The Essential Care For Every Baby Digital Action Plan: Design And Usability Testing Of A Mobile Phone-Based Newborn Care Decision Support Tool In Kenya

Background: Each year, there are 2.5 million neonatal deaths, primarily within low/middle-income countries (LMICs). Helping Babies Survive educational and training programs, including Essential Care for Every Baby (ECEB), equip LMIC healthcare providers (HCPs) with the knowledge, skills, and competencies to save newborn lives. Concurrently, growing access to mobile phones and improved network connectivity in LM4ICs open the possibility for digital decision support tools to assist HCPs to provide higher quality newborn care. Our team has developed an integrated suite of apps, mobile Helping Babies Survive powered by DHIS2 (mHBS/DHIS2), which are purpose-built to support effective implementation of Helping Babies Survive initiatives around the world. Existing mHBS/DHIS2 functionality includes: education, training, monitoring and evaluation, and quality improvement for Helping Babies Breathe. Here, we describe expanding mHBS/DHIS2 capabilities to include decision support for ECEB. Purpose: To describe the design and evaluation of a novel mobile phone-based digital decision-support tool for essential newborn care providers in LMICs. Methods: The 10-month study included 3 phases. During Phase 1, our multi-disciplinary, international team utilized open-source Java tools (DHIS2 mobile), human-centered design methods, iterative, agile processes (weekly scrum meetings), and heuristic evaluation to develop 2 versions of the ECEB decision support app. Then (Phase 2), we utilized the People At the Center of Mobile Application Development (PACMAD) model to evaluate, among 40 Kenyan newborn health providers from 3 high-volume health facilities (1 teaching and referral hospital; 2 county hospitals), each ECEB app version (n = 20 HCPs per version, Figure 1) across 7 domains of usability. During Phase 3, a final functional prototype was developed, based on feedback from the African PACMAD evaluation, and in consultation with a panel of global technical experts from the American Medical Informatics Association (AMIA). Results: ECEB app versions used in the PACMED evaluation are shown in Figure 1. Version B emerged as the clearly preferred option among Kenyan HCPs, particularly in regards to PACMAD domains of: Memorability (ECEB app promoted accurate delivery of time-sensitive clinical interventions through time-stamping of deliveries and recognition, rather than recall); Effectiveness (automated classification and color-coding of babies as "normal"/green; "problem"/yellow; "urgent"/red); Efficiency and Cognitive Load (offline capability to access and track, in one application, multiple babies across nursing shifts and wards); and Learnability (rapid access to key information for improved clinical management). The final prototype (Figure 2) won first prize in the competitive 2019 AMIA Student Design Challenge. Conclusion(s): The ECEB app is an innovative and potentially powerful digital tool for essential newborn care providers in LMICs. We have integrated the ECEB Digital Action Plan and newborn care decision support tool with the mobile Helping Babies Survive powered by DHIS2 app, to create an Android-based digital "toolkit" for Helping Babies Survive providers around the world.