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

Defining a malaria diagnostic pathway from innovation to adoption: Stakeholder perspectives on data and evidence gaps

Malaria, a major global health concern, requires effective diagnostic tools for patient care, disease control, and elimination. The pathway from concept to the adoption of diagnostic products is complex, involving multiple steps and stakeholders. To map this process, our study introduces a malaria-specific diagnostic pathway, synthesising existing frameworks with expert insights. Comprising six major stages and 31 related activities, the pathway retains the core stages from existing frameworks and integrates essential malaria diagnostic activities, such as WHO prequalification processes, global stakeholder involvement, and broader health systems considerations. To understand the scope and availability of evidence guiding the activities along this pathway, we conducted an online survey with 113 participants from various stages of the malaria diagnostic pathway. The survey assessed perceptions on four critical attributes of evidence: clear requirements, alignment with user needs, accuracy and reliability, and public and free availability. It also explored the types of evidence used and the challenges and potential solutions related to evidence generation and use. Respondents reported using a broad range of formal and informal data sources. Findings indicated differing levels of agreement on the attributes across pathway stages, with notable challenges in the Approvals and Manufacturing stage and consistent concerns regarding the public availability of data/evidence. The study offers valuable insights for optimising evidence generation and utilisation across the malaria diagnostic pathway. It highlights the need for enhanced stakeholder collaboration, improved data availability, and increased funding to support effective evidence generation, sharing, and use. We propose actionable solutions, including the use of public data repositories, progressive data sharing policies, open-access publishing, capacity-building initiatives, stakeholder engagement forums, and innovative funding solutions. The developed framework and study insights have broader applications, offering a model adaptable for other diseases, particularly for neglected tropical diseases, which face similar diagnostic challenges.

How Can Community Data Be Leveraged to Advance Primary Health Care? A Scoping Review of Community-Based Health Information Systems

BACKGROUND

Community-based health information systems (CBISs) can provide critical insights into how community health systems function, and digitized CBISs may improve the quality of community-level data and facilitate integration and use of CBISs within the broader health system. This scoping review aims to understand how CBISs have been implemented, integrated, and used to support community health outcomes in low- and middle-income countries (LMICs).

METHODS

Both peer-reviewed and gray literature were included; relevant articles were identified using key terms and controlled vocabulary related to community/primary health care, health information systems, digital health, and LMICs. A total of 11,611 total records were identified from 5 databases and the gray literature. After deduplication, 6,985 peer-reviewed/gray literature were screened, and 95 articles/reports were included, reporting on 105 CBIS implementations across 38 countries.

RESULTS

Findings show that 55% of CBISs included some level of digitization, with just 28% being fully digitized (for data collection and reporting). Data flow from the community level into the health system varied, with digitized CBISs more likely to reach national-level integration. National-level integration was primarily seen among vertical CBISs. Data quality challenges were present in both paper-based and digitized CBISs, exacerbated by fragmentation of the community health landscape with often parallel reporting systems. CBIS data use was constrained to mostly vertical and digitized (partially or fully) CBISs at national/subnational levels.

CONCLUSION

Digitization can play a pivotal role in strengthening CBIS use, but findings demonstrate that CBISs are only as effective as the community health systems they are embedded within. Community-level data are often not being integrated into national/subnational health information systems, undermining the ability to understand what the community health needs are. Furthermore, stronger investments within community health systems need to be in place broadly to reduce fragmentation and provide stronger infrastructural and systemic support to the community health workforce.

A consolidated and geolocated facility list in Senegal from triangulating secondary data

Having a geolocated list of all facilities in a country - a "master facility list" (MFL) - can provide critical inputs for health program planning and implementation. To the best of our knowledge, Senegal has never had a centralized MFL, though many data sources currently exist within the broader Senegalese data landscape that could be leveraged and consolidated into a single database - a critical first step toward building a full MFL. We collated 12,965 facility observations from 16 separate datasets and lists in Senegal, and applied matching algorithms, manual checking and revisions as needed, and verification processes to identify unique facilities and triangulate corresponding GPS coordinates. Our resulting consolidated facility list has a total of 4,685 facilities, with 2,423 having at least one set of GPS coordinates. Developing approaches to leverage existing data toward future MFL establishment can help bridge data demands and inform more targeted approaches for completing a full facility census based on areas and facility types with the lowest coverage. Going forward, it is crucial to ensure routine updates of current facility lists, and to strengthen government-led mechanisms around such data collection demands and the need for timely data for health decision-making.

Key Informants in Applied Qualitative Health Research

Identifying and recruiting key informants is a widely used sampling strategy in applied qualitative health research. Key informants were first conceptualized within ethnography, but there is little methodological guidance about how to use this technique outside of that research tradition. The objective of this article is to offer practical suggestions about how existing methods for data collection with key informants could be translated to methodologies commonly used in applied qualitative health research. This article delineates how key informants could be conceptualized and sampled and how data sufficiency can be approached. The article prompts deeper consideration of the politics of representation and epistemic power that are inherent to the use of key informants in applied qualitative health research.

Behavioral Determinants of Routine Health Information System Data Use in Senegal: A Qualitative Inquiry Based on the Integrated Behavioral Model

Although behavioral factors are thought to be important barriers to routine data use, they remain understudied particularly in low-income country settings. We show that the integrated behavior model can be a valuable theoretical framework for targeted communication strategies and capacity-building interventions aimed at promoting a culture of data use.

Routine health information system (RHIS) data are essential in driving decision making and planning in health systems as well as health programs. However, despite their importance, these data are underutilized, and the underlying individual-level facilitators and barriers to use remain understudied. In this research, we applied the Integrated Behavior Model (IBM) to examine how attitudes toward RHIS data, perceived norms concerning RHIS data use, and the ability to use RHIS data influence the demand and use of RHIS data among stakeholders in Senegal. Using data from interviews with respondents working at national levels of malaria, HIV, and TB control programs in Senegal, we used a framework analysis approach to apply the IBM behavioral constructs and identify their linkages to RHIS data use. We found that attitudes about the quality, availability, and relevance of RHIS data for decision making were important in driving data use among respondents. Institutional expectations, organizational protocols, policies, and practices around RHIS data ultimately shape social norms around the use of the data. Although we found that perceived ability and self-efficacy to use RHIS data were not barriers to RHIS data use among stakeholders at the strategic levels of their respective organizations, these were reported to be barriers at lower levels of the health system. Low perceived control of the RHIS data production process ultimately reduced RHIS data use for decision making among the strategic-level respondents. We recommend context-specific reexamination of existing RHIS interventions with a renewed emphasis on behavioral aspects of data use. The IBM can help guide practitioners, policy makers, and academics to address multiple socioecological factors that influence data use behavior when recommending RHIS and data use solutions.

A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014-2017

Background

As the global burden of malaria decreases, routine health information systems (RHIS) have become invaluable for monitoring progress towards elimination. The District Health Information System, version 2 (DHIS2) has been widely adopted across countries and is expected to increase the quality of reporting of RHIS. In this study, we evaluated the quality of reporting of key indicators of childhood malaria from January 2014 through December 2017, the first 4 years of DHIS2 implementation in Senegal.

Methods

Monthly data on the number of confirmed and suspected malaria cases as well as tests done were extracted from the Senegal DHIS2. Reporting completeness was measured as the number of monthly reports received divided by the expected number of reports in a given year. Completeness of indicator data was measured as the percentage of non-missing indicator values. We used a quasi-Poisson model with natural cubic spline terms of month of reporting to impute values missing at the facility level. We used the imputed values to take into account the percentage of malaria cases that were missed due to lack of reporting. Consistency was measured as the absence of moderate and extreme outliers, internal consistency between related indicators, and consistency of indicators over time.

Results

In contrast to public facilities of which 92.7% reported data in the DHIS2 system during the study period, only 15.3% of the private facilities used the reporting system. At the national level, completeness of facility reporting increased from 84.5% in 2014 to 97.5% in 2017. The percentage of expected malaria cases reported increased from 76.5% in 2014 to 94.7% in 2017. Over the study period, the percentage of malaria cases reported across all districts was on average 7.5% higher (P < 0.01) during the rainy season relative to the dry season. Reporting completeness rates were lower among hospitals compared to health centers and health posts. The incidence of moderate and extreme outlier values was 5.2 and 2.3%, respectively. The number of confirmed malaria cases increased by 15% whereas the numbers of suspected cases and tests conducted more than doubled from 2014 to 2017 likely due to a policy shift towards universal testing of pediatric febrile cases.

Conclusions

The quality of reporting for malaria indicators in the Senegal DHIS2 has improved over time and the data are suitable for use to monitor progress in malaria programs, with an understanding of their limitations. Senegalese health authorities should maintain the focus on broader adoption of DHIS2 reporting by private facilities, the sustainability of district-level data quality reviews, facility-level supervision and feedback mechanisms at all levels of the health system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07364-6.