Research gaps in routine health information system design barriers to data quality and use in low- and middle-income countries: A literature review

[Quality of health information in Mexico in the OECD context: 2017-2021]

OBJECTIVE

To evaluate the health information system (HIS) of Mexico according to the information reported to the Organization for Economic Co-operation and Development (OECD). The ultimate goal is to identify the improvements that should be considered.

METHOD

Health indicators published by the OECD (2017 to 2021) are analyzed according to 11 thematic groups. Coverage (quantity and type of indicators reported by thematic group) and quality of information were assessed, according to OECD guidelines.

RESULTS

Mexico reported annually 14 of 378 indicators (3.7%), and discontinuously 204. In no group were all indicators reported annually, except for the two on COVID-19. Three out of 88 were reported annually on use of services; and none on health status, quality of care and pharmaceutical market. Twelve indicators (5.5% of those reported by Mexico, 3.2% of the full OECD set) had optimal quality and annual reporting. 57.7% of the reported indicators had at least one quality defect.

CONCLUSIONS

Within the framework of the standards set by the OECD, of which Mexico is a member, the Mexican HIS presents significant deficits in coverage and quality of information. These results should be considered to implement improvement initiatives.

Applying a zero-corrected, gravity model estimator reduces bias due to heterogeneity in healthcare utilization in community-scale, passive surveillance datasets of endemic diseases

Data on population health are vital to evidence-based decision making but are rarely adequately localized or updated in continuous time. They also suffer from low ascertainment rates, particularly in rural areas where barriers to healthcare can cause infrequent touch points with the health system. Here, we demonstrate a novel statistical method to estimate the incidence of endemic diseases at the community level from passive surveillance data collected at primary health centers. The zero-corrected, gravity-model (ZERO-G) estimator explicitly models sampling intensity as a function of health facility characteristics and statistically accounts for extremely low rates of ascertainment. The result is a standardized, real-time estimate of disease incidence at a spatial resolution nearly ten times finer than typically reported by facility-based passive surveillance systems. We assessed the robustness of this method by applying it to a case study of field-collected malaria incidence rates from a rural health district in southeastern Madagascar. The ZERO-G estimator decreased geographic and financial bias in the dataset by over 90% and doubled the agreement rate between spatial patterns in malaria incidence and incidence estimates derived from prevalence surveys. The ZERO-G estimator is a promising method for adjusting passive surveillance data of common, endemic diseases, increasing the availability of continuously updated, high quality surveillance datasets at the community scale.

The transition of human resources for health information systems from the MDGs into the SDGs and the post-pandemic era: reviewing the evidence from 2000 to 2022

BACKGROUND

This review paper offers a policy-tracing trend analysis of national experiences among low- and middle-income countries in strengthening human resources for health information systems (HRHIS). This paper draws on evidence from the last two decades and applies a modified Bardach's policy analysis framework. A timely review of the evidence on HRHIS and underlying data systems is needed now more than ever, given the halfway mark of the Global Strategy on Human Resources for Health: Workforce 2030 and the protracted COVID-19 pandemic and other global health emergencies, over and above the increasing need for health and care workers to provide essential health services.

MAIN TEXT

Considering World Health Assembly resolutions and HRH-related global developments between 2000 and 2022, we targeted peer-reviewed and gray literature covering the inception, impact, bottlenecks, and gaps of HRHIS. We also considered results from a Bill and Melinda Gates Foundation-funded project that assessed HRH data systems in 21 countries and the use of HRH data and information for policy, planning, and management. Aligned with the National Health Workforce Accounts (NHWA), we identify priority themes related to digital priorities for HRHIS and governance/leadership and present case studies of five countries that pursued different pathways to successfully develop their HRHIS. Over the last two decades, considerable progress has been achieved through a scaled-up implementation of HRHIS combined with the skills needed to analyze and use data, sustain systems functionality, and make systematic improvements over time. Global health development aid investments and technical innovations have led to advancements in HRHIS, district health information software (DHIS2), and partner collaborations during the HIV/AIDS, Ebola, and COVID-19 crises. Although the progressive implementation of NHWA continues to steer country-level efforts through standardized indicators and regular reporting, traditional challenges remain, such as data systems fragmentation, lack of interoperability between systems, and underutilization of reported data. Encouragingly, some countries demonstrate strong governance and leadership capacities and others strong HRHIS digital capacities. Both HRH and health service data are needed to inform on-demand decisions during times of emergencies and pandemics as well as during routine essential health services delivery. Evidence-based examples from distinctive countries demonstrate that reliable HRHIS is achievable for better planning and management of the health and care workforce.

Data Quality in Health Research: Integrative Literature Review

BACKGROUND

Decision-making and strategies to improve service delivery must be supported by reliable health data to generate consistent evidence on health status. The data quality management process must ensure the reliability of collected data. Consequently, various methodologies to improve the quality of services are applied in the health field. At the same time, scientific research is constantly evolving to improve data quality through better reproducibility and empowerment of researchers and offers patient groups tools for secured data sharing and privacy compliance.

OBJECTIVE

Through an integrative literature review, the aim of this work was to identify and evaluate digital health technology interventions designed to support the conducting of health research based on data quality.

METHODS

A search was conducted in 6 electronic scientific databases in January 2022: PubMed, SCOPUS, Web of Science, Institute of Electrical and Electronics Engineers Digital Library, Cumulative Index of Nursing and Allied Health Literature, and Latin American and Caribbean Health Sciences Literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and flowchart were used to visualize the search strategy results in the databases.

RESULTS

After analyzing and extracting the outcomes of interest, 33 papers were included in the review. The studies covered the period of 2017-2021 and were conducted in 22 countries. Key findings revealed variability and a lack of consensus in assessing data quality domains and metrics. Data quality factors included the research environment, application time, and development steps. Strategies for improving data quality involved using business intelligence models, statistical analyses, data mining techniques, and qualitative approaches.

CONCLUSIONS

The main barriers to health data quality are technical, motivational, economical, political, legal, ethical, organizational, human resources, and methodological. The data quality process and techniques, from precollection to gathering, postcollection, and analysis, are critical for the final result of a study or the quality of processes and decision-making in a health care organization. The findings highlight the need for standardized practices and collaborative efforts to enhance data quality in health research. Finally, context guides decisions regarding data quality strategies and techniques.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1101/2022.05.31.22275804.

MAPPinfo - mapping quality of health information: Validation study of an assessment instrument

BACKGROUND

Health information is a prerequisite for informed choices-decisions, made by individuals about their own health based on knowledge and in congruence with own preferences. Criteria for development, content and design have been defined in a corresponding guideline. However, no instruments exist that provide reasonably operationalised measurement items. Therefore, we drafted the checklist, MAPPinfo, addressing the existing criteria with 19 items.

OBJECTIVES

The current study aimed to validate MAPPinfo.

METHODS

Five substudies were conducted subsequently at the Martin Luther University Halle-Wittenberg, Germany and the Medical University of Graz, Austria: (1) to determine content validity through expert reviews of the first draft, (2) to determine feasibility using 'think aloud' in piloting with untrained users, (3) to determine inter-rater reliability and criterion validity through a pretest on 50 health information materials, (4) to determine construct validity using 50 developers' self-declarations about development methods as a reference standard, (5) to determine divergent validity in comparison with the Ensuring Quality Information for Patients (EQIP) (expanded) Scale. The analyses used were qualitative methods and correlation-based methods for determining both inter-rater reliability and validity.

RESULTS

The instrument was considered by experts to operationalise the existing guidelines convincingly. Health and nursing science students found it easy to understand and use. It also had good interrater reliability (mean of T coefficients = .79) and provided a very good estimate of the reference standard (Spearman's rho = .89), implying sound construct validity. Finally, comparison with the EQIP instrument revealed important and distinct areas of similarities and differences.

CONCLUSIONS

The new instrument is ready for use as a screening instrument without the need for training. According to its underpinning concept the instrument exclusively comprises items which are justified by either ethics or research evidence, implying negligence of not yet evidence based, however, potentially important criteria. Further research is needed to complete the body of evidence-based criteria, aiming at an extension of the guideline and MAPPinfo.

TRIAL REGISTRATION NUMBER

AsPredicted22546; date of registration: 24 July 2019.

The Vinyasa Tool for mHealth Solutions: Supporting Human-Centered Design in Nascent Digital Health Ecosystems

BACKGROUND

mHealth (mobile health) systems have been deployed widely in low- and middle-income countries (LMICs) for health system strengthening, requiring considerable resource allocation. However, most solutions have not achieved scale or sustainability. Poor usability and failure to address perceived needs are among the principal reasons mHealth systems fail to achieve acceptance and adoption by health care workers. A human-centered design approach to improving mHealth system use requires an exploration of users' perceptions of mHealth systems, including the environmental, user-related, and technological aspects of a system. At present, there is a dearth of contextually intelligent tools available to mHealth developers that can guide such exploration before full-scale development and deployment.

OBJECTIVE

To develop a tool to aid optimization of mHealth solutions in LMICs to facilitate human-centered design and, consequently, successful adoption.

METHODS

We collated findings and themes from key qualitative studies on mHealth deployment in LMICs. We then used the Informatics Stack framework by Lehmann to label, sort, and collate findings and themes into a list of questions that explore the environment, users, artifacts, information governance, and interoperability of mHealth systems deployed in LMICs.

RESULTS

We developed the Vinyasa Tool to aid qualitative research about the need and usability of mHealth solutions in LMICs. The tool is a guide for focus group discussions and key informant interviews with community-based health care workers and primary care medical personnel who use or are expected to use proposed mHealth solutions. The tool consists of 71 questions organized in 11 sections that unpack and explore multiple aspects of mHealth systems from the perspectives of their users. These include the wider world and organization in which an mHealth solution is deployed; the roles, functions, workflow, and adoption behavior of a system's users; the security, privacy, and interoperability afforded by a system; and the artifacts of an information system-the data, information, knowledge, algorithms, and technology that constitute the system. The tool can be deployed in whole or in part, depending on the context of the study.

CONCLUSIONS

The Vinyasa Tool is the first such comprehensive qualitative research instrument incorporating questions contextualized to the LMIC setting. We expect it to find wide application among mHealth developers, health system administrators, and researchers developing and deploying mHealth tools for use by patients, providers, and administrators. The tool is expected to guide users toward human-centered design with the goal of improving relevance, usability, and, therefore, adoption.

Inaccessibility and low maintenance of medical data archive in low-middle income countries: Mystery behind public health statistics and measures

INTRODUCTION

Africa bears the largest burden of communicable and non-communicable diseases globally, yet it contributes only about 1 % of global research output, partly because of inaccessibility and low maintenance of medical data. Data is widely recognized as a crucial tool for improvement of population health. Despite the introduction of electronic health data systems in low-and middle-income countries (LMICs) to improve data quality, some LMICs still lack an efficient system to collect and archive data. This study aims to examine the underlying causes of data archive inaccessibility and poor maintenance in LMICS, and to highlight sustainable mitigation measures.

METHOD

Authors conducted a comprehensive search on PubMed, Google scholar, organization websites using the search string "data archive" or "medical data" or "public health statistics" AND "challenges" AND "maintenance" AND "Low Middle Income Countries" or "LMIC". to Identify relevant studies and reports to be included in our review. All articles related data archive in low and middle income countries were considered without restrictions due to scarcity of data.

RESULT

Medical data archives in LMICs face challenges impacting data quality. Insufficient training, organizational constraints, and limited infrastructure hinder archive maintenance. To improve, support for public datasets, digital literacy, and technology infrastructure is needed. Standardization, cloud solutions, and advanced technologies can enhance data management, while capacity building and training programs are crucial.

CONCLUSION

The creation and maintenance of data archives to facilitate the storage of retrospective datasets is critical to create reliable and consistent data to better equip the development of resilient health systems and surveillance of diseases in LMICs.

Refining the Performance of Routine Information System Management (PRISM) framework for data use at the local level: An integrative review

INTRODUCTION

Foundational to a well-functioning health system is a strong routine health information system (RHIS) that informs decisions and actions at all levels of the health system. In the context of decentralization across low- and middle-income countries, RHIS has the promise of supporting sub-national health staff to take data-informed actions to improve health system performance. However, there is wide variation in how "RHIS data use" is defined and measured in the literature, impeding the development and evaluation of interventions that effectively promote RHIS data use.

METHODS

An integrative review methodology was used to: (1) synthesize the state of the literature on how RHIS data use in low- and middle-income countries is conceptualized and measured; (2) propose a refined RHIS data use framework and develop a common definition for RHIS data use; and (3) propose improved approaches to measure RHIS data use. Four electronic databases were searched for peer-reviewed articles published between 2009 and 2021 investigating RHIS data use.

RESULTS

A total of 45 articles, including 24 articles measuring RHIS data use, met the inclusion criteria. Less than half of included articles (42%) explicitly defined RHIS data use. There were differences across the literature whether RHIS data tasks such as data analysis preceded or were a part of RHIS data use; there was broad consensus that data-informed decisions and actions were essential steps within the RHIS data use process. Based on the synthesis, the Performance of Routine Information System Management (PRISM) framework was refined to specify the steps of the RHIS data use process.

CONCLUSION

Conceptualizing RHIS data use as a process that includes data-informed actions emphasizes the importance of actions in improving health system performance. Future studies and implementation strategies should be designed with consideration for the different support needs for each step of the RHIS data use process.

Understanding maternity care providers' use of data in Southern Tanzania

INTRODUCTION

Health information management system data is collected for national planning and evaluation but is rarely used for healthcare improvements at subnational or facility-level in low-and-middle-income countries. Research suggests that perceived data quality and lack of feedback are contributing factors. We aimed to understand maternity care providers' perceptions of data and how they use it, with a view to co-design interventions to improve data quality and use.

METHODS

We based our research on constructivist grounded theory. We conducted 14 in-depth interviews, two focus group discussions with maternity care providers and 48 hours of observations in maternity wards to understand maternity providers' interaction with data in two rural hospitals in Southern Tanzania. Constant comparative data analysis was applied to develop initial and focused codes, subcategories and categories were continuously validated through peer and member checks.

RESULTS

Maternity care providers found routine health information data of little use to reconcile demands from managers, the community and their challenging working environment within their daily work. They thus added informal narrative documentation sources. They created alternative narratives through data of a maternity care where mothers and babies were safeguarded. The resulting documentation system, however, led to duplication and increased systemic complexity.

CONCLUSIONS

Current health information systems may not meet all data demands of maternity care providers, or other healthcare workers. Policy makers and health information system specialists need to acknowledge different ways of data use beyond health service planning, with an emphasis on healthcare providers' data needs for clinical documentation.

The need for standardised methods of data collection, sharing of data and agency coordination in humanitarian settings

Humanitarian crises and emergencies are prevalent all over the world. With a surge in crises in the last decade, humanitarian agencies have increased their presence in these areas. Initiatives such as the Sphere Project and the Minimum Initial Service Package known as MISP were formed to set standards and priorities for humanitarian assistance agencies. MISP was initiated to coordinate and standardise data and collection methods and involve locals for programme sustainability. Developing policies and programmes based on available data in humanitarian crises is necessary to make evidence-based decisions. Data sharing between humanitarian agencies increases the effectiveness of rapid responses and limits duplication of services and research. In addition, standardising data collection methods helps alleviate the risk of inaccurate information and allows for comparison and estimates among different settings. Big data is a new collection method that can help assemble timely data if resources are available and turn the data into information. Further research on setting priority indicators for humanitarian situations can help guide agencies to collect quality data.

The use of and need for data and information by health professionals supporting the delivery of palliative cancer care services in sub-Saharan Africa: A qualitative study

PURPOSE

The ability to develop and evaluate approaches to the management of advanced cancer in sub-Saharan Africa is limited by the lack of local, reliable and valid data to ensure that practice is evidence-based, replicable and reflects the needs of the population served.

METHODS

A secondary qualitative analysis of in-depth interviews with 59 health professionals delivering palliative cancer care in Nigeria, Uganda and Zimbabwe were conducted to determine the use and needs for data and information for patient care and service delivery. Framework analysis was used, informed by a conceptual model for data use in low and middle-income countries.

RESULTS

Three meta-themes include: (1) Current practice in data gathering and use; (2) Gaps for capturing, storing information and supporting communication, and; (3) Needs and opportunities for data use. Deficits in current data access and use were identified, alongside targets for improving the quality, accessibility and utility of data to inform the development of palliative cancer care.

CONCLUSIONS

The availability and use of relevant and reliable data relating to the current provision of palliative cancer care are requisite for the contextually appropriate and effective development of health services. The requirements and constraints articulated by participants can guide future development and optimisation of digital health approaches for palliative cancer care in the participating countries, with relevance to the wider sub-Saharan Africa region.

Barriers and Facilitators to Data Use for Decision Making: The Experience of the African Health Initiative Partnerships in Ethiopia, Ghana, and Mozambique

BACKGROUND

Three African Health Initiative (AHI) partnership projects in Ethiopia, Ghana, and Mozambique implemented strategies to improve the quality and evaluation of routinely collected data at the primary health care level and stimulate its use in evidence-based decision making. We compare how these programs designed and carried out data for decision-making (DDM) strategies, elaborate on barriers and facilitators to implementation success, and offer recommendations for future DDM programming.

METHODS

Researchers from each project collaboratively wrote a cross-country protocol based on these objectives. By adapting the Consolidated Framework for Implementation Research (CFIR) through a qualitative theme reduction process, they harmonized lines of inquiry on the design of the respective DDM strategies and the barriers and facilitators of effective implementation. We conducted in-depth interviews and focus group discussions with stakeholders from the primary health care systems in each country, and we carried out multistage, thematic analyses using a deductive lens.

RESULTS

Effective implementation of DDM depended on whether implementers felt that DDM was adaptable to context, feasible to trial, and easy to introduce and maintain. The prevailing policy and political environment in the wider health system, learning climate and absorptive capacity for evidence-based change in DDM settings, engagement of external change agents and internal change leaders, and promotion of opportunities and means for team-based reflection and evaluations of what works influenced the success or failure of DDM strategies.

CONCLUSION

Opportunities for team-based capacity building and individual mentorship led to effective DDM programming. External policies and associated incentives bolstered this but occasionally led to unintended consequences. Leadership engagement and availability of resources to act on recommendations; respond to capacity-building needs; and facilitate collaborations between peers, within hierarchies, and across the local health system proved crucial to DDM, as was encouraging adaptation and opportunities for iterative on-the-job learning.

Assessing the Use of Hospital Information Systems (HIS) to Support Decision-Making: A Cross-Sectional Study in Public Hospitals in the Huíla Health Region of Southern Angola

Hospital information systems could be relevant tools to inform hospital managers, support better management decisions in healthcare, and increase efficiency. Nonetheless, hospital managers’ effective use of these systems to support decision-making in Angola is unknown. Our study aimed to analyse the use of hospital information systems as a tool to support decision-making by hospital managers in Huíla, Angola. It was a descriptive, cross-sectional study inducted between July and September 2017 in seven hospitals in Huíla Province, Angola, specifically in the cities of Lubango and Matala. Thirty-six members of the hospital boards filled out a self-questionnaire that consisted of twenty questions based on the following issues: Characterisation of the interviewee’s profile; availability of information in the institution; and quality and usefulness of the available operational information. At least two thirds of the participants reported being unsatisfied or relatively satisfied with each assessed hospital information systems-specific feature. More than 50% have rarely or never used the health information system to support decision-making. Most managers do not use hospital information systems to support management-related decision-making in Angola. Improving the ability of hospital information systems to compute adequate indicators and training for hospital managers could be targets for future interventions to support better management-related decision-making in Angolan healthcare.

Exploring data quality and use of the routine health information system in Ethiopia: a mixed-methods study

OBJECTIVE

A routine health information system (RHIS) enables decision making in the healthcare system. We aimed to analyse data quality at the district and regional level and explore factors and perceptions affecting the quality and use of routine data.

DESIGN

This was a mixed-methods study. We used the WHO toolkit for analysing data quality and interviewed staff at the point of data generation and along with the flow of data. Data were analysed using the Performance of Routine Information System Management framework.

SETTING

This study was performed in eight districts in four regions of Ethiopia. The study was nested within a 2-year programme of the Operational Research and Coaching for government Analysts.

PARTICIPANTS

We visited 45 health posts, 1 district hospital, 16 health centres and 8 district offices for analysis of routine RHIS data and interviewed 117 staff members for the qualitative assessment.

OUTCOME MEASURES

We assessed availability of source documents, completeness, timeliness and accuracy of reporting of routine data, and explored data quality and use perceptions.

RESULTS

There was variable quality of both indicator and data element. Data on maternal health and immunisation were of higher quality than data on child nutrition. Issues ranged from simple organisational factors, such as availability of register books, to intricate technical issues, like complexity of indicators and choice of denominators based on population estimates. Respondents showed knowledge of the reporting procedures, but also demonstrated limited skills, lack of supportive supervision and reporting to please the next level. We saw limited examples of the use of data by the staff who were responsible for data reporting.

CONCLUSION

We identified important organisational, technical, behavioural and process factors that need further attention to improve the quality and use of RHIS data in Ethiopia.

Research gaps in transforming tuberculosis data to action for better health outcomes: A systematic literature review

Background

In their work to end the tuberculosis (TB) epidemic in lower- and middle-income countries, national TB programs need a tool to measure, monitor, and strengthen relevant capabilities to create a continuous transformation of data into action (D2A) to improve TB program results. However, there is a lack of scientific evidence to determine specific measurement dimensions of a D2A continuum that enables TB programs to identify the barriers and enablers of D2A and to guide the selection of interventions appropriate for the context and decision-making capabilities of various TB program actors.

Methods

A systematic review of peer-reviewed and grey literature was conducted per Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 48 peer-reviewed publications were selected for data extraction and analysis.

Results

The findings show that selected publications discussed the health system level, stakeholders involved in decision making, decision type, data system, data sources, data use enablers and barriers, decision-making framework and steps, decision outcome/impact, and how that outcome was measured. The findings highlight barriers and enablers to data use and explain the relationship among data sources, decision type, and stakeholders. Seventeen D2A measurement dimensions were identified.

Conclusions

Transforming data to action is a continuous process that recognizes that data use indicators vary by type of decisions, decision makers, and the health system level at which decisions are made. As a logical next step, the project team plans to develop and validate a D2A continuum toolkit that will include a measurement scale, implementation guide, and data collection and analysis Microsoft Excel workbook.

Obstacles and features of health information systems: A systematic literature review

BACKGROUND

Currently many healthcare systems are supported by an increasing set of Health Information Sys-tems (HISs), which assist the activities for multiple stakeholders. The literature on HISs is, however, fragmented and a solid overview of the current state of HISs is missing. This impedes the understanding and characterization of the required HISs for the healthcare domain.

METHODS

In this article, we present the results of a Systematic Literature Review (SLR) that identifies the HISs, their domains, stakeholders, features, and obstacles.

RESULTS

In the SLR, we identified 1340 papers from which we selected 136 studies, on which we performed a full-text analysis. After the synthesis of the data, we were able to report on 33 different domains, 41 stakeholders, 73 features, and 69 obstacles. We discussed how these domains, features, and obstacles interact with each other and presented suggestions to overcome the identified obstacles. We recognized five groups of obstacles: technical problems, operational functionality, maintenance & support, usage problems, and quality problems. Obstacles from all groups require to be solved to pave the way for further research and application of HISs.

CONCLUSION

This study shows that there is a plentitude of HISs with unique features and that there is no consensus on the requirements and types of HISs in the literature.

Advancing sustainable development goals through immunization: a literature review

BACKGROUND

Immunization directly impacts health (SDG3) and brings a contribution to 14 out of the 17 Sustainable Development Goals (SDGs), such as ending poverty, reducing hunger, and reducing inequalities. Therefore, immunization is recognized to play a central role in reaching the SDGs, especially in low- and middle-income countries (LMICs). Despite continuous interventions to strengthen immunization systems and to adequately respond to emergency immunization during epidemics, the immunization-related indicators for SDG3 lag behind in sub-Saharan Africa. Especially taking into account the current Covid19 pandemic, the current performance on the connected SDGs is both a cause and a result of this.

METHODS

We conduct a literature review through a keyword search strategy complemented with handpicking and snowballing from earlier reviews. After title and abstract screening, we conducted a qualitative analysis of key insights and categorized them according to showing the impact of immunization on SDGs, sustainability challenges, and model-based solutions to these challenges.

RESULTS

We reveal the leveraging mechanisms triggered by immunization and position them vis-à-vis the SDGs, within the framework of Public Health and Planetary Health. Several challenges for sustainable control of vaccine-preventable diseases are identified: access to immunization services, global vaccine availability to LMICs, context-dependent vaccine effectiveness, safe and affordable vaccines, local/regional vaccine production, public-private partnerships, and immunization capacity/capability building. Model-based approaches that support SDG-promoting interventions concerning immunization systems are analyzed in light of the strategic priorities of the Immunization Agenda 2030.

CONCLUSIONS

In general terms, it can be concluded that relevant future research requires (i) design for system resilience, (ii) transdisciplinary modeling, (iii) connecting interventions in immunization with SDG outcomes, (iv) designing interventions and their implementation simultaneously, (v) offering tailored solutions, and (vi) model coordination and integration of services and partnerships. The research and health community is called upon to join forces to activate existing knowledge, generate new insights and develop decision-supporting tools for Low-and Middle-Income Countries' health authorities and communities to leverage immunization in its transformational role toward successfully meeting the SDGs in 2030.

Assessing the indirect effects of COVID-19 on healthcare delivery, utilization and health outcomes: a scoping review

Background

The COVID-19 pandemic and global efforts to contain its spread, such as stay-at-home orders and transportation shutdowns, have created new barriers to accessing healthcare, resulting in changes in service delivery and utilization globally. The purpose of this study is to provide an overview of the literature published thus far on the indirect health effects of COVID-19 and to explore the data sources and methodologies being used to assess indirect health effects.

Methods

A scoping review of peer-reviewed literature using three search engines was performed.

Results

One hundred and seventy studies were included in the final analysis. Nearly half (46.5%) of included studies focused on cardiovascular health outcomes. The main methodologies used were observational analytic and surveys. Data were drawn from individual health facilities, multicentre networks, regional registries, and national health information systems. Most studies were conducted in high-income countries with only 35.4% of studies representing low- and middle-income countries (LMICs).

Conclusion

Healthcare utilization for non-COVID-19 conditions has decreased almost universally, across both high- and lower-income countries. The pandemic’s impact on non-COVID-19 health outcomes, particularly for chronic diseases, may take years to fully manifest and should be a topic of ongoing study. Future research should be tied to system improvement and the promotion of health equity, with researchers identifying potentially actionable findings for national, regional and local health leadership. Public health professionals must also seek to address the disparity in published data from LMICs as compared with high-income countries.

A realist systematic review of evidence from low- and middle-income countries of interventions to improve immunization data use

BACKGROUND

The use of routine immunization data by health care professionals in low- and middle-income countries remains an underutilized resource in decision-making. Despite the significant resources invested in developing national health information systems, systematic reviews of the effectiveness of data use interventions are lacking. Applying a realist review methodology, this study synthesized evidence of effective interventions for improving data use in decision-making.

METHODS

We searched PubMed, POPLINE, Centre for Agriculture and Biosciences International Global Health, and African Journals Online for published literature. Grey literature was obtained from conference, implementer, and technical agency websites and requested from implementing organizations. Articles were included if they reported on an intervention designed to improve routine data use or reported outcomes related to data use, and targeted health care professionals as the principal data users. We developed a theory of change a priori for how we expect data use interventions to influence data use. Evidence was then synthesized according to data use intervention type and level of the health system targeted by the intervention.

RESULTS

The searches yielded 549 articles, of which 102 met our inclusion criteria, including 49 from peer-reviewed journals and 53 from grey literature. A total of 66 articles reported on immunization data use interventions and 36 articles reported on data use interventions for other health sectors. We categorized 68 articles as research evidence and 34 articles as promising strategies. We identified ten primary intervention categories, including electronic immunization registries, which were the most reported intervention type (n = 14). Among the research evidence from the immunization sector, 32 articles reported intermediate outcomes related to data quality and availability, data analysis, synthesis, interpretation, and review. Seventeen articles reported data-informed decision-making as an intervention outcome, which could be explained by the lack of consensus around how to define and measure data use.

CONCLUSIONS

Few immunization data use interventions have been rigorously studied or evaluated. The review highlights gaps in the evidence base, which future research and better measures for assessing data use should attempt to address.

Key informant perspectives on the challenges and opportunities for using routine health data for decision-making in Senegal

Background

Increasing the performance of routine health information systems (RHIS) is an important policy priority both globally and in Senegal. As RHIS data become increasingly important in driving decision-making in Senegal, it is imperative to understand the factors that determine their use.

Methods

Semi-structured interviews were conducted with 18 high- and mid-level key informants active in the malaria, tuberculosis and HIV programmatic areas in Senegal. Key informants were employed in the relevant divisions of the Senegal Ministry of Health or nongovernmental / civil society organizations. We asked respondents questions related to the flow, quality and use of RHIS data in their organizations. A framework approach was used to analyze the qualitative data.

Results

Although the respondents worked at the strategic levels of their respective organizations, they consistently indicated that data quality and data use issues began at the operational level of the health system before the data made its way to the central level. We classify the main identified barriers and facilitators to the use of routine data into six categories and attempt to describe their interrelated nature. We find that data quality is a central and direct determinant of RHIS data use. We report that a number of upstream factors in the Senegal context interact to influence the quality of routine data produced. We identify the sociopolitical, financial and system design determinants of RHIS data collection, dissemination and use. We also discuss the organizational and infrastructural factors that influence the use of RHIS data.

Conclusions

We recommend specific prescriptive actions with potential to improve RHIS performance in Senegal, the quality of the data produced and their use. These actions include addressing sociopolitical factors that often interrupt RHIS functioning in Senegal, supporting and motivating staff that maintain RHIS data systems as well as ensuring RHIS data completeness and representativeness. We argue for improved coordination between the various stakeholders in order to streamline RHIS data processes and improve transparency. Finally, we recommend the promotion of a sustained culture of data quality assessment and use.

Barriers and enablers to routine register data collection for newborns and mothers: EN-BIRTH multi-country validation study

BACKGROUND

Policymakers need regular high-quality coverage data on care around the time of birth to accelerate progress for ending preventable maternal and newborn deaths and stillbirths. With increasing facility births, routine Health Management Information System (HMIS) data have potential to track coverage. Identifying barriers and enablers faced by frontline health workers recording HMIS source data in registers is important to improve data for use.

METHODS

The EN-BIRTH study was a mixed-methods observational study in five hospitals in Bangladesh, Nepal and Tanzania to assess measurement validity for selected Every Newborn coverage indicators. We described data elements required in labour ward registers to track these indicators. To evaluate barriers and enablers for correct recording of data in registers, we designed three interview tools: a) semi-structured in-depth interview (IDI) guide b) semi-structured focus group discussion (FGD) guide, and c) checklist assessing care-to-documentation. We interviewed two groups of respondents (January 2018-March 2019): hospital nurse-midwives and doctors who fill ward registers after birth (n = 40 IDI and n = 5 FGD); and data collectors (n = 65). Qualitative data were analysed thematically by categorising pre-identified codes. Common emerging themes of barriers or enablers across all five hospitals were identified relating to three conceptual framework categories.

RESULTS

Similar themes emerged as both barriers and enablers. First, register design was recognised as crucial, yet perceived as complex, and not always standardised for necessary data elements. Second, register filling was performed by over-stretched nurse-midwives with variable training, limited supervision, and availability of logistical resources. Documentation complexity across parallel documents was time-consuming and delayed because of low staff numbers. Complete data were valued more than correct data. Third, use of register data included clinical handover and monthly reporting, but little feedback was given from data users.

CONCLUSION

Health workers invest major time recording register data for maternal and newborn core health indicators. Improving data quality requires standardised register designs streamlined to capture only necessary data elements. Consistent implementation processes are also needed. Two-way feedback between HMIS levels is critical to improve performance and accurately track progress towards agreed health goals.

Decentralizing evidence-based decision-making in resource limited setting: A case of SNNP region, Ethiopia

BACKGROUND

Access to and the use of accurate, valid, reliable, timely, relevant, legible and complete information is vital for safe and reliable healthcare. Though the study area has been implementing standardized Health Management Information System (HMIS), there was a need for information on how well structures were utilizing information and this study was designed to assess HMIS data utilization.

METHODS

Facility based retrospective study was conducted in Southern Nations Nationalities and People's Region (SNNPR) in April, 2017. We included data from 163 sample facilities. Data use was evaluated by reviewing eight items from performance monitoring system that included activities from problem identification to monitoring of proposed action plans. Each item reviewed was recoded to yes or no and summed to judge overall performance.

RESULTS

About half (52%) of woredas, 26.2% health centers (HCs), 25% hospitals and 6.2% health posts (HPs) reviewed their performance monthly but only 20% woredas, 6.2% HCs, 1.5% HPs and no hospital prepared action plans after reviewing performance. Summary of 8 items assessed showed that majority of facilities (87.5% hospitals, 81.5% HPs and 70.8% HCs) were poor in data utilization.

CONCLUSIONS

Only about half of woredas and below one-fifth of health facilities were utilizing HMIS data and a lot to move to catch-up country's information revolution plan. Lower health care systems should be supported in evidence-based decision-making and progress should be monitored routinely quantitatively and/or qualitatively.

Understanding the challenges associated with the use of data from routine health information systems in low- and middle-income countries: A systematic review

BACKGROUND

Routine health information systems (RHISs) are crucial to informing decision-making at all levels of the health system. However, the use of RHIS data in low- and middle-income countries (LMICs) is limited due to concerns regarding quality, accuracy, timeliness, completeness and representativeness.

OBJECTIVE

This study systematically reviewed technical, behavioural and organisational/environmental challenges that hinder the use of RHIS data in LMICs and strategies implemented to overcome these challenges.

METHOD

Four electronic databases were searched for studies describing challenges associated with the use of RHIS data and/or strategies implemented to circumvent these challenges in LMICs. Identified articles were screened against inclusion and exclusion criteria by two independent reviewers.

RESULTS

Sixty studies met the inclusion criteria and were included in this review, 55 of which described challenges in using RHIS data and 20 of which focused on strategies to address these challenges. Identified challenges and strategies were organised by their technical, behavioural and organisational/environmental determinants and by the core steps of the data process. Organisational/environmental challenges were the most commonly reported barriers to data use, while technical challenges were the most commonly addressed with strategies.

CONCLUSION

Despite the known benefits of RHIS data for health system strengthening, numerous challenges continue to impede their use in practice.

IMPLICATIONS

Additional research is needed to identify effective strategies for addressing the determinants of RHIS use, particularly given the disconnect identified between the type of challenge most commonly described in the literature and the type of challenge most commonly targeted for interventions.

The Nigerian health information system policy review of 2014 : the need, content, expectations and progress

BACKGROUND

Nigeria's national health information system (HIS) data sources are grouped into institutional and population based data that traverse many government institutions. Communication and collaboration between these institutions are limited, fraught with fragmentation and challenges national HIS functionality.

OBJECTIVES

The objective of this paper was to share insights from and the implications of a recent review of Nigeria's HIS policy in 2014 that resulted in its substantial revision. We also highlight some subsequent enactments.

REVIEW PROCESS AND OUTCOMES

In 2013, Nigeria's Federal Ministry of Health launched an inter-ministerial and multi-departmental review of the National Health Management Information System policy of 2006. The review was guided by World Health Organization's 'Framework and Standards for Country Health Information Systems'. The key finding was a lack of governance mechanisms in the execution of the policy, including an absent data management governance process. The review also found a multiplicity of duplicative, parallel reporting tools and platforms.

CONCLUSION

Recommendations for HIS Policy revisions were proposed to and implemented by the Federal Government of Nigeria. The revised HIS policy now provides for a strong framework for the leadership and governance of the HIS with early results.