Neonatal Data Reporting Challenges in Kenyan Hospitals for SDG Tracking

United Nations Sustainable Development Goal Target 3.2 aims to reduce neonatal mortality. This dataset, from a study by Christiane Hagel of the University of Oxford, investigates implementation experiences of the District Health Information Software (DHIS2) for collecting neonatal hospital data in low- and middle-income countries, with a focus on Kenya. The research maps information flows and identifies challenges in people-based and paper-based subsystems that precede digitization.

Use Cases

• Analyze challenges in neonatal data capture based on the described information flow mapping from healthcare facilities to the national level.
• Identify systemic bottlenecks in health information systems based on the described use cases of newborn data collection and reporting in hospitals.
• Study the implementation of DHIS2 software for mortality tracking based on the described narrative review of literature and policy documents from LMICs.

Strengths

• Focuses on a critical UN Sustainable Development Goal (Target 3.2) for reducing neonatal mortality.
• Research includes validation and adjustment of results, as mentioned in the description.
• Analysis is grounded in specific use cases from Kenyan hospitals.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Oxford

Collection Method

Narrative review of published literature and policy documents, information flow mapping, and case studies in Kenyan hospitals.

Geography

Kenya, with references to low- and middle-income countries (LMICs)