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Objectives: This article delves into the challenges of medical data collection during the COVID-19 pandemic in developing countries, using Nigeria as a case study. It emphasizes how data collection impacts research quality, reliability, and validity. Methods: Qualitative research utilizing purposive sampling was employed to explore experiences in designing a diagnostic tool for febrile diseases in Nigeria. A questionnaire with selectable and open-ended questions was utilized for data collection, and 23 respondents participated. Results: Among 74 potential participants, 23 valid responses were gathered, revealing significant themes related to experiences and challenges in medical data collection. A multidisciplinary team approach proved beneficial, fostering collaboration, enhancing knowledge, and promoting positive experiences. Despite challenges with paper questionnaires, most participants preferred them for ease of use. Connectivity issues hindered timely data uploading and disrupted virtual meetings. Conclusion: Innovative and flexible strategies, such as a blended data collection approach and well-coordinated teams, were vital in overcoming challenges. Electronic data collection tools, reminders, and effective communication played key roles, leading to positive outcomes. This study provides valuable insights for researchers and practitioners involved in data collection, particularly in developing countries like Nigeria.

Electronic medical records (EMR) are extensively used in developed countries to manage patient records and facilitate consultations and follow-up of treatment. This has resulted in centralised databases where different services and clinicians can quickly access patient data to support healthcare delivery. However, adoption and usage of EMR in developing countries is not common and, in most cases, non-existent. Clinicians are dependent on patients keeping their own records manually with no centralised database to manage and control the patient medical history. The key objective of this study was to investigate the propensity of clinicians and senior management personnel in healthcare facilities to adopt EMR and evaluate the contextual factors that impact or impede adoption. Using Davis's technology adoption model extended with other factors, this study determined if contextual or situational factors are associated with barriers that impede adoption of EMRs in developing countries. Using a cross-sectional quantitative research approach, a questionnaire was designed to collect data across four states in the Niger Delta region of Nigeria. Stratified random sampling was used to select healthcare facilities that participated in the survey and selection of respondents from each healthcare facility. Data was collected by trained research assistants and a total of 1,177 valid responses were received and analysed using factor analysis and multiple regression analysis. The results from the analysis show that usefulness, critical success factors, awareness and relative advantage significantly influence clinicians' intention to adopt EMRs. Surprisingly, infrastructure availability was not statistically significant. Meanwhile, risk and data security both negatively influence adoption, indicating that user perception of risk and safety of their data decreases their propensity to adopt EMRs. The results from this study suggests that usefulness and anticipated success factors in facilitating operations within healthcare facilities have a great influence on user adoption of EMRs. Awareness, training and education of users on the effectiveness of EMRs and their usefulness will increase adoption. The results will be beneficial in helping government and healthcare leaders formulate policies that will guide and support adoption of EMR. Other policy recommendations and suggestions for future research were also proffered.

BackgroundHealth workers in low- and middle-income countries are increasingly demanded to collect more and more data to report them to higher levels of the health information system (HIS), in detriment of useful data for clinical and public health decision-making, potentially compromising the quality of their health care provison. In order to support health workers' decision-making, we engaged with partners in Côte d'Ivoire, Mozambique and Nigeria in a research project to conceive, design, produce, implement and test paper-based health information tools: the PHISICC tools. Our aim was to understand the use of PHISICC tools by health workers and to improve them based on their feedback.MethodsThe design Health Facility Laboratories (HF Labs) in Côte d'Ivoire and in Nigeria were set up after months of use of PHISICC tools. Activities were structured in three phases or ‘sprints' of co-creative research. We used a transdisciplinary approach, including anthropology and Human Centered Design (HCD), observations, shadowing, structured interviews and co-creation.ResultsHealth workers appreciated the standardization of the tools across different health care areas, with a common visual language that optimized use. Several design issues were raised, in terms of formats and contents. They strongly appreciated how the PHISICC registers guided their clinical decision-making and how it facilitated tallying and counting for monthly reporting. However, adherence to new procedures was not universal. The co-creation sessions resulted in modifications to the PHISICC tools of out-patient care and postnatal care.DiscussionAlthough health systems and systemic thinking allowed the teams to embrace complexity, it was the HCD approach that actually produced a shift in researchers' mind-set: from HIS as data management tools to HIS as quality of care instruments. HCD allowed navigating the complexity of health systems interventions due to its capacity to operate change: it not only allowed us to understand how the PHISICC tools were used but also how to further improve them. In the absence of (or even with) an analytical health systems framework, HCD approaches can work in real-life situations for the ideation, testing and implementation of interventions to improve health systems and health status outcomes.

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.

INTRODUCTION: In developing countries, community health workers (CHWs) are essential, for provision of behaviour change communication towards prevention of coronavirus 2019 (COVID-19) infection at rural grassroots level. We aimed at assessing their level of knowledge and practice of preventive measures in a developing country setting. METHODS: total enumeration of all CHWs in a rural local government area in southern Nigeria was carried out, using cross-sectional descriptive study design. Pretested self-administered 15-item questionnaire was used to assess knowledge of COVID-19 including basic epidemiology, virology, preventive measures and use of personal protective equipment (PPE). Practice of preventive measures was also assessed. Each correct response to knowledge question contributed one unit to the total score which was converted to percentage. Total knowledge score of 50% or greater was considered satisfactory. RESULTS: complete data was obtained from eighty-six (86) respondents with mean age of 36.3±8.9 years (18-54 years). Mean total knowledge score was 28.14 ± 12.8% (6.7 to 53.3%), and 9.3% (n = 8) had score of at least 50%. Correct responses to appropriate sequence of putting on and removing personal protective equipment (PPE) were 5.8% (n = 5) and 8.1% (n = 7), respectively. Regular practice of use of face masks, goggles, gloves, and hand hygiene was found to be 50% (n = 43), 12.8% (n = 11), 30.2% (n = 26), and 56.4% (n = 48), respectively. CONCLUSION: community health workers are grossly underprepared for provision of health education on COVID-19, due to their poor level of knowledge. Their capacity building through workshops and effective continuing education program are urgently needed.