Lessons learned from early implementation of the Growing Expertise in E-health Knowledge and Skills (GEEKS) program in Nigeria, 2019 - 2021.

Introduction: the Growing Expertise in E-health Knowledge and Skills (GEEKS) program is an applied apprenticeship program that aims to improve informatics capacity at various levels of the national health system and create a sustainable informatics workforce. Nigeria adapted the GEEKS model in 2019 as a mechanism to strengthen data quality and use of routine immunization (RI) and vaccine-preventable disease (VPD) surveillance data among Expanded Programme on Immunization (EPI) staff. Since the start of the GEEKS-EPI program, there has not been a formal assessment conducted to measure the extent to which GEEKS-EPI has been able to build local informatics workforce capacity and strengthen RI and VPD surveillance (VPDS) data quality and use in Nigeria. Methods: we conducted a qualitative assessment to inform the extent to which GEEKS-EPI has been able to build informatics skillsets to enhance local workforce capacity, foster collaboration across government agencies, and create a sustainable informatics workforce in Nigeria. In-Depth Interviews (IDIs) and Focus Group Discussions (FGDs) were held with GEEKS-EPI supervisors, mentors, and mentees from previous GEEKS-EPI cohorts. Results: while there were challenges reported during early implementation of the GEEKS-EPI program in Nigeria, particularly early on in the COVID-19 pandemic, participants and supervisors reported that the fellowship provided a framework for building a sustainable RI and VPDS informatics workforce through regular mentorship, peer-to-peer exchanges and Subject Matter Expert (SME)-led trainings. Conclusion: lessons learned from early implementation of GEEKS-EPI in Nigeria will help to inform its implementation in other countries, where strengthened national RI and VPDS informatics capacity is the primary objective.

Researching, co-creating and testing innovations in paper-based health information systems (PHISICC) to support health workers' decision-making: protocol of a multi-country, transdisciplinary, mixed-methods research programme in three sub-Saharan countries.

BACKGROUND: Health information systems are crucial to provide data for decision-making and demand for data is constantly growing. However, the link between data and decisions is not always rational or linear and the management of data ends up overloading frontline health workers, which may compromise quality of healthcare delivery. Despite limited evidence, there is an increasing push for the digitalization of health information systems, which poses enormous challenges, particularly in remote, rural settings in low- and middle-income countries. Paper-based tools will continue to be used in combination with digital solutions and this calls for efforts to make them more responsive to local needs. Paper-based Health Information Systems in Comprehensive Care (PHISICC) is a transdisciplinary, multi-country research initiative to create and test innovative paper-based health information systems in three sub-Saharan African countries. METHODS/DESIGN: The PHISICC initiative is being carried out in remote, rural settings in Côte d'Ivoire, Mozambique and Nigeria through partnership with ministries of health and research institutions. We began with research syntheses to acquire the most up-to-date knowledge on health information systems. These were coupled with fieldwork in the three countries to understand the current design, patterns and contexts of use, and healthcare worker perspectives. Frontline health workers, with designers and researchers, used co-creation methods to produce the new PHISICC tools. This suite of tools is being tested in the three countries in three cluster-randomized controlled trials. Throughout the project, we have engaged with a wide range of stakeholders and have maintained the highest scientific standards to ensure that results are relevant to the realities in the three countries. DISCUSSION: We have deployed a comprehensive research approach to ensure the robustness and future policy uptake of findings. Besides the innovative PHISICC paper-based tools, our process is in itself innovative. Rather than emphasizing the technical dimensions of data management, we focused instead on frontline health workers' data use and decision-making. By tackling the whole scope of primary healthcare areas rather than a subset of them, we have developed an entirely new design and visual language for a suite of tools across healthcare areas. The initiative is being tested in remote, rural areas where the most vulnerable live.

Does an innovative paper-based health information system (PHISICC) improve data quality and use in primary healthcare? Protocol of a multicountry, cluster randomised controlled trial in sub-Saharan African rural settings.

INTRODUCTION: Front-line health workers in remote health facilities are the first contact of the formal health sector and are confronted with life-saving decisions. Health information systems (HIS) support the collection and use of health related data. However, HIS focus on reporting and are unfit to support decisions. Since data tools are paper-based in most primary healthcare settings, we have produced an innovative Paper-based Health Information System in Comprehensive Care (PHISICC) using a human-centred design approach. We are carrying out a cluster randomised controlled trial in three African countries to assess the effects of PHISICC compared with the current systems. METHODS AND ANALYSIS: Study areas are in rural zones of Côte d'Ivoire, Mozambique and Nigeria. Seventy health facilities in each country have been randomly allocated to using PHISICC tools or to continuing to use the regular HIS tools. We have randomly selected households in the catchment areas of each health facility to collect outcomes' data (household surveys have been carried out in two of the three countries and the end-line data collection is planned for mid-2021). Primary outcomes include data quality and use, coverage of health services and health workers satisfaction; secondary outcomes are additional data quality and use parameters, childhood mortality and additional health workers and clients experience with the system. Just prior to the implementation of the trial, we had to relocate the study site in Mozambique due to unforeseen logistical issues. The effects of the intervention will be estimated using regression models and accounting for clustering using random effects. ETHICS AND DISSEMINATION: Ethics committees in Côte d'Ivoire, Mozambique and Nigeria approved the trials. We plan to disseminate our findings, data and research materials among researchers and policy-makers. We aim at having our findings included in systematic reviews on health systems interventions and future guidance development on HIS. TRIAL REGISTRATION NUMBER: PACTR201904664660639; Pre-results.

Implementing the routine immunisation data module and dashboard of DHIS2 in Nigeria, 2014-2019.

In 2010, Nigeria adopted the use of web-based software District Health Information System, V.2 (DHIS2) as the platform for the National Health Management Information System. The platform supports real-time data reporting and promotes government ownership and accountability. To strengthen its routine immunisation (RI) component, the US Centers for Disease Control and Prevention (CDC) through its implementing partner, the African Field Epidemiology Network-National Stop Transmission of Polio, in collaboration with the Government of Nigeria, developed the RI module and dashboard and piloted it in Kano state in 2014. The module was scaled up nationally over the next 4 years with funding from the Bill & Melinda Gates Foundation and CDC. One implementation officer was deployed per state for 2 years to support operations. Over 60 000 RI healthcare workers were trained on data collection, entry and interpretation and each local immunisation officer in the 774 local government areas (LGAs) received a laptop and stock of RI paper data tools. Templates for national-level and state-level RI bulletins and LGA quarterly performance tools were developed to promote real-time data use for feedback and decision making, and enhance the performance of RI services. By December 2017, the DHIS2 RI module had been rolled out in all 36 states and the Federal Capital Territory, and all states now report their RI data through the RI Module. All states identified at least one government DHIS2 focal person for oversight of the system's reporting and management operations. Government officials routinely collect RI data and use them to improve RI vaccination coverage. This article describes the implementation process-including planning and implementation activities, achievements, lessons learnt, challenges and innovative solutions-and reports the achievements in improving timeliness and completeness rates.