Browsing by Author "Kadengye, Damazo"

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Experiences of Mothers and Health Workers With Momcare and Safecare Bundles In Kenya And Tanzania: A Qualitative Evaluation.
    (Kabale University, 2023) Izudi, Jonathan; Owoko, Henry Odero; Bagayoko, Moussa; Kadengye, Damazo
    Between 2019 and 2022, the Digital Dividend Project (DDP), a technology-based intervention that combined care (MomCare) and quality improvement (SafeCare) bundles to empower mothers to access quality care during pregnancy, labor, and delivery, and postnatally, was implemented in Kenya and Tanzania aiming to improve maternal and newborn health out-comes. We describe the experiences of the mothers in accessing and utilizing health services under the bundles, and the experiences of the health workers in providing the services. Between November and December 2022, we conducted a qualitative evaluation across health facilities in Kenya and Tanzania. We held Interviews with mothers (pregnant and postpartum women who had benefited from the care bundles) and health workers (physicians, nurses, and midwives who provided the care bundles, including health facility In-Charges) at the antenatal care (ANC), skilled birth attendance (SBA), and postnatal care (PNC) service delivery points. We performed content analysis. Findings are reported using themes and quotes from the participants. We included 127 mothers (Kenya = 76, Tanzania = 51) and 119 health workers. Findings revealed that among mothers, the care bundles eased access to health services, ensured easy access and optimal ANC use, provision of respectful care removed financial constraints, and led to the receipt of sufficient health education. Health workers reported that the care bundles offered them a new opportunity to provide quality maternal and newborn care and to adhere to the standard of care besides experiencing a positive and fulfilling practice. Health systems improvements included prompt emergency response and continual care, infrastructural developments, medical sup- plies and logistics, staffing, and increased documentation. Overall, the care bundles led to the strengthening of the healthcare system (staffing, service delivery, financing, supplies/logistics, and information management) to deliver quality maternal and child health services. The bundles should be replicated in settings with similar maternal and child health challenges.
  • Thumbnail Image
    ItemOpen Access
    INSPIRE Datahub: A Pan-African Integrated Suite of Services For Harmonising Longitudinal Population Health Data Using OHDSI Tools.
    (Kabale University, 2024) Bhattacharjee, Tathagata; Kiwuwa-Muyingo, Sylvia; Kanjala, Chifundo; Maoyi, Molulaqhooa L.; Amadi, David; Ochola, Michael; Kadengye, Damazo; Gregory, Arofan; Kiragga, Agnes; Amelia, Taylor; Greenfield, Jay; Slaymaker, Emma; Todd, Jim; INSPIRE Network8
    low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making. This paper proposes a pan-African, Findable, Accessible, Interoperable, and Reusable (FAIR) research architecture and infrastructure named the INSPIRE datahub. This cloud-based Platform-as-a-Service (PaaS) and on-premises setup aims to enhance the discovery, integration, and analysis of clinical, population-based surveys, and other health data sources. Methods: The INSPIRE datahub, part of the Implementation Network for Sharing Population Information from Research Entities (INSPIRE), employs the Observational Health Data Sciences and Informatics (OHDSI) open-source stack of tools and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to harmonize data from African longitudinal population studies. Operating on Microsoft Azure and Amazon Web Services cloud platforms, and on on-premises servers, the architecture offers adaptability and scalability for other cloud providers and technology infrastructure. The OHDSI-based tools enable a comprehensive suite of services for data pipeline development, profiling, mapping, extraction, transformation, loading, documentation, anonymization, and analysis. Results: The INSPIRE datahub’s “On-ramp” services facilitate the integration of data and metadata from diverse sources into the OMOP CDM. The datahub supports the implementation of OMOP CDM across data producers, harmonizing source data semantically with standard vocabularies and structurally conforming to OMOP table structures. Leveraging OHDSI tools, the datahub performs quality assessment and analysis of the transformed data. It ensures FAIR data by establishing metadata flows, capturing provenance throughout the ETL processes, and providing accessible metadata for potential users. The ETL provenance is documented in a machine- and human-readable Implementation Guide (IG), enhancing transparency and usability.