Data Equity to Advance Health and Health Equity in Low- and Middle-Income Countries: A Scoping Review

Health Data Sciences and Cardiovascular Disease in Africa: Needs and the Way Forward

PURPOSE OF REVIEW

The rising burden of cardiovascular disease (CVD) in Africa is of great concern. Health data sciences is a rapidly developing field which has the potential to improve health outcomes, especially in low-middle income countries with burdened healthcare systems. We aim to explore the current CVD landscape in Africa, highlighting the importance of health data sciences in the region and identifying potential opportunities for application and growth by leveraging health data sciences to improve CVD outcomes.

RECENT FINDINGS

While there have been a number of initiatives aimed at developing health data sciences in Africa over the recent decades, the progress and growth are still in their early stages. Its maximum potential can be leveraged through adequate funding, advanced training programs, focused resource allocation, encouraging bidirectional international partnerships, instituting best ethical practices, and prioritizing data science health research in the region. The findings of this review explore the current landscape of CVD and highlight the potential benefits and utility of health data sciences to address CVD challenges in Africa. By understanding and overcoming the barriers associated with health data sciences training, research, and application in the region, focused initiatives can be developed to promote research and development. These efforts will allow policymakers to form informed, evidence-based frameworks for the prevention and management of CVDs, and ultimately result in improved CVD outcomes in the region.

Improvements in data completeness in health information systems reveal racial inequalities: longitudinal national data from hospital admissions in Brazil 2010-2022

BACKGROUND

Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals.

METHODS

We conducted a longitudinal analysis, examining hospital admission data from Brazil's Hospital Information System (SIH) between 2010 and 2022, and analysed trends in reporting completeness and racial inequalities. These hospitalization records were examined based on year, quarter, cause of admission (using International Classification of Diseases (ICD-10) codes), and race/color (categorized as Black, White, or missing). We examined the patterns in hospitalization rates and the prevalence of missing data over a period of time.

RESULTS

Over the study period, there was a notable improvement in data completeness regarding race/color in hospital admissions in Brazil. The proportion of missing values on race decreased from 34.7% in 2010 to 21.2% in 2020. As data completeness improved, racial inequalities in hospitalization rates became more evident - across several causes, including assaults, tuberculosis, hypertensive diseases, at-risk hospitalizations during pregnancy and motorcycle accidents.

CONCLUSIONS

The study highlights the critical role of data quality in identifying and addressing racial health inequalities. Improved data completeness has revealed previously hidden inequalities in health records, emphasizing the need for comprehensive data collection to inform equitable health policies and interventions. Policymakers working in areas where socioeconomic data reporting (including on race and ethnicity) is suboptimal, should address data completeness to fully understand the scale of health inequalities.

Effect of Face Mask on Lowering COVID-19 Incidence in School Settings: A Systematic Review

BACKGROUND

The emergence of COVID-19 resulted in a substantial loss of education because of global school closures. Face masks are a potential measure to restrain the COVID-19 spread; therefore, this paper evaluated the effectiveness of face masks in reducing COVID-19 incidence in school settings.

METHODS

A systematic review was conducted by searching the literature in the Cochrane COVID-19 Study Register and the World Health Organization COVID-19 global literature. Data were summarized in tabular forms, and the findings were presented as narrative synthesis.

RESULTS

A total of 15,709 records were retrieved. The screening and selection led to the inclusion of 12 observational and 2 quasi-experimental studies. Nine studies were conducted in different states, counties, or districts of the United States, and the remaining 5 were reported from Germany, Finland, Spain, and the United Kingdom. The results of 10 out of 14 studies favored mask use in reducing school COVID-19 incidence. Three studies found no link between mask use and COVID-19 incidences, whereas 1 quasi-experimental study noted a higher COVID-19 incidence with mask use in students aged 6-11 years than no use of mask among preschool children aged 3-5 years.

CONCLUSION

Mask mandates may lessen the incidence of respiratory infectious diseases in school settings during a pandemic; more well-designed studies are warranted to clarify further the evidence regarding mask use in school settings.

Centering Digital Health Equity During Technology Innovation: Protocol for a Comprehensive Scoping Review of Evidence-Based Tools and Approaches

BACKGROUND

In the rush to develop health technologies for the COVID-19 pandemic, the unintended consequence of digital health inequity or the inability of priority communities to access, use, and receive equal benefits from digital health technologies was not well examined.

OBJECTIVE

This scoping review will examine tools and approaches that can be used during digital technology innovation to improve equitable inclusion of priority communities in the development of digital health technologies. The results from this study will provide actionable insights for professionals in health care, health informatics, digital health, and technology development to proactively center equity during innovation.

METHODS

Based on the Arksey and O'Malley framework, this scoping review will consider priority communities' equitable involvement in digital technology innovation. Bibliographic databases in health, medicine, computing, and information sciences will be searched. Retrieved citations will be double screened against the inclusion and exclusion criteria using Covidence (Veritas Health Innovation). Data will be charted using a tailored extraction tool and mapped to a digital health innovation pathway defined by the Centre for eHealth Research roadmap for eHealth technologies. An accompanying narrative synthesis will describe the outcomes in relation to the review's objectives.

RESULTS

This scoping review is currently in progress. The search of databases and other sources returned a total of 4868 records. After the initial screening of titles and abstracts, 426 studies are undergoing dual full-text review. We are aiming to complete the full-text review stage by May 30, 2024, data extraction in October 2024, and subsequent synthesis in December 2024. Funding was received on October 1, 2023, from the Centre for Health Equity Incubator Grant Scheme, University of Melbourne, Australia.

CONCLUSIONS

This paper will identify and recommend a series of validated tools and approaches that can be used by health care stakeholders and IT developers to produce equitable digital health technology across the Centre for eHealth Research roadmap. Identified evidence gaps, possible implications, and further research will be discussed.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/53855.

A guide to outcome evaluation of simulation-based education programmes in low and middle-income countries

Evaluation is a vital part of any learning activity and is essential to optimize and improve educational programmes. It should be considered and prioritized prior to the implementation of any learning activity. However, comprehensive programme evaluation is rarely conducted, and there are numerous barriers to high-quality evaluation. This review provides a framework for conducting outcome evaluation of simulation-based education programmes in low and middle-income countries (LMICs). The basis of evaluation, including core ideas of theory, purpose and structure are outlined, followed by an examination of the levels and healthcare applications of the Kirkpatrick model of evaluation. Then, methods of conducting evaluation of simulation-based education in LMICs are discussed through the lens of a successful surgical simulation programme in Myanmar, a lower-middle-income country. The programme involved the evaluation of 11 courses over 4 years in Myanmar and demonstrated evaluation at the highest level of the Kirkpatrick model. Reviewing this programme provides a bridge between evaluation theory and practical implementation. A range of evaluation methods are outlined, including surveys, interviews, and clinical outcome measurement. The importance of a mixed-methods approach, enabling triangulation of quantitative and qualitative analysis, is highlighted, as are methods of analysing data, including statistical and thematic analysis. Finally, issues and challenges of conducting evaluation are considered, as well as strategies to overcome these barriers. Ultimately, this review informs readers about evaluation theory and methods, grounded in a practical application, to enable other educators in low-resource settings to evaluate their own activities.

Secondary data for global health digitalisation

Substantial opportunities for global health intelligence and research arise from the combined and optimised use of secondary data within data ecosystems. Secondary data are information being used for purposes other than those intended when they were collected. These data can be gathered from sources on the verge of widespread use such as the internet, wearables, mobile phone apps, electronic health records, or genome sequencing. To utilise their full potential, we offer guidance by outlining available sources and approaches for the processing of secondary data. Furthermore, in addition to indicators for the regulatory and ethical evaluation of strategies for the best use of secondary data, we also propose criteria for assessing reusability. This overview supports more precise and effective policy decision making leading to earlier detection and better prevention of emerging health threats than is currently the case.

Digital Health Equity: Addressing Power, Usability, and Trust to Strengthen Health Systems

BACKGROUND

Without specific attention to health equity considerations in design, implementation, and evaluation, the rapid expansion of digital health approaches threatens to exacerbate rather than ameliorate existing health disparities.

METHODS

We explored known factors that increase digital health inequity to contextualize the need for equity-centered informatics. This work used a narrative review method to summarize issues about inequities in digital health and to discuss future directions for researchers and clinicians. We searched literature using a combination of relevant keywords (e.g., "digital health", "health equity", etc.) using PubMed and Google Scholar.

RESULTS

We have highlighted strategies for addressing medical marginalization in informatics according to vectors of power such as race and ethnicity, gender identity and modality, sexuality, disability, housing status, citizenship status, and criminalization status.

CONCLUSIONS

We have emphasized collaboration with user and patient groups to define priorities, ensure accessibility and localization, and consider risks in development and utilization of digital health tools. Additionally, we encourage consideration of potential pitfalls in adopting these diversity, equity, and inclusion (DEI)-related strategies.

Applying the iDARE Methodology in Uganda, Kenya, and Tanzania to Improve Health Outcomes During the COVID-19 Pandemic

INTRODUCTION

We introduce the iDARE methodology and present the results of iDARE implementation in Uganda, Kenya, and Tanzania during the coronavirus disease (COVID-19) pandemic. IDARE METHODOLOGY: iDARE drives locally led solutions that address barriers to achieving improved health outcomes. WI-HER supported the governments of Uganda, Kenya, and Tanzania, to design and implement solutions to improve (1) HIV health outcomes, (2) gender-based violence identification and response, and (3) mass drug administration coverage, respectively.

RESULTS

In Uganda, the iDARE team at Nagongera Health Center IV increased viral load suppression (VLS) among actively enrolled men in care from 65% to 95% and increased VLS among actively enrolled children in care from 60% to 96% in 12 months. In 11 months, the Mulanda Health Center IV iDARE team increased VLS among actively enrolled men in care from 85% to 93% and actively enrolled children in care from 73% to 96%. In Kenya, 8 facility iDARE teams improved identification, management, and response for gender-based violence survivors by a monthly average of 642% in 10 months. Additionally, the identification, management, and response for male survivors of gender-based violence increased from an average of 8 to 188 men per month and from an average of 81 to 364 women per month. In Tanzania, the government applied iDARE to improve mass drug administration (MDA) access and uptake among school-age children. Eighteen percent of the children (equal male and female) had missed or refused treatment during school-based MDA. After 1 month of application of iDARE, the 4 schools achieved 99% MDA uptake among registered children (enrolled and nonenrolled).

DISCUSSION

Due to the various lockdowns, restrictions, and safety implications during the COVID-19 pandemic, iDARE was used to rapidly adjust from planned in-person to sometimes virtual engagements. Despite these challenges, iDARE demonstrated improvements in Uganda, Kenya, and Tanzania.