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Objective To describe a systematic process of transforming paper registers into a digital system optimized to enhance service provision and fulfil reporting requirements. Methods We designed a formative study around primary health workers providing reproductive, maternal, newborn and child health services in three countries in Bangladesh, Indonesia and Pakistan. The study ran from November 2014 to June 2018. We developed a prototype digital application after conducting a needs assessment of health workers' responsibilities, workflows, routine data requirements and service delivery needs. Methods included desk reviews, focus group discussions, in-depth interviews; data mapping of paper registers; observations of health workers; co-design workshops with health workers; and usability testing. Finally, we conducted an observational feasibility assessment to monitor uptake of the application. Findings Researchers reviewed a total of 17 paper registers across the sites, which we transformed into seven modules within a digital application running on mobile devices. Modules corresponded to the services provided, including household enumeration, antenatal care, family planning, immunization, nutrition and child health. A total of 65 health workers used the modules during the feasibility assessment, and average weekly form submissions ranged from 8 to 234, depending on the health worker and their responsibilities. We also observed variability in the use of modules, requiring consistent monitoring support for health workers. Conclusion Lessons learnt from this study shaped key global initiatives and resulted in a software global good. The deployment of digital systems requires well-designed applications, change management and strengthening human resources to realize and sustain health system gains. Objectif Decrire un processus methodique de transformation des registres papier en systeme numerique optimise, en vue d'ameliorer la fourniture de services et de remplir les exigences relatives a l'etablissement de rapports. Methodes Nous avons concu une etude formative consacree aux professionnels des soins primaires proposant des services de sante reproductive et maternelle, de sante des nouveau-nes et de sante infantile dans trois pays: le Bangladesh, l'Indonesie et le Pakistan. Cette etude a ete menee entre novembre 2014 et juin 2018. Nous avons mis au point un prototype d'application numerique apres avoir evalue les besoins des soignants, leurs responsabilites, leur charge de travail, les donnees necessaires a leurs activites quotidiennes et les imperatifs lies a leurs prestations de service. Parmi les methodes employees figuraient des examens documentaires, des discussions de groupes, des entretiens approfondis; une cartographie des donnees fondee sur les registres papier; une observation des professionnels de la sante; des ateliers de cocreation avec les soignants; et enfin, des tests d'utilisabilite. Pour terminer, nous avons effectue une analyse de faisabilite observationnelle afin de mesurer le taux d'adhesion a l'application. Resultats Les chercheurs ont passe au crible un total de 17 registres papier sur l'ensemble des sites, que nous avons transformes en sept modules repris dans une application numerique compatible avec les appareils mobiles. Ces modules correspondaient aux services proposes, dont le recensement des menages, les soins prenatals, la planification familiale, la vaccination, la nutrition et la sante infantile. Au total, 65 soignants ont utilise les modules au cours de l'analyse de faisabilite et le nombre moyen de formulaires soumis chaque semaine etait compris entre 8 et 234, en fonction du soignant et de ses responsabilites. Nous avons egalement observe des variations dans l'utilisation des modules, ce qui montre la necessite d'assurer un suivi permanent aupres des professionnels de la sante. Conclusion Les lecons tirees de cette etude ont permis de faconner des initiatives internationales majeures et d'elaborer un logiciel d'interet mondial. Le deploiement de dispositifs numeriques requiert des applications bien pensees, une bonne gestion du changement et un renforcement des ressources humaines afin d'obtenir et de preserver les avantages pour le systeme de sante. Objetivo Describir un proceso sistematico que permita transformar los registros en papel en un sistema digital optimizado para mejorar la prestacion de servicios y cumplir con los requisitos de informacion. Metodos Se diseno un estudio formativo en torno a los profesionales de la salud primaria que prestan servicios de salud reproductiva, materna, neonatal e infantil en tres paises: de Bangladesh, Indonesia y Pakistan. El estudio se realizodesarrollo entre noviembre de 2014 y junio de 2018. Se desarrollo un prototipo de aplicacion digital despues de realizar una evaluacion sobre las necesidades de las responsabilidades de los profesionales sanitarios, los flujos de trabajo, los requisitos de datos rutinarios y las necesidades de prestacion de servicios. Los metodos incluyeron revisiones de documentos, grupos de discusion, entrevistas en profundidad; mapeo de datos de los registros en papel; observaciones de los profesionales sanitarios; talleres de codiseno con los profesionales sanitarios; y pruebas de usabilidad. Por ultimo, se llevo a cabo una evaluacion de viabilidad observacional para supervisar la aceptacion de la aplicacion. Resultados Los investigadores revisaron un total de 17 registros en papel en todos los sitios, que se adaptaron a siete modulos dentro de una aplicacion digital que funcionaba en dispositivos moviles. Los modulos correspondian a los servicios prestados, como la enumeracion de los hogares, la atencion prenatal, la planificacion familiar, la inmunizacion, la nutricion y la salud infantil. Un total de 65 profesionales sanitarios utilizaron los modulos durante la evaluacion de viabilidad, y la media de envios de formularios semanales oscilo entre 8 y 234, dependiendo del profesional sanitario y de sus responsabilidades. Tambien se observo una variabilidad en el uso de los modulos, lo que requirio un apoyo de seguimiento constante por parte de los profesionales sanitarios. Conclusion Las lecciones aprendidas de este estudio dieron forma a iniciativas globales clave y permitieron crear un programa informatico de interes mundial. El despliegue de los sistemas digitales requiere aplicaciones bien disenadas, la gestion del cambio y el fortalecimiento de los recursos humanos para realizar y mantener los beneficios del sistema sanitario., Introduction Global agencies advocate for the use of information and communication technologies to accelerate progress on priorities, such as the sustainable development goals, the Roadmap for Measurement and Accountability, and [...]

Background: Despite the availability of free routine immunizations in low- and middle-income countries, many children are not completely vaccinated, vaccinated late for age, or drop out from the course of the immunization schedule. Without the technology to model and visualize risk of large datasets, vaccinators and policy makers are unable to identify target groups and individuals at high risk of dropping out; thus default rates remain high, preventing universal immunization coverage. Predictive analytics algorithm leverages artificial intelligence and uses statistical modeling, machine learning, and multidimensional data mining to accurately identify children who are most likely to delay or miss their follow-up immunization visits. Objective: This study aimed to conduct feasibility testing and validation of a predictive analytics algorithm to identify the children who are likely to default on subsequent immunization visits for any vaccine included in the routine immunization schedule. Methods: The algorithm was developed using 47,554 longitudinal immunization records, which were classified into the training and validation cohorts. Four machine learning models (random forest; recursive partitioning; support vector machines, SVMs; and C-forest) were used to generate the algorithm that predicts the likelihood of each child defaulting from the follow-up immunization visit. The following variables were used in the models as predictors of defaulting: gender of the child, language spoken at the child's house, place of residence of the child (town or city), enrollment vaccine, timeliness of vaccination, enrolling staff (vaccinator or others), date of birth (accurate or estimated), and age group of the child. The models were encapsulated in the predictive engine, which identified the most appropriate method to use in a given case. Each of the models was assessed in terms of accuracy, precision (positive predictive value), sensitivity, specificity and negative predictive value, and area under the curve (AUC). Results: Out of 11,889 cases in the validation dataset, the random forest model correctly predicted 8994 cases, yielding 94.9% sensitivity and 54.9% specificity. The C-forest model, SVMs, and recursive partitioning models improved prediction by achieving 352, 376, and 389 correctly predicted cases, respectively, above the predictions made by the random forest model. All models had a C-statistic of 0.750 or above, whereas the highest statistic (AUC 0.791, 95% CI 0.784-0.798) was observed in the recursive partitioning algorithm. Conclusions: This feasibility study demonstrates that predictive analytics can accurately identify children who are at a higher risk for defaulting on follow-up immunization visits. Correct identification of potential defaulters opens a window for evidence-based targeted interventions in resource limited settings to achieve optimal immunization coverage and timeliness. [ABSTRACT FROM AUTHOR]

Background: The Zindagi Mehfooz (safe life; ZM) electronic immunization registry (EIR) is a comprehensive suite of digital health interventions that aims to improve equitable access, timeliness, and coverage of child immunizations through a smartphone-based app for vaccinators, web-based dashboards for supervisors and managers, text message alerts and reminders for caregivers, and a call center. It has been implemented at scale in Sindh Province, Pakistan., Objective: This study aimed to present findings from an evaluation of the ZM-EIR suite of digital health interventions in order to improve data availability and use as a contribution, among other immunization program interventions, to enhanced immunization outcomes for children aged 12-23 months in Sindh Province., Methods: The mixed methods study included (1) analysis of ZM-EIR system data to identify high-, moderate-, and low-adoption and compliance sites; (2) in-depth interviews with caregivers, vaccinators, supervisors, and managers in the Expanded Program for Immunization (EPI); and (3) pre-post outcome evaluation using vaccine coverage from the Multiple Indicator Cluster Surveys (MICS) 2014 and 2018-2019. Key outcomes of interest were improved data availability, use and contribution to immunization outcomes, including receipt of individual antigens (Bacillus Calmette-Guérin [BCG], pentavalent [Penta] 1-3, measles), full immunization (all antigens), and zero-dose children defined as children aged 6-23 months who have not received the first dosage of the diphtheria-pertussis-tetanus 1/Penta vaccine., Results: By registering newborns, providing alerts and reminders, and tracking their immunization completion, the ZM-EIR improved data availability and use in the EPI. The ZM-EIR was well received by EPI administrators, supervisors, vaccinators, and caregivers. The key benefit highlighted by ZM-EIR users was a list of children who missed scheduled vaccines (defaulters). Through greater availability and use of data, the ZM-EIR implementation, as part of a broader package of immunization program-strengthening activities in Sindh Province, may have contributed to an increase in immunization coverage and timeliness for BCG vaccinations and a decrease in zero-dose children in 2018-2019 from 2014. Additional findings from the study included the dual burden of reporting on paper and gender-related considerations of female caregivers not wanting to provide their phone numbers to male vaccinators, creating barriers to greater uptake of the ZM-EIR., Conclusions: The ZM-EIR is a promising technology platform that has increased the availability and use of immunization data, which may have contributed, along with other intensive immunization program interventions, to improvements in immunization outcomes through systematic registration of children, alerts and reminders, and increased use of data for planning and monitoring by the EPI., Trial Registration: ISRCTN Registry ISRCTN23078223; https://doi.org/10.1186/ISRCTN23078223., (©Patricia Mechael, Sara Gilani, Ahsan Ahmad, Amnesty LeFevre, Diwakar Mohan, Asra Memon, Mubarak Taighoon Shah, Danya Arif Siddiqi, Subhash Chandir, Riswana Soundardjee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.10.2024.)

Competing Interests: We declare no competing interests.