Innovative dashboard for optimising emergency obstetric care geographical accessibility in Nigeria: Qualitative study with technocrats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• We explored digital dashboards’ potential for planning EmOC geo-access optimisation. • Stakeholders recognise that service planning should be informed by evidence on need. • Politics, pressured community advocacy, and donor funding actually drive planning. • There is a strong appetite for using digital technology to inform service planning. • Stakeholders have concerns about accuracy of data that will inform the digital tool. To explore perspectives of public sector technocrats on the role of and considerations needed for implementing an innovative dashboard that leverages geographic information systems (GIS) in supporting optimisation of emergency obstetric care (EmOC) geographical accessibility in Nigeria. Twenty-three semi-structured interviews were conducted in person or virtually with six policymakers and 17 senior civil servants in Nigeria. Braun and Clarke's six-step approach to thematic analysis, which involved data familiarisation, initial code generation, searching for themes, reviewing themes, defining themes, and producing the report, was applied. Despite recognising the ideal of data-driven needs assessment, in reality, factors such as political pressure, persistent community advocacy, and donor funding drive decisions on siting EmOC facilities. Irregular short-term political cycles and exigencies in health systems prevent new facilities from being established or motivate a focus on facility quality over quantity. There was a strong appetite for using GIS-enabled dashboards to support planning, with enthusiasm for such technology more apparent where innovation was already part of government's philosophy. A digital dashboard that is dynamic, reflective of reality, inclusive of public and private providers, incorporates facility characteristics, and can test accessibility scenarios, was deemed particularly valuable. Its value proposition extended beyond EmOC and provider type. However, its success as a policy tool will depend on the veracity and currency of the data informing it. Technocrats welcome dynamic GIS-enabled dashboards as it offers a significant step-change compared to the current practice for EmOC service planning. Value-for-money of such innovations must be considered if implemented. Planning and siting of emergency services used by pregnant women (EmOC) in many low-resource countries are mostly haphazard. However, there is increasing recognition that technology can refine this process. In this study, we explored perspectives of public sector technocrats in Nigeria on the role of and considerations needed for implementing an innovative digital dashboard that leverages geographic information systems in optimising EmOC geographical accessibility. We found that current planning is mainly driven by political pressure, community advocacy, and donor funding. However, there is a strong appetite in government for using GIS-enabled dashboards to inform service planning, with enthusiasm for such technology appearing to be more grounded in states where innovation was already part of the government's philosophy. Yet, concerns about data accuracy were expressed. Broadly, dashboards that are dynamic, reflective of reality, inclusive of public and private providers, incorporate facility characteristics, and can test access scenarios, were deemed particularly valuable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it