Introduction: Digital data systems have the potential to improve data quality and provide individual-level information to understand gaps in the quality of care. This study explored experiences and perceptions of a perinatal eRegistry in two hospitals in Mtwara region, Tanzania. Drawing from realist evaluation and systems thinking, we go beyond a descriptive account of stakeholders' experiences and provide insight into key structural drivers and underlying social paradigms.
Methods: We carried out 6 weeks of focused ethnographic observations at the labour wards of the two hospitals and 29 semi-structured qualitative interviews with labour ward staff, as well as with administrative and managerial stakeholders at hospital, district and regional levels. Multi-stage reflexive thematic data analysis was carried out.
Results: We provide an in-depth account of the day-to-day functioning of the eRegistry in the two hospitals, including both aspects of positive change and key challenges with its integration into routine documentation duties. Experiences with and perceptions of the eRegistry were inextricably linked to broader systemic constraints relating to staffing, workload and infrastructure. A key underlying theme shaping the way people engaged with the eRegistry was the notion of data ownership: the presence or absence of a feeling of being responsible, involved and in control of data.
Conclusion: Some of the key systemic challenges in recording accurate, timely information about women and their babies are not solved by digital tools. Our findings also underline that when healthcare workers feel that data are not primarily for them, they document only for reporting purposes. The eRegistry increased a sense of data ownership among the nurse-midwives directly involved with data entry, but the potential for promoting and supporting data use feedback loops for improvement in care provision remained largely untapped. Our findings highlight the importance of local relevance and ownership in digitisation of routine health information systems.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11580263 | PMC |
http://dx.doi.org/10.1136/bmjgh-2024-016765 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!