Transitioning from the “Three Delays” to a focus on continuity of care: A qualitative analysis of maternal deaths in rural Pakistan and Mozambique
Bibliographic record
Abstract
Abstract Background: The Three Delays Framework was instrumental in the reduction of maternal mortality leading up to, and during the Millennium Development Goals. However, this paper suggests the original framework might be reconsidered, now that most mothers give birth in facilities, the quality and continuity of the clinical care is of growing importance. Methods: The paper explores the factors that contributed to maternal deaths in rural Pakistan and Mozambique, using 76 verbal autopsy narratives from the Community Level Interventions for Pre-eclampsia (CLIP) Trial. Results: Qualitative analysis of these maternal death narratives reveals an interplay of various influences, such as, underlying risks and comorbidities, temporary improvements after seeking care, gaps in quality care in emergencies, convoluted referral systems, and arrival at the final facility in critical condition. Evaluation of these narratives helps to reframe the pathways of maternal mortality beyond a single journey of care-seeking, to update the categories of seeking, reaching and receiving care. Conclusions: There is a need to reimagine the pioneering “Three Delays Framework” to include focusing on continuity of care and the “Four Critical Connection Points”: (1) between the stages of pregnancy, (2) between families and health care workers, (3) between health care facilities and (4) between multiple care-seeking journeys. Trial registration: NCT01911494, Date Registered 30/07/2013
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".