eHBB); linkage to partner Web sites HBB, ECEB, ECSB Education and training https://github.com/iupui-soic/mHBS_tracker 
mHBS-DHIS271,73–75,93,94: Tracker module Indiana University School of Medicine, IUPUI School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital Digitized knowledge checks, BMV and OSCE skills checklists, and QI tools such as delivery observation checklist, and perinatal death audit; linkage to partner apps (eg, AIIMS, Safe Delivery, eHBB) HBB, ECEB, ECSB Data collection for monitoring and evaluation; QI https://github.com/iupui-soic/dhis2-android-trackercapture 
mHBS-DHIS29597 : ECEB Digital Action Plan app Indiana University School of Medicine, IUPUI School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital Support tool to track multiple infants with automated advice for management ECEB Clinical decision support — 
Digital ToolDeveloperBrief DescriptionHBS ContentFunctionsWeb Site
GHMP Video Repository GHMP Live-action videos of evidence-based practices with patients and HCPs in clinical settings in LMICs HBB, ECEB, ESCB Education and training https://globalhealthmedia.org/ 
AIIMS ECEB app AIIMS Digital reference for ECEB curriculum with scenarios for role playing and evaluation of knowledge through case exercises ECEB Education and training; clinical decision support https://play.google.com/store/apps/details?id=com.eceb 
AIIMS ECSB app AIIMS Digital reference for ECSB curriculum with scenarios for role playing and evaluation of knowledge through case exercises ECSB Education and training; clinical decision support https://play.google.com/store/apps/details?id=com.ecsb 
LIFE (VR and mobile) KEMRI Oxford University Mobile VR simulation for neonatal resuscitation HBB Education and training https://play.google.com/store/apps/details?id=uk.ac.ox.NDM.LIFE 
eHBB VR and eHBB mobile apps University of Washington and Oxford LIFE team Mobile VR simulation for neonatal resuscitation HBB Education and training https://play.google.com/store/search?q=ehbb 
Liveborn Laerdal Global Health, UNC SOM Audit-feedback app for observer documentation of timing of resuscitation actions; gives automated feedback that is based on the HBB algorithm HBB Data collection for monitoring and evaluation; QI https://play.google.com/store/apps/details?id=com.laerdalglobalhealth.neobeatbirthregistration.newborn_ventilation_tool 
mHBS-DHIS272,91,92,94: Trainer module Indiana University School of Medicine, IUPUI School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital Digitalized curricula, such as the provider’s guide; access to educational and VR training videos (ie, eHBB); linkage to partner Web sites HBB, ECEB, ECSB Education and training https://github.com/iupui-soic/mHBS_tracker 
mHBS-DHIS271,73–75,93,94: Tracker module Indiana University School of Medicine, IUPUI School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital Digitized knowledge checks, BMV and OSCE skills checklists, and QI tools such as delivery observation checklist, and perinatal death audit; linkage to partner apps (eg, AIIMS, Safe Delivery, eHBB) HBB, ECEB, ECSB Data collection for monitoring and evaluation; QI https://github.com/iupui-soic/dhis2-android-trackercapture 
mHBS-DHIS29597 : ECEB Digital Action Plan app Indiana University School of Medicine, IUPUI School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital Support tool to track multiple infants with automated advice for management ECEB Clinical decision support — 

BMV, bag mask ventilation; IUPUI, Indiana University–Purdue University Indianapolis; KEMRI, Kenya Medical Research Institute; —, not applicable.

TABLE 2

Additional Digital Health Innovations of Potential Interest to HBS Practitioners

Delivery room timer 
 In conjunction with a large global implementation trial of HBB in Kenya and India,3,4,116  Somannavar et al117  developed and tested a voice-activated mobile phone–based timer to be used during deliveries for capture of time elapsed between birth and beginning of bag mask ventilation efforts in non-crying infants. 
HBB Prompt 
 Investigators from North America and Uganda are currently designing, developing, and performing feasibility testing in Uganda for an app, HBB Prompt, to improve retention of HBB skills and competencies.104  
NeoTree 
 This is an mHealth tool that integrates educational, data collection, and neonatal care decision support functions to improve the quality of care provided to newborns in LMICs. The content is aligned with HBS curricula. Usability testing was conducted in Malawi.118  
Safe Delivery app 
 The Safe Delivery app is a digital health tool used to support acquisition of knowledge and skills for basic emergency obstetric and neonatal care; the guidelines for neonatal resuscitation align with recommendations found in HBB, second edition. Recommendations for labor, delivery, and postpartum care harmonize with those found in the Helping Mothers Survive curricula.4345  
Telehealth 
 Increasingly, Telehealth is being used for telementoring to foster north-south and south-south educational and training relationships and to support virtual learning within neonatal resuscitation training programs,119  including HBB.120  
Delivery room timer 
 In conjunction with a large global implementation trial of HBB in Kenya and India,3,4,116  Somannavar et al117  developed and tested a voice-activated mobile phone–based timer to be used during deliveries for capture of time elapsed between birth and beginning of bag mask ventilation efforts in non-crying infants. 
HBB Prompt 
 Investigators from North America and Uganda are currently designing, developing, and performing feasibility testing in Uganda for an app, HBB Prompt, to improve retention of HBB skills and competencies.104  
NeoTree 
 This is an mHealth tool that integrates educational, data collection, and neonatal care decision support functions to improve the quality of care provided to newborns in LMICs. The content is aligned with HBS curricula. Usability testing was conducted in Malawi.118  
Safe Delivery app 
 The Safe Delivery app is a digital health tool used to support acquisition of knowledge and skills for basic emergency obstetric and neonatal care; the guidelines for neonatal resuscitation align with recommendations found in HBB, second edition. Recommendations for labor, delivery, and postpartum care harmonize with those found in the Helping Mothers Survive curricula.4345  
Telehealth 
 Increasingly, Telehealth is being used for telementoring to foster north-south and south-south educational and training relationships and to support virtual learning within neonatal resuscitation training programs,119  including HBB.120  

Global Health Media Project (GHMP) is a US-based nonprofit founded in 2010 that has created a large digital repository of live-action videos to help health workers and caregivers in low-resource settings obtain information and skills that can improve health care and health outcomes.48  The media are designed to be basic, practical, and reliable. The content is distilled from current international guidelines, and scripts and videos are rigorously reviewed by global content experts with extensive experience in low-resource settings. The videos are shot with in-service frontline health workers, exhibiting best practices with patients in actual LMIC clinical settings.

The videos, which are accessible across various modalities, demonstrate kind and respectful behavior and are carefully crafted to draw a trainee’s eyes and ears to all the subtleties that lead to good knowledge acquisition. Voice-over makes it easy to narrate the films in multiple languages. Using real HCPs who role model best practices for delivery of evidence-based health care aligns with adult-learning principles for the development of competencies through self-directed learning.49,50 

GHMP has created 150 videos that are focused on maternal, newborn, and child health. For HBS, there are 4 videos with live footage to complement HBB and 30 videos closely aligned with ECEB, covering newborn care skills, problems, and breastfeeding.51  To support ECSB content, 27 videos are available.52  GHMP videos have been watched in nearly every country in the world and streamed online >430 million times. Available in >40 languages, they have been downloaded by >7500 organizations. Recently, GHMP released the Birth & Beyond app, available on iOS; it allows 1-click access to their 28 videos that have been designed specifically for mothers and caregivers and are available in 21 languages.

Developed by collaborators at the All India Institute of Medical Sciences (AIIMS), the Helping Babies Survive–Essential Newborn Care (HBS-ENC) and Helping Babies Survive–Essential Care for Small Babies (HBS-ECSB) apps are available on Google Play and iOS; the Android versions of HBS-ENC and HBS-ECSB have been downloaded >5000 and 1000 times, respectively. Both apps are aligned with existing versions of the American Academy of Pediatrics’ (AAP) ECEB and ECSB programs. They support acquisition of knowledge among HCPs in regard to immediate care of the newborn after birth and during the first day (HBS-ENC) and for well small infants (HBS-ECSB).

The HBS-ENC can be paired with the ECEB curriculum as a ready digital reference for the action plan, which highlights key steps in essential care and classification of the newborn. (Fig 1). The app also has case exercises for paired practice by health care workers that combine several actions with an objective to harness skills for each component of the action plan.

FIGURE 1

AIIMS HBS-ECEB Android app (reproduced with the permission from A.D.). Screenshots from the AIIMS HBS-ECEB Android app demonstrating the classify-the-infant function.

FIGURE 1

AIIMS HBS-ECEB Android app (reproduced with the permission from A.D.). Screenshots from the AIIMS HBS-ECEB Android app demonstrating the classify-the-infant function.

Close modal

The HBS-ECSB app is structured similar to the HBS-ENC app, but the content is based on the ECSB program (Fig 2).8  In addition to offering opportunities for self-directed learning to serve as memory aides and tips for facility-based QI, both apps also link to educational videos that are offered by a variety of newborn care partners, including GHMP. HCPs may use the apps as preparation for and during an initial training workshop, as well as after the completion of the course for self-directed knowledge refresher training and as point-of-care tools at the bedside. The apps guide activities that help providers maintain and improve knowledge and skills through review and practice. In addition, both apps also incorporate QI functions.

FIGURE 2

AIIMS HBS-ECEB IOS app (reproduced with the permission from A.D.). Screenshots from the AIIMS HBS-ECEB iOS app: home screen, tabs to navigate through content, “Essential care for every baby,” and prevention of disease.

FIGURE 2

AIIMS HBS-ECEB IOS app (reproduced with the permission from A.D.). Screenshots from the AIIMS HBS-ECEB iOS app: home screen, tabs to navigate through content, “Essential care for every baby,” and prevention of disease.

Close modal

In high-income countries, computer-based training simulations such as HeartCode Pediatric Advanced Life Support and the Neonatal Resuscitation Program eSIM programs complement in-person courses.53,54  Although these software programs require a high-speed Internet connection and a personal computer with sufficient graphics capabilities, mobile virtual simulations, such as Life-Saving Instruction for Emergencies (LIFE) (mobile) and the electronic Helping Babies Breathe (eHBB) program (see descriptions below), can be delivered off-line on mobile phones as screen-based experiences transformed into immersive experiences with the use of a low-cost virtual reality (VR) headset.54  Game-based learning creates interconnections between the off-line identity, the game scenarios, and the actual interactions with and within the virtual simulation, allowing the learner to demonstrate skills and modify behaviors that relate to clinical practice.5557 

“Serious games” are electronic games or apps that are deliberatively designed for learning as well as entertainment. Through integration of simulations, virtual environments, and mixed reality and media, they provide educational and training opportunities through storytelling, narratives, and game-play encounters.58  There is evidence that serious-game simulations result in a 20% higher post-training self-efficacy, 11% higher declarative knowledge, 14% higher procedural knowledge, and 9% higher retention.59  Serious games and virtual simulations are increasingly being used to augment traditional methods of neonatal resuscitation training and have particular potential to augment simulation-based medical and nursing education.53,54,60,61  Mobile VR simulations can be used to demonstrate real-world phenomena, illustrate abstract concepts, and motivate learners.62  In a national survey of 161 pediatric health care workers in Nigeria, nearly all respondents (98% physicians [n = 92] and 96% of nurses [n = 52]) would recommend the use of online simulation for their center.63 

LIFE is a platform that was developed in a partnership between researchers in Kenya and the United Kingdom.64,65  It hosts mobile and VR training scenarios that help health workers to learn the steps they need to manage medical emergencies. The LIFE platform employs the concept of serious games to deliver training in a virtual environment that follows highly structured care pathways (or algorithms; Fig 3).

FIGURE 3

LIFE screenshots (reproduced with permission from Dr Chris Paton, Oxford University). Screenshots from the LIFE VR serious gaming platform reveal interactive learning and labor and delivery room screens.

FIGURE 3

LIFE screenshots (reproduced with permission from Dr Chris Paton, Oxford University). Screenshots from the LIFE VR serious gaming platform reveal interactive learning and labor and delivery room screens.

Close modal

The LIFE platform is intended to serve as a tool for neonatal resuscitation refresher training to prevent the documented decay in knowledge and skills that occur after initial skills acquisition.66  When subsequent face-to-face training courses are not accessible, LIFE offers realistic simulation training via VR headsets or mobile phones. The scenarios hosted in the LIFE app, available on Google Play67  and iOS, are based on the Emergency Triage, Assessment and Treatment plus admission care program (ETAT+).68  More than 5000 African health workers have received ETAT+ training. The initial steps of ETAT+ basic neonatal resuscitation training are closely aligned with those of HBB; also similar to HBB, ETAT+ training among health workers is associated with reduced child mortality at facilities where it is implemented.69 

LIFE (mobile) is a highly interactive three-dimensional mobile game, currently being rolled out nationwide in Kenya, in collaboration with the Kenya Pediatric Association. Using LIFE (mobile), health workers can access neonatal resuscitation training modules off-line via their smartphones whenever desired. To incentivize health workers to keep using the app, LIFE has partnered with the Kenya Pediatric Association to offer Continuing Professional Development points to providers using the platform. Additional training modules are being developed, and user design and evaluation research is currently being conducted.70 

eHBB VR and mobile applications feature 3 simulations that are based on the HBB curriculum (second edition) in which a newborn may require only routine care, some resuscitation, or resuscitation with positive-pressure ventilation (Fig 4). eHBB VR is designed primarily to work on low-cost mobile VR viewers such as Google Cardboard. The focus of the activity is to have the user “show” what they would do for the infant by interacting with the three-dimensional objects in the simulation and making selections by pressing a button-lever mechanism on the outside of the headset or by touching the screen. eHBB is designed to complement in-person classes, promote individualized learning, and provide standardized feedback that is based on the HBB Action Plan.

FIGURE 4

eHBB screenshots (reproduced with permission from R.U.). A, eHBB mobile screen-based simulation. B, eHBB mobile VR simulation.

FIGURE 4

eHBB screenshots (reproduced with permission from R.U.). A, eHBB mobile screen-based simulation. B, eHBB mobile VR simulation.

Close modal

To develop eHBB, the eHBB research team, led by the University of Washington, worked with the Oxford LIFE team to codesign scenarios with stakeholders representing a range of technical and clinical experience in Nigeria and Kenya. The working group used an agile, iterative codesign and testing approach to create VR scenario storyboards, identify game actions and animations, specify user prompts, and create individualized feedback. Internal testing during development was performed by the project team at several international sites: University of Washington, Seattle, Washington; Indiana University, Indianapolis, Indiana; National Hospital Abuja, Abuja, Nigeria; and the Kenya Medical Research Institute, Nairobi, Kenya. User feedback was also obtained during demonstrations at several national and international meetings. Collaborating institutions for pilot testing were the University of Lagos (Nigeria) and Alupe University College (Busia, Kenya). Mobile eHBB VR training for retention of neonatal resuscitation knowledge and skills is being field tested in a randomized controlled trial among nurses and midwives in Nigeria and Kenya.

The mobile Helping Babies Survive powered by District Health Information System 2 app (mHBS-DHIS2) is an integrated suite of open-source digital health tools to equip HCPs with one-stop access to, and linkage of, key resources and functions that are of particular importance to them in their educational, training, and clinical service trajectories.7175  mHBS-DHIS2 supports off-line mobile phone- and tablet-based data collection, education and training, reporting, and QI functions, as well as Web-based data visualization and dashboards via individually owned or shared (facility-based) Android devices. Built within the District Health Information System 2 platform,76  which is currently used in >60 countries, including by many ministries of health that have also integrated HBB at the national level,7781  mHBS-DHIS2 is extremely flexible and customizable; it is purpose designed for rapid scale-up and sustainability within the global regions where neonatal mortality is the highest,82,83  where HBS programs have scaled, and where partners are focused on achieving Sustainable Development Goals.19,79,8489 

The methods used to develop the mHBS-DHIS2 app included a human-centered design approach in conjunction with agile, iterative development processes, heuristic evaluation,90  and extensive usability testing, in conjunction with international partners.91  All mHBS-DHIS2 innovations are open source, and code is available on GitHub.92,93  The mHBS-DHIS2 privacy policy is compliant with the General Data Protection Regulation (2016/679).

The mHBS-DHIS2 app is composed of a suite of integrated digital modules (trainer and tracker). It is accessed via a single, customizable log-on screen using an assigned or self-selected username, pin code, or other credential. After logging on, users toggle seamlessly between self-directed learning (mHBS-DHIS2 trainer module) and data collection and reporting or QI functions (mHBS-DHSIS2 tracker module). Customized, permission-based access allows various types and levels of users (eg, country champions, district managers, HBS master trainers or providers) to enroll and track participating health facilities and HBS trainees or providers according to geographic location (country, province, district), level of health facility, and the HBS program in which a health worker is participating (Fig 5A).93 

FIGURE 5

Screenshots of the mHBS-DHIS2 tracker (version 1.0.1, build 653). A, Enrollment of new participants can be customized by geographic location, facility, and type of HBS program. B, Digitized data collection forms enable mobile devices to be used for monitoring, evaluating, and reporting of HBS educational and training outcomes; OSCE B is shown. C, Providers can self-report information that may be useful for QI initiatives; the delivery observation checklist is shown. Screenshots were reproduced with permission from S.L.B. BMV, bag mask ventilation.

FIGURE 5

Screenshots of the mHBS-DHIS2 tracker (version 1.0.1, build 653). A, Enrollment of new participants can be customized by geographic location, facility, and type of HBS program. B, Digitized data collection forms enable mobile devices to be used for monitoring, evaluating, and reporting of HBS educational and training outcomes; OSCE B is shown. C, Providers can self-report information that may be useful for QI initiatives; the delivery observation checklist is shown. Screenshots were reproduced with permission from S.L.B. BMV, bag mask ventilation.

Close modal

The mHBS-DHIS2 trainer module91  provides linkage to digital and Web-based educational, training, and implementation partner resources (eg, AAP HBS site), educational videos, and easily navigable digitized HBB second edition materials, including the action plan and provider’s guide. Android-based partner apps (eg, AIIMS apps, eHBB, Safe Delivery43 ) and online toolkits (eg, PATH) are seamlessly integrated with and accessible via the trainer module (Fig 6 A–D). In addition to using the mHBS-DHIS2 app for educational and training functions, end users can easily and effectively capture a wide variety of key monitoring and evaluation metrics, indicators, and outcomes. Currently, a total of 12 HBB educational evaluation, data collection, and reporting tools are available. Scoring is automated, and “pass” or “fail” messages as well as guided debriefing sequences are fully customizable. After submission to the mHBS-DHIS2 server, evaluation forms are no longer editable, providing a digital record of the progression of learning, skills, and competencies among trainees.94 

FIGURE 6

Screenshots from the mHBS-DHIS2 trainer app. A, The mHBS-DHIS2 trainer app, in addition to other Android-based educational, training, and data collection apps, is accessed from links integrated in the mHBS-DHIS2 tracker app. B, From the mHBS-DHIS2 trainer home screen (left) users can navigate to partner Web sites, educational videos, and digitized HBS materials, including action plans and provider’s guides (right). C, Users can navigate as desired through the digitized HBB second edition provider’s guide. D, Web-based resources can be accessed from the mHBS-DHIS2 trainer app. Screenshots were reproduced with permission from S.L.B.

FIGURE 6

Screenshots from the mHBS-DHIS2 trainer app. A, The mHBS-DHIS2 trainer app, in addition to other Android-based educational, training, and data collection apps, is accessed from links integrated in the mHBS-DHIS2 tracker app. B, From the mHBS-DHIS2 trainer home screen (left) users can navigate to partner Web sites, educational videos, and digitized HBS materials, including action plans and provider’s guides (right). C, Users can navigate as desired through the digitized HBB second edition provider’s guide. D, Web-based resources can be accessed from the mHBS-DHIS2 trainer app. Screenshots were reproduced with permission from S.L.B.

Close modal

In addition to digitized versions of the HBB second edition multiple choice questionnaire, bag-and-mask skills assessment (bag mask ventilation), and Objective Structured Clinical Examinations (OSCEs) (Fig 5B), the mHBS-DHIS2 tracker module includes QI tools, such as the health facility site visit, delivery observation checklist (Fig 5C), and HBB delivery and practice log. The former is a standardized tool used to rapidly assess a facility’s readiness to provide basic neonatal resuscitation services. The delivery observation checklist is used to assess HBB competencies among HCPs during actual, observed deliveries. HBB providers use the HBB delivery and practice log to self-report (1) the number of deliveries and resuscitations they perform each shift and (2) stillbirths, as well as (3) if they had an opportunity to engage in peer learning or skills practice. QI champions can use the mHBS-DHIS2 app to follow-up on reported resuscitations and perinatal deaths through use of the resuscitation debriefing form and perinatal death audit.

HBS program implementers and participants can use mHBS-DHIS2 in various ways to support acquisition, retention, and evaluation of key knowledge, skills, and competencies at different time points throughout the dissemination and implementation cascade. For example, facilitators or champions can use mHBS-DHIS2 to administer educational evaluations and skills assessments to trainees before and after a course or during QI exercises. HBS providers can use the app to evaluate one another during peer learning at a course or subsequently as part of low-dose high-frequency training sessions after an in-person workshop.

Currently used as a research tool in conjunction with partners from Alupe University College, Lagos University, University of Washington, and Kenya Medical Research Institute/Oxford University (United Kingdom), mHBS-DHIS2 is undergoing field testing among HBB providers at 20 health facilities in Kenya and Nigeria. After completion of the study, mHBS-DHIS2 will be available for free download from Google Play.

The ECEB Digital Action Plan (Fig 7 A–C) is a mobile phone–based clinical decision support tool built to support nurses, midwives, and physicians in LMICs to more effectively deliver key newborn care interventions from birth through 24 hours postnatal and to equip HCPs to prevent, recognize, and manage common newborn complications as outlined in the AAP’s ECEB educational and training curriculum.

FIGURE 7

A, Screenshots from the ECEB Digital Action Plan; clinical decision support to guide essential newborn care. A, Customized log-on (left) and then register and track multiple infants (right). B, Births are time stamped, and automated care reminders are generated. C, Requests for consultation are embedded in the app (left); HCPs can track changes in infants’ health status over time (right). Screenshots were reproduced with permission from S.L.B.

FIGURE 7

A, Screenshots from the ECEB Digital Action Plan; clinical decision support to guide essential newborn care. A, Customized log-on (left) and then register and track multiple infants (right). B, Births are time stamped, and automated care reminders are generated. C, Requests for consultation are embedded in the app (left); HCPs can track changes in infants’ health status over time (right). Screenshots were reproduced with permission from S.L.B.

Close modal

The ECEB app, which can be used as a standalone app or as a module with mHBS-DHIS2, has numerous functions, including allowing health workers to simultaneously track multiple infants across nursing shifts and to quickly ascertain, in real time, the overall patient acuity in a facility’s newborn population (eg, number of “normal” versus “problem” versus “high-risk”). Births are time stamped, and automated, time-specific reminders for ECEB interventions are generated for each infant according to the infant’s time of birth. There are checklists that providers can use to track the delivery of ECEB interventions for each infant. On the basis of information entered by the user (eg, birth weight, vital signs), the ECEB app automatically classifies each infant into green (normal), yellow (problem), or red (high-risk) zones and generates advice for management. The app then automatically tracks the infants’ health status over time, including their movement between ECEB zones. Requests for consultation or help from on-call providers can be sent directly from the app.

The ECEB Digital Action Plan was designed by an international team of faculty, students, and clinicians, including content experts and mobile app developers from Indiana University School of Medicine, Indiana University–Purdue University School of Informatics and Computing, Alupe University College, and Moi Teaching and Referral Hospital (Eldoret, Kenya). The multidisciplinary team collaborated over 10 months to design, develop, evaluate, and build a user interface prototype.95  Heuristic evaluation and person-centered design assessments were conducted in Kenya among 40 nurses and midwives from 3 facilities.96  The app, which works off-line, was awarded first prize in the American Medical Informatics Association 2019 Student Design Challenge.97  It is anticipated to be available on Google Play in 2021.

Evaluation of resuscitation care in LMICs is challenged by poor documentation of delivery room practices. As such, these evaluations are frequently limited to an assessment of delivery room preparedness (availability of an HBB-trained birth attendant and essential resuscitation equipment) rather than actions taken during a resuscitation. Digital tools to document resuscitation actions in real time provide a unique opportunity to enhance understanding of delivery room practices in LMICs and ultimately support QI.

Liveborn is an audit-feedback mobile health application for newborn resuscitation designed by Laerdal Global Health in partnership with the University of North Carolina School of Medicine (UNC SOM). Initially developed as a data collection tool, the application has been adapted for clinical use with the additions of a simplified documentation screen and automated feedback after a resuscitation. To date, Liveborn has been used in the Democratic Republic of the Congo (DRC), Nepal, Norway, and Tanzania to document >26 564 newborn resuscitations.98 

Using Liveborn, an observer can document the timing of resuscitation actions using push buttons with HBB icons for dry or stimulate, skin-to-skin, clamp cord, suction, and ventilate (Fig 8). The observer can also document when the infant begins breathing and crying. Using Bluetooth technology, Liveborn includes the option to stream heart rate from NeoBeat, Laerdal’s battery-operated newborn heart rate meter. After the resuscitation, providers can review a feedback screen that visually displays a time line of resuscitation events and the newborn’s breathing status and heart rate (if NeoBeat is used). This screen includes an observation about a gap in quality derived from an automatic comparison of recorded actions to the HBB algorithm. The observation is accompanied by an HBB recommendation for how to improve care and a discussion question for reflection. Data from multiple resuscitations can also be aggregated through a Microsoft Power BI dashboard system to support facility-based QI activities. Liveborn is free of charge and publicly available on both Android and iOS platforms with English and French versions.

FIGURE 8

Screenshots from the Liveborn app. The Liveborn event registration screen allows an observer to document the timing of resuscitation actions and breathing status of the newborn. The feedback screen depicts a time line of the resuscitation, highlights a gap in quality, provides an HBB recommendation about how to improve care, and suggests a question for discussion. Screenshots were reproduced with permission from Laerdal Global Health (https://laerdalglobalhealth.com/).

FIGURE 8

Screenshots from the Liveborn app. The Liveborn event registration screen allows an observer to document the timing of resuscitation actions and breathing status of the newborn. The feedback screen depicts a time line of the resuscitation, highlights a gap in quality, provides an HBB recommendation about how to improve care, and suggests a question for discussion. Screenshots were reproduced with permission from Laerdal Global Health (https://laerdalglobalhealth.com/).

Close modal

Although publicly available, there is still uncertainty regarding how best to use Liveborn in the clinical setting. A team of investigators from UNC SOM, the Kinshasa School of Public Health, and Laerdal are evaluating usability, feasibility, and acceptability of Liveborn in a pilot study in one health center in Kinshasa, DRC (University of North Carolina Institutional Review Board 19–3479; DRC Institutional Review Board 166/CNES/BN/PMMF/2020). Future directions for Liveborn include audiovisual real-time feedback during a resuscitation when paired with NeoBeat, as well as automation of data capture to eliminate the need for an observer.

The global community has 10 years to achieve Sustainable Development Goals, including health target 3.2, to reduce the overall global neonatal mortality rate to 12 per 1000 live births.99  HBS partners and related collaboratives, such as the World Health Organization’s Every Newborn Action Plan and Quality, Equity, Dignity Network, are striving to achieve this ambitious goal. To be successful, there is a critical need to substantially improve the quality of health worker education and training and delivery of newborn care for effective, high-impact interventions such as neonatal resuscitation, essential newborn care, and care for premature and small infants.19,84,85,100  Better tracking of high-quality neonatal data and key indicators is also urgently needed.79,101 

Over the past decade, a number of mobile phone app and digital health innovations have been developed to support education and training, data collection for monitoring and evaluation, clinical decision support, and QI for HBS programs. Additional data are needed regarding the efficacy, cost, and impact of each of these apps as standalone tools and as bundled innovations, where applicable.102,103  A number of trials are currently underway.98,104  If shown to be effective, and if adopted and scaled, particularly as integrated interventions,105  digital tools and platforms may have the potential to address some of the gaps and barriers that have been identified in the dissemination and implementation cascade for HBS. Overcoming these challenges might, in turn, augment global progress toward better policies, outcomes, and clinical care for newborns in LMICs.106108 

Stakeholders can potentially integrate digital innovations with HBS dissemination and implementation efforts in a myriad of ways. For example, all of the digital tools described in this article could be potentially used in creative ways to support acquisition, consolidation, and retention of knowledge, skills, and performance competencies for neonatal resuscitation,2,4,109  both during pre-service and through integration into low-dose high-frequency skills practice, in-person refresher courses, continuing medical and/or nursing education, on-the-job training, or peer-to-peer learning among in-service providers.2,4,109,110  The quality of newborn care is also often impacted by high rates of staff turnover and chronic shortages of skilled nursing and physician cadres, as well as lack of high-quality data regarding key indicators and outcomes.111  Thus, any training and data collection efficiencies that can be leveraged, via digital health interventions, to ameliorate these challenges and strengthen health systems112  are potentially of high value.113115 

We thank the many student and Kenyan collaborators who have contributed to the mHBS-DHIS2 and ECEB Digital Action Plan design, development, usability testing, and evaluation from 2012 to 2020, including M.T. Imran Chowdhury, Bhavani Singh Agnikula Kshatriya, Prem Chand Avanigadda, Siva Addepally, Elisabeth Meyers (in memoriam), Taylor Childers, Olakunle Olardiran, Siddhartha Nuthakki, Chinazom Chukwuemeka, Anushri S. Rajapuri, Radhika Ravindran, Kevin Horan, Kevin Otieno, Janet Rukunga, Sammy Barasa, Bonnie Munyalo, Geoffrey Mwai, Mary Concepta Nafula, Annet Musale, Professor Fabian Esamai, and the many nurses and nurse-midwives who have graciously provided invaluable feedback over the years.

Dr Bucher conceptualized and designed the review, drafted the initial manuscript, coauthored the sections on mobile Helping Babies Survive powered by the District Health Information System 2 (mHBS-DHIS2), was the primary author for the section regarding the Essential Care for Every Baby Digital Action Plan, and created the mHBS-DHIS2 and mobile Helping Babies Survive–Essential Care for Every Baby figures; Dr Cardellichio was the primary author for the section regarding Global Health Media Project; Ms Muinga was the primary author for the section regarding the Life-Saving Instruction for Emergencies platform and created the Life-Saving Instruction for Emergencies figure; Dr Patterson was the primary author for the section regarding Liveborn, created the Liveborn figure, and developed Table 1; Drs Thukral and Deorari were the primary authors for the section regarding the All India Institute for Medical Science apps and created the All India Institute for Medical Science app figures; Dr Umoren was the primary author for the section regarding electronic Helping Babies Breathe and created the electronic Helping Babies Breathe figure; Dr Purkayastha coauthored the sections on mHBS-DHIS2 and cocreated the mHBS-DHIS2 figures; and all authors reviewed and revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

     
  • AAP

    American Academy of Pediatrics

  •  
  • AIIMS

    All India Institute for Medical Science

  •  
  • DRC

    Democratic Republic of the Congo

  •  
  • ECEB

    Essential Care for Every Baby

  •  
  • ECSB

    Essential Care for Small Babies

  •  
  • eHBB

    electronic Helping Babies Breathe

  •  
  • ETAT+

    Emergency Triage, Assessment and Treatment plus admission care program

  •  
  • GHMP

    Global Health Media Project

  •  
  • HBB

    Helping Babies Breathe

  •  
  • HBS

    Helping Babies Survive

  •  
  • HBS-ECSB

    Helping Babies Survive–Essential Care for Small Babies

  •  
  • HBS-ENC

    Helping Babies Survive–Essential Newborn Care

  •  
  • HCP

    health care providers

  •  
  • LIFE

    Life-Saving Instruction for Emergencies

  •  
  • LMIC

    low- and middle-income country

  •  
  • mHBS-DHIS2

    mobile Helping Babies Survive powered by District Health Information System 2

  •  
  • OSCE

    Objective Structured Clinical Examination

  •  
  • QI

    quality improvement

  •  
  • UNC SOM

    University of North Carolina School of Medicine

  •  
  • VR

    virtual reality

1
Singhal
N
,
Lockyer
J
,
Fidler
H
, et al
.
Helping Babies Breathe: global neonatal resuscitation program development and formative educational evaluation
.
Resuscitation
.
2012
;
83
(
1
):
90
96
2
Hoban
R
,
Bucher
S
,
Neuman
I
,
Chen
M
,
Tesfaye
N
,
Spector
JM
.
‘Helping Babies Breathe’ training in sub-Saharan Africa: educational impact and learner impressions
.
J Trop Pediatr
.
2013
;
59
(
3
):
180
186
3
Bellad
RM
,
Bang
A
,
Carlo
WA
, et al;
HBB Study Group
.
A pre-post study of a multi-country scale up of resuscitation training of facility birth attendants: does Helping Babies Breathe training save lives?
BMC Pregnancy Childbirth
.
2016
;
16
(
1
):
222
4
Bang
A
,
Patel
A
,
Bellad
R
, et al
.
Helping Babies Breathe (HBB) training: what happens to knowledge and skills over time?
BMC Pregnancy Childbirth
.
2016
;
16
(
1
):
364
5
Bose
C
,
Singhal
N
, eds
; American Academy of Pediatrics; Laerdal Global Health. Helping Babies Survive: Essential Care for Every Baby. Facilitator flip chart.
2014
. Available at: https://www.aap.org/en-us/advocacy-and-policy/aap-health-initiatives/helping-babies-survive/Pages/Essential-Care-Every-Baby.aspx. Accessed July 23, 2020
6
Thukral
A
,
Lockyer
J
,
Bucher
SL
, et al
.
Evaluation of an educational program for essential newborn care in resource-limited settings: Essential Care for Every Baby
.
BMC Pediatr
.
2015
;
15
:
71
7
Perez
K
,
Patterson
J
,
Hinshaw
J
, et al
.
Essential Care for Every Baby: improving compliance with newborn care practices in rural Nicaragua
.
BMC Pregnancy Childbirth
.
2018
;
18
(
1
):
371
8
Singhal
N
,
Berkelhamer
S
, eds
; American Academy of Pediatrics; Laerdal Global Health. Helping Babies Survive: Essential Care for Every Baby. Facilitator flip chart.
2015
. Available at: https://www.aap.org/en-us/advocacy-and-policy/aap-health-initiatives/helping-babies-survive/Pages/Essential-Care-Small-Babies.aspx. Accessed July 23, 2020
9
Prullage
GS
,
Baker
VL
.
Readiness for essential care of the small baby practice in Rwanda: an exploratory study
.
Midwifery
.
2018
;
58
:
50
55
10
Kak
LP
,
Johnson
J
,
McPherson
R
,
Keenan
W
,
Schoen
E
.
Helping Babies Breathe: Lessons Learned Guiding the Way Forward
.
Westport, CT
:
Save the Children
;
2015
11
Moshiro
R
,
Ersdal
HL
,
Mdoe
P
,
Kidanto
HL
,
Mbekenga
C
.
Factors affecting effective ventilation during newborn resuscitation: a qualitative study among midwives in rural Tanzania
.
Glob Health Action
.
2018
;
11
(
1
):
1423862
12
Musafili
A
,
Essén
B
,
Baribwira
C
,
Rukundo
A
,
Persson
.
Evaluating Helping Babies Breathe: training for healthcare workers at hospitals in Rwanda
.
Acta Paediatr
.
2013
;
102
(
1
):
e34
e38
13
Rule
ARL
,
Maina
E
,
Cheruiyot
D
,
Mueri
P
,
Simmons
JM
,
Kamath-Rayne
BD
.
Using quality improvement to decrease birth asphyxia rates after ‘Helping Babies Breathe’ training in Kenya
.
Acta Paediatr
.
2017
;
106
(
10
):
1666
1673
14
Eblovi
D
,
Kelly
P
,
Afua
G
,
Agyapong
S
,
Dante
S
,
Pellerite
M
.
Retention and use of newborn resuscitation skills following a series of Helping Babies Breathe trainings for midwives in rural Ghana
.
Glob Health Action
.
2017
;
10
(
1
):
1387985
15
Ersdal
HL
,
Vossius
C
,
Bayo
E
, et al
.
A one-day “Helping Babies Breathe” course improves simulated performance but not clinical management of neonates
.
Resuscitation
.
2013
;
84
(
10
):
1422
1427
16
Mduma
E
,
Kvaløy
JT
,
Soreide
E
, et al
.
Frequent refresher training on newborn resuscitation and potential impact on perinatal outcome over time in a rural Tanzanian hospital: an observational study
.
BMJ Open
.
2019
;
9
(
9
):
e030572
17
Drake
M
,
Bishanga
DR
,
Temu
A
, et al
.
Structured on-the-job training to improve retention of newborn resuscitation skills: a national cohort Helping Babies Breathe study in Tanzania
.
BMC Pediatr
.
2019
;
19
(
1
):
51
18
Gurung
R
,
Gurung
A
,
Sunny
AK
, et al
.
Effect of skill drills on neonatal ventilation performance in a simulated setting-observation study in Nepal
.
Stem Cell Res Ther
.
2019
;
10
(
1
):
314
19
Kamath-Rayne
BD
,
Berkelhamer
SK
,
Kc
A
,
Ersdal
HL
,
Niermeyer
S
.
Neonatal resuscitation in global health settings: an examination of the past to prepare for the future
.
Pediatr Res
.
2017
;
82
(
2
):
194
200
20
Ley
B
,
Rijal
KR
,
Marfurt
J
, et al
.
Analysis of erroneous data entries in paper based and electronic data collection
.
BMC Res Notes
.
2019
;
12
(
1
):
537
21
Njuguna
HN
,
Caselton
DL
,
Arunga
GO
, et al
.
A comparison of smartphones to paper-based questionnaires for routine influenza sentinel surveillance, Kenya, 2011-2012
.
BMC Med Inform Decis Mak
.
2014
;
14
:
107
22
Campbell
TC
,
Hodanics
CJ
,
Babin
SM
, et al
.
Developing open source, self-contained disease surveillance software applications for use in resource-limited settings
.
BMC Med Inform Decis Mak
.
2012
;
12
:
99
23
Thriemer
K
,
Ley
B
,
Ame
SM
, et al
.
Replacing paper data collection forms with electronic data entry in the field: findings from a study of community-acquired bloodstream infections in Pemba, Zanzibar
.
BMC Res Notes
.
2012
;
5
:
113
24
Dickinson
FM
,
McCauley
M
,
Madaj
B
,
van den Broek
N
.
Using electronic tablets for data collection for healthcare service and maternal health assessments in low resource settings: lessons learnt
.
BMC Health Serv Res
.
2019
;
19
(
1
):
336
25
Zeleke
AA
,
Worku
AG
,
Demissie
A
, et al
.
Evaluation of electronic and paper-pen data capturing tools for data quality in a public health survey in a health and demographic surveillance site, Ethiopia: randomized controlled crossover health care information technology evaluation
.
JMIR Mhealth Uhealth
.
2019
;
7
(
2
):
e10995
26
Medhanyie
AA
,
Moser
A
,
Spigt
M
, et al
.
Mobile health data collection at primary health care in Ethiopia: a feasible challenge
.
J Clin Epidemiol
.
2015
;
68
(
1
):
80
86
27
Medhanyie
AA
,
Spigt
M
,
Yebyo
H
, et al
.
Quality of routine health data collected by health workers using smartphone at primary health care in Ethiopia
.
Int J Med Inform
.
2017
;
101
:
9
14
28
Jemere
AT
,
Yeneneh
YE
,
Tilahun
B
,
Fritz
F
,
Alemu
S
,
Kebede
M
.
Access to mobile phone and willingness to receive mHealth services among patients with diabetes in Northwest Ethiopia: a cross-sectional study
.
BMJ Open
.
2019
;
9
(
1
):
e021766
29
Endehabtu
B
,
Weldeab
A
,
Were
M
,
Lester
R
,
Worku
A
,
Tilahun
B
.
Mobile phone access and willingness among mothers to receive a text-based mHealth intervention to improve prenatal care in northwest Ethiopia: cross-sectional study
.
JMIR Pediatr Parent
.
2018
;
1
(
2
):
e9
30
Lee
S
,
Cho
YM
,
Kim
SY
.
Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis
.
Global Health
.
2017
;
13
(
1
):
63
31
Madanian
S
,
Parry
DT
,
Airehrour
D
,
Cherrington
M
.
mHealth and big-data integration: promises for healthcare system in India
.
BMJ Health Care Inform
.
2019
;
26
(
1
):
e100071
32
Kemp
S
;
We
Are Social
. Digital in 2018: world’s Internet users pass the 4 billion mark.
2018
. Available at: https://digitalreport.wearesocial.com/. Accessed February 12, 2020
33
Noordam
AC
,
Kuepper
BM
,
Stekelenburg
J
,
Milen
A
.
Improvement of maternal health services through the use of mobile phones
.
Trop Med Int Health
.
2011
;
16
(
5
):
622
626
34
Garner
SL
,
Sudia
T
,
Rachaprolu
S
.
Smart phone accessibility and mHealth use in a limited resource setting
.
Int J Nurs Pract
.
2018
;
24
(
1
):
e12609
35
Källander
K
,
Tibenderana
JK
,
Akpogheneta
OJ
, et al
.
Mobile health (mHealth) approaches and lessons for increased performance and retention of community health workers in low- and middle-income countries: a review
.
J Med Internet Res
.
2013
;
15
(
1
):
e17
36
Amoakoh-Coleman
M
,
Borgstein
AB
,
Sondaal
SF
, et al
.
Effectiveness of mHealth interventions targeting health care workers to improve pregnancy outcomes in low- and middle-income countries: a systematic review
.
J Med Internet Res
.
2016
;
18
(
8
):
e226
37
Gisore
P
,
Shipala
E
,
Otieno
K
, et al
.
Community based weighing of newborns and use of mobile phones by village elders in rural settings in Kenya: a decentralised approach to health care provision
.
BMC Pregnancy Childbirth
.
2012
;
12
:
15
38
Winters
N
,
Langer
L
,
Nduku
P
, et al
.
Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence
.
BMJ Glob Health
.
2019
;
4
(
4
):
e001421
39
Oyeyemi
SO
,
Wynn
R
.
Giving cell phones to pregnant women and improving services may increase primary health facility utilization: a case-control study of a Nigerian project
.
Reprod Health
.
2014
;
11
(
1
):
8
40
Oyeyemi
SO
,
Wynn
R
.
The use of cell phones and radio communication systems to reduce delays in getting help for pregnant women in low- and middle-income countries: a scoping review
.
Glob Health Action
.
2015
;
8
:
28887
41
Early
J
,
Gonzalez
C
,
Gordon-Dseagu
V
,
Robles-Calderon
L
.
Use of mobile health (mHealth) technologies and interventions among community health workers globally: a scoping review
.
Health Promot Pract
.
2019
;
20
(
6
):
805
817
42
Modi
D
,
Dholakia
N
,
Gopalan
R
, et al
.
mHealth intervention “ImTeCHO” to improve delivery of maternal, neonatal, and child care services-A cluster-randomized trial in tribal areas of Gujarat, India
.
PLoS Med
.
2019
;
16
(
10
):
e1002939
43
Thomsen
CF
,
Barrie
AMF
,
Boas
IM
, et al
.
Health workers’ experiences with the Safe Delivery app in west Wollega zone, Ethiopia: a qualitative study
.
Reprod Health
.
2019
;
16
(
1
):
50
44
Lund
S
,
Boas
IM
,
Bedesa
T
,
Fekede
W
,
Nielsen
HS
,
Sørensen
BL
.
Association between the Safe Delivery app and quality of care and perinatal survival in Ethiopia: a randomized clinical trial
.
JAMA Pediatr
.
2016
;
170
(
8
):
765
771
45
Bolan
NE
,
Sthreshley
L
,
Ngoy
B
, et al
.
mLearning in the Democratic Republic of the Congo: a mixed-methods feasibility and pilot cluster randomized trial using the Safe Delivery app
.
Glob Health Sci Pract
.
2018
;
6
(
4
):
693
710
46
Carmichael
SL
,
Mehta
K
,
Srikantiah
S
, et al;
Ananya Study Group
.
Use of mobile technology by frontline health workers to promote reproductive, maternal, newborn and child health and nutrition: a cluster randomized controlled Trial in Bihar, India
.
J Glob Health
.
2019
;
9
(
2
):
0204249
47
US Agency of International Development
.
Survive and thrive global developmental alliance.
2012
. Available at: https://surviveandthrive.org/Pages/default.aspx. Accessed February 26, 2020
48
Global Health Media Project.
2020
. Available at: https://globalhealthmedia.org/. Accessed July 23, 2020
49
Reed
S
,
Shell
R
,
Kassis
K
, et al
.
Applying adult learning practices in medical education
.
Curr Probl Pediatr Adolesc Health Care
.
2014
;
44
(
6
):
170
181
50
Curtis
HA
,
Trang
K
,
Chason
KW
,
Biddinger
PD
.
Video-based learning vs traditional lecture for instructing emergency medicine residents in disaster medicine principles of mass triage, decontamination, and personal protective equipment
.
Prehosp Disaster Med
.
2018
;
33
(
1
):
7
12
51
Global Health Media Project
. Newborn care educational videos
2020
. Available at: https://globalhealthmedia.org/videos/. Accessed June 30, 2020
52
Global Health Media Project
.
Care of small babies educational videos.
2020
. Available at: https://globalhealthmedia.org/videos/. Accessed June 30, 2020
53
Sawyer
T
,
Umoren
RA
,
Gray
MM
.
Neonatal resuscitation: advances in training and practice
.
Adv Med Educ Pract
.
2016
;
8
:
11
19
54
Ghoman
SK
,
Patel
SD
,
Cutumisu
M
, et al
.
Serious games, a game changer in teaching neonatal resuscitation? A review
.
Arch Dis Child Fetal Neonatal Ed
.
2020
;
105
(
1
):
98
107
55
Parsons
TD
,
Rizzo
AA
.
Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: a meta-analysis
.
J Behav Ther Exp Psychiatry
.
2008
;
39
(
3
):
250
261
56
Seymour
NE
.
VR to OR: a review of the evidence that virtual reality simulation improves operating room performance
.
World J Surg
.
2008
;
32
(
2
):
182
188
57
Riva
G
,
Wiederhold
BK
,
Mantovani
F
.
Neuroscience of virtual reality: from virtual exposure to embodied medicine
.
Cyberpsychol Behav Soc Netw
.
2019
;
22
(
1
):
82
96
58
Almeida
L
,
Menezes
P
,
Dias
J
.
Augmented Reality Framework for the Socialization Between Elderly People
.
Philadelphia, PA
:
IGI Global
;
2013
59
Sitzmann
T
.
A meta-analytic examination of the instructional effectiveness of computer-based simulation games
.
Person Psychol
.
2011
;
64
(
2
):
489
528
60
Kaplan
AD
,
Cruit
J
,
Endsley
M
,
Beers
SM
,
Sawyer
BD
,
Hancock
PA
.
The effects of virtual reality, augmented reality, and mixed reality as training enhancement methods: a meta-analysis [published online ahead of print February 24, 2020]
.
Hum Factors
. doi:
61
Foronda
CL
,
Fernandez-Burgos
M
,
Nadeau
C
,
Kelley
CN
,
Henry
MN
.
Virtual simulation in nursing education: a systematic review spanning 1996 to 2018
.
Simul Healthc
.
2020
;
15
(
1
):
46
54
62
Vishwanath
A
,
Kam
M
.
Kumar
N
.
Examining low-cost virtual reality for learning in low-resource environments
. In:
Mival
O
, ed.
Proceedings from the Conference on Designing Interactive Systems
.
New York, NY
:
Association for Computing Machinery
;
2017
:
1277
1281
63
Umoren
R
,
Ezeaka
VC
,
Fajolu
IB
, et al
.
Perspectives on simulation-based training from paediatric healthcare providers in Nigeria: a national survey
.
BMJ Open
.
2020
;
10
(
2
):
e034029
64
Edgcombe
H
,
Paton
C
,
English
M
.
Enhancing emergency care in low-income countries using mobile technology-based training tools
.
Arch Dis Child
.
2016
;
101
(
12
):
1149
1152
65
University of Oxford
.
Team: the LIFE team.
2020
. Available at: https://oxlifeproject.org/team/. Accessed May 31, 2020
66
Dol
J
,
Campbell-Yeo
M
,
Murphy
GT
,
Aston
M
,
McMillan
D
,
Richardson
B
.
The impact of the Helping Babies Survive program on neonatal outcomes and health provider skills: a systematic review
.
JBI Database Syst Rev Implement Reports
.
2018
;
16
(
3
):
701
737
67
University of Oxford
. LIFE: Life-saving Instruction for Emergencies.
2020
. Available at: https://oxlifeproject.org/. Accessed June 2, 2020
68
Royal College of Paediatrics and Child Health
. Emergency Triage, Assessment, and Treatment plus (ETAT+) - online learning.
2020
. Available at: https://www.rcpch.ac.uk/resources/emergency-triage-assessment-treatment-plus-etat-online-learning. Accessed May 31, 2020
69
Hands
S
,
Verriotis
M
,
Mustapha
A
,
Ragab
H
,
Hands
C
.
Nurse-led implementation of ETAT+ is associated with reduced mortality in a children’s hospital in Freetown, Sierra Leone
.
Paediatr Int Child Health
.
2020
;
40
(
3
):
186
193
70
Tuti
T
,
Winters
N
,
Muinga
N
,
Wanyama
C
,
English
M
,
Paton
C
.
Evaluation of adaptive feedback in a smartphone-based serious game on health care providers’ knowledge gain in neonatal emergency care: protocol for a randomized controlled trial
.
JMIR Res Protoc
.
2019
;
8
(
7
):
e13034
71
Patel
P
;
Global Nursing Caucus.
Olivia Vélez – global digital health and nursing.
2018
. Available at: https://www.globalnursingcaucus.org/blog/olivia-velez-global-digital-health-and-nursing/. Accessed January 15, 2020
72
Mueller
R
;
Univadis
.
PAS
2018—Mobile app provides assistance for newborn care providers in low-income countries.
2018
. Available at: https://www.univadis.pt/conference-reports/868/PAS-2018-Mobile-app-provides-assistance-for-newborn-care-providers-in-low-income-countries#?. Accessed December 3, 2019
73
Bucher
SL
.
mHBB: Using Mobile Phones to Support Helping Babies Breathe in Kenya
.
Arlington, VA
:
Pediatric Academic Societies
;
2015
74
Agravat
N
.
Mhealth and Neonatal Resuscitation: A Review of Interventions, Approaches, and Applications
.
Washington, DC
:
mHealth Alliance
;
2013
75
Abwao
S
,
Bucher
S
,
Kaimenyi
P
,
Wachira
J
,
Esamai
F
,
Wamae
A.
 Kenya Case Study. In:
Kak
LP
,
Johnson
J
,
McPherson
R
,
Keenan
W
,
Schoen
E
, eds.
Helping Babies Breathe: Lessons Learned Guiding the Way Forward: A 5-Year Report from the HBB Global Development Alliance
.
Washington, DC
:
US Agency of International Development
;
2015
. Available at: http://cdn.laerdal.com/downloads-test/f3790/HBB_report_2010-2015_FINAL.pdf
76
District Health Information System 2.
2020
. Available at: https://www.dhis2.org/. Accessed July 23, 2020
77
Muruka
C
,
Ogendi
J
,
Onyango
P
.
Effect of implementation of free maternity policy on selected maternal and newborn health indicators in gem sub-county, Siaya County, Western Kenya
.
J Health Care Poor Underserved
.
2019
;
30
(
3
):
1132
1150
78
Bhattacharya
AA
,
Umar
N
,
Audu
A
, et al
.
Quality of routine facility data for monitoring priority maternal and newborn indicators in DHIS2: a case study from Gombe State, Nigeria
.
PLoS One
.
2019
;
14
(
1
):
e0211265
79
Day
LT
,
Ruysen
H
,
Gordeev
VS
, et al
.
“Every Newborn-BIRTH” protocol: observational study validating indicators for coverage and quality of maternal and newborn health care in Bangladesh, Nepal and Tanzania
.
J Glob Health
.
2019
;
9
(
1
):
010902
80
Odei-Lartey
EO
,
Prah
RKD
,
Anane
EA
, et al
.
Utilization of the national cluster of District Health Information System for health service decision-making at the district, sub-district and community levels in selected districts of the Brong Ahafo region in Ghana
.
BMC Health Serv Res
.
2020
;
20
(
1
):
514
81
Begum
T
,
Khan
SM
,
Adamou
B
, et al
.
Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: a qualitative exploratory study
.
BMC Health Serv Res
.
2020
;
20
(
1
):
465
82
Saleem
S
,
Tikmani
SS
,
McClure
EM
, et al
.
Trends and determinants of stillbirth in developing countries: results from the Global Network’s Population-Based Birth Registry
.
Reprod Health
.
2018
;
15
(
suppl 1
):
100
83
Doctor
HV
.
Assessing antenatal care and newborn survival in sub-Saharan Africa within the context of renewed commitments to save newborn lives
.
AIMS Public Health
.
2016
;
3
(
3
):
432
447
84
Niermeyer
S
,
Robertson
NJ
,
Ersdal
HL
.
Beyond basic resuscitation: what are the next steps to improve the outcomes of resuscitation at birth when resources are limited?
Semin Fetal Neonatal Med
.
2018
;
23
(
5
):
361
368
85
Niermeyer
S
.
Improving global newborn survival: building upon Helping Babies Breathe
.
Neonatology
.
2020
;
117
(
2
):
211
216
86
Kinney
MV
,
Cocoman
O
,
Dickson
KE
, et al
.
Implementation of the Every Newborn Action Plan: progress and lessons learned
.
Semin Perinatol
.
2015
;
39
(
5
):
326
337
87
Darmstadt
GL
,
Shiffman
J
,
Lawn
JE
.
Advancing the newborn and stillbirth global agenda: priorities for the next decade
.
Arch Dis Child
.
2015
;
100
(
suppl 1
):
S13
S18
88
Chou
D
,
Daelmans
B
,
Jolivet
RR
,
Kinney
M
,
Say
L
;
Every Newborn Action Plan (ENAP) and Ending Preventable Maternal Mortality (EPMM) working groups
.
Ending preventable maternal and newborn mortality and stillbirths
.
BMJ
.
2015
;
351
:
h4255
89
Baschieri
A
,
Gordeev
VS
,
Akuze
J
, et al
.
“Every Newborn-INDEPTH” (EN-INDEPTH) study protocol for a randomised comparison of household survey modules for measuring stillbirths and neonatal deaths in five Health and Demographic Surveillance sites
.
J Glob Health
.
2019
;
9
(
1
):
010901
90
Purkayastha
S
,
Addepally
SA
,
Bucher
S
.
Engagement and usability of a cognitive behavioral therapy mobile app compared with web-based cognitive behavioral therapy among college students: randomized heuristic trial
.
JMIR Human Factors
.
2020
;
7
(
1
):
e14146
91
Bucher
S
,
Meyers
E
,
Kshatriya
BSA
,
Avanigadda
PC
,
Purkayastha
S
. Development of an Innovative Mobile Phone-Based Newborn Care Training Application. In:
Abraham
A
,
Gandhi
N
,
Pant
M
, eds.
Innovations in Bio-Inspired Computing and Applications
.
Cham, Switzerland
:
Springer International Publishing
;
2019
:
361
374
92
Purkayastha
S
,
Bucher
S
; GitHub. Mobile Helping Babies Survive powered by DHIS2 trainer app.
2016
. Available at: https://github.com/iupui-soic/mHBS_tracker. Accessed June 1, 2020
93
Purkayastha
S
,
Bucher
S
; GitHub. Mobile Helping Babies Survive powered by DHIS2: tracker app.
2016
. Available at: https://github.com/iupui-soic/dhis2-android-trackercapture. Accessed June 1, 2020
94
Bucher
SL
,
Purkayastha
S
,
Agnikula Kshatriya
BS
,
Avanigadda
PC
,
Chowdhury
MI
.
Development of digitized educational evaluation checklists to support implementation of neonatal resuscitation programs in low/middle-income countries
. In:
Proceedings from the Global Digital Health Forum
; December 9–10, 2019; Washington, DC
95
Nuthakki
S
,
Bucher
S
,
Purkayastha
S
.
The development and usability testing of a decision support mobile app for the Essential Care for Every Baby (ECEB) program
. In:
Stephanidis
C
,
Antona
M
, eds.
Proceedings from the 21st HCI International Conference
; July 26–31, 2019;
Orlando, FL
;
259
263
96
Rajapuri
AS
,
Ravindran
R
,
Horan
K
,
Bucher
S
,
Purkayastha
S
. Essential Care for Every Baby: Neonatal Clinical Decision Support Tool. In:
Kalra
J
,
Lightner
N
, eds.
Advances in Human Factors and Ergonomics in Healthcare and Medical Devices. AHFE 2020. Advances in Intelligent Systems and Computing
, vol.
1205
.
Cham
:
Springer
;
2020
. Available at:
97
Lovrinic
J.
 Students’ “Essential Care for Every Baby”.
app Wins at AMIA
.
Indiana University–Purdue University Indianapolis School of Informatics and Computing
;
2019
98
Gurung
R
,
Jha
AK
,
Pyakurel
S
, et al.
Scaling Up Safer Birth Bundle Through Quality Improvement in Nepal (SUSTAIN)-a stepped wedge cluster randomized controlled trial in public hospitals. Implement Sci.
2019
;14(1):65
99
United Nations
.
Sustainable development goals.
2020
. Available at: https://www.un.org/sustainabledevelopment/health/. Accessed July 23, 2020
100
Ehret
DY
,
Patterson
JK
,
Bose
CL
.
Improving neonatal care: a global perspective
.
Clin Perinatol
.
2017
;
44
(
3
):
567
582
101
Hagel
C
,
Paton
C
,
Mbevi
G
,
English
M
;
Clinical Information Network (CIN) information systems interest group
.
Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya
.
BMJ Glob Health
.
2020
;
5
(
3
):
e002108
102
Shukla
V
,
Carlo
WA
.
Technology-driven neonatal health care in low-resource settings: expectations and reality
.
EClinicalMedicine
.
2019
;
12
:
2
3
103
Khanna
R
,
Karikalan
N
,
Mishra
AK
,
Agarwal
A
,
Bhattacharya
M
,
Das
JK
.
Repository on maternal child health: health portal to improve access to information on maternal child health in India
.
BMC Public Health
.
2013
;
13
:
2
104
Merali
HS
,
Chan
NH
,
Mistry
N
, et al
.
Designing and evaluating a novel mobile application for Helping Babies Breathe skills retention in Uganda: comparative study protocol
.
BMJ Paediatr Open
.
2019
;
3
(
1
):
e000561
105
Ruton
H
,
Musabyimana
A
,
Gaju
E
, et al
.
The impact of an mHealth monitoring system on health care utilization by mothers and children: an evaluation using routine health information in Rwanda
.
Health Policy Plan
.
2018
;
33
(
8
):
920
927
106
Tuti
T
,
Bitok
M
,
Malla
L
, et al
.
Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals
.
BMJ Glob Health
.
2016
;
1
(
1
):
e000028
107
English
M
,
Irimu
G
,
Agweyu
A
, et al
.
Building learning health systems to accelerate research and improve outcomes of clinical care in low- and middle-income countries
.
PLoS Med
.
2016
;
13
(
4
):
e1001991
108
Smith
JM
,
de Graft-Johnson
J
,
Zyaee
P
,
Ricca
J
,
Fullerton
J
.
Scaling up high-impact interventions: how is it done?
Int J Gynaecol Obstet
.
2015
;
130
(
suppl 2
):
S4
S10
109
Goudar
SS
,
Somannavar
MS
,
Clark
R
, et al
.
Stillbirth and newborn mortality in India after Helping Babies Breathe training
.
Pediatrics
.
2013
;
131
(
2
). Available at: www.pediatrics.org/cgi/content/full/131/2/e344
110
Cordova
E
,
Al-Rousan
T
,
Castillo-Angeles
M
,
Aftab
S
,
Nelson
BD
.
Effect of low-cost interventions on the retention of knowledge and skills following Helping Babies Breathe training
.
Int J Gynaecol Obstet
.
2018
;
142
(
2
):
248
254
111
English
M
,
Mwaniki
P
,
Julius
T
, et al
.
Hospital mortality - a neglected but rich source of information supporting the transition to higher quality health systems in low and middle income countries
.
BMC Med
.
2018
;
16
(
1
):
32
112
Burstein
R
,
Henry
NJ
,
Collison
ML
, et al
.
Mapping 123 million neonatal, infant and child deaths between 2000 and 2017
.
Nature
.
2019
;
574
(
7778
):
353
358
113
Gachau
S
,
Ayieko
P
,
Gathara
D
, et al
.
Does audit and feedback improve the adoption of recommended practices? Evidence from a longitudinal observational study of an emerging clinical network in Kenya
.
BMJ Glob Health
.
2017
;
2
(
4
):
e000468
114
Tuti
T
,
Bitok
M
,
Paton
C
, et al
.
Innovating to enhance clinical data management using non-commercial and open source solutions across a multi-center network supporting inpatient pediatric care and research in Kenya
.
J Am Med Inform Assoc
.
2016
;
23
(
1
):
184
192
115
Murphy
GAV
,
Gathara
D
,
Mwaniki
A
, et al
.
Nursing knowledge of essential maternal and newborn care in a high-mortality urban African setting: a cross-sectional study
.
J Clin Nurs
.
2019
;
28
(
5–6
):
882
893
116
Berkelhamer
S
,
Singhal
N
.
Revisiting: “A pre-post study of a multi-country scale up of resuscitation training of facility birth attendants: does Helping Babies Breathe training save lives?”
.
BMC Pregnancy Childbirth
.
2019
;
19
(
1
):
380
117
Somannavar
MS
,
Goudar
SS
,
Revankar
AP
, et al
.
Evaluating time between birth to cry or bag and mask ventilation using mobile delivery room timers in India: the NICHD Global Network’s Helping Babies Breathe Trial
.
BMC Pediatr
.
2015
;
15
:
93
118
Crehan
C
,
Kesler
E
,
Nambiar
B
, et al
.
The NeoTree application: developing an integrated mHealth solution to improve quality of newborn care and survival in a district hospital in Malawi
.
BMJ Glob Health
.
2019
;
4
(
1
):
e000860
119
McCauley
K
,
Kreofsky
BL
,
Suhr
T
,
Fang
JL
.
Developing a Newborn Resuscitation Telemedicine program: a follow-up study comparing two technologies
.
Telemed J E Health
.
2020
;
26
(
5
):
589
596
120
Jones-Bamman
C
,
Niermeyer
S
,
McConnell
K
,
Thomas
JF
,
Olson
C
.
Teaching Helping Babies Breathe via Telehealth: a new application in rural Guatemala
.
Biomed Hub
.
2019
;
4
(
3
):
1
6

Competing Interests

POTENTIAL CONFLICT OF INTEREST: Dr Bucher is principal investigator (PI) of mobile Helping Babies Survive (HBS) powered by the District Health Information System 2 and Essential Care for Every Baby Digital Action Plan initiatives. She was the co-PI for the electronic Helping Babies Breathe (HBB) project, in collaboration with Dr Umoren. She serves as an international mentor, on behalf of the American Academy of Pediatrics, for HBS programs, and as the HBS country mentor for Kenya and Liberia. Dr Cardellichio is the associate director of Global Health Media Project. Ms Muinga is a health informatics researcher based at Kenya Medical Research Institute Wellcome Trust Programme for the Life-Saving Instruction for Emergencies initiative. Dr Patterson is the PI for the feedback and debriefing portions of Liveborn and the ongoing β-testing of Liveborn. Dr Thukral and Prof Deorari serve as associate professor in the department of pediatrics and professor and head of the department of pediatrics at All India Institute for Medical Science, New Delhi; Prof Deorari serves on the HBS Planning Group. Dr Santorino Data is the PI and colead designer for the HBB Prompt app. Dr Umoren was lead PI for the electronic HBB project. Dr Saptarshi Purkayastha is co-PI of the HBS powered by the District Health Information System 2 and Essential Care for Every Baby app projects. The authors have indicated they have no other potential conflicts of interest to disclose

FINANCIAL DISCLOSURES: Support for the development of Global Health Media Project videos related to Helping Babies Survive programs was provided by the Laerdal Foundation, Latter-day Saint Charities, Vitol Foundation, and Save the Children Federation. Life-Saving Instruction for Emergencies design and development funding was provided through a crowdfunding initiative by the University of Oxford and the Saving Lives at Birth seed funds (round 6). Support for the development of electronic Helping Babies Breathe and electronic Helping Babies Breathe + mobile Helping Babies Survive powered by the District Health Information System 2 (mHBS-DHIS2) field testing activities was provided by Bill and Melinda Gates Foundation to the University of Washington (Dr Umoren; OPP1169873). Development and proof-of-concept funding for mHBS-DHIS2 was provided, in part, to Dr Bucher by the Laerdal Foundation for Acute Medicine (2012–2014); contextual analysis (2015–2016) by Johnson & Johnson corporate giving (4581903); and Indiana University–Purdue University Indianapolis Center for Teaching and Learning, Multidisciplinary Undergraduate Research Institute (summer 2017; academic year 2017–2018). Essential Care for Every Baby Digital Action Plan app development and additional mHBS-DHIS2 server hosting were supported by Indiana University School of Medicine (Bucher) and Indiana University–Purdue University Indianapolis School of Informatics and Computing (Dr Purkayastha). Dr Santorino Data received funding from Grand Challenges Canada for the development and testing of the Helping Babies Breathe Prompt application; support for development and β-testing of Liveborn was provided, in part, by a University of North Carolina Junior Faculty Development Award to Dr Patterson; the authors have indicated they have no other financial relationships relevant to this article to disclose.