Maternal and perinatal death surveillance and response in low- and middle-income countries: a scoping review of implementation factors
Bibliographic record
Abstract
Maternal and perinatal death surveillance and response (MPDSR), or any form of maternal and/or perinatal death review or audit, aims to improve health services and pre-empt future maternal and perinatal deaths. With expansion of MPDSR across low- and middle-income countries (LMIC), we conducted a scoping review to identify and describe implementation factors and their interactions. The review adapted an implementation framework with four domains (intervention, individual, inner and outer settings) and three cross-cutting health systems lenses (service delivery, societal and systems). Literature was sourced from six electronic databases, online searches and key experts. Selection criteria included studies from LMIC published in English from 2004 to July 2018 detailing factors influencing implementation of MPDSR, or any related form of MPDSR. After a systematic screening process, data for identified records were extracted and analysed through content and thematic analysis. Of 1027 studies screened, the review focuses on 58 studies from 24 countries, primarily in Africa, that are mainly qualitative or mixed methods. The literature mostly examines implementation factors related to MPDSR as an intervention, and to its inner and outer setting, with less attention to the individuals involved. From a health systems perspective, almost half the literature focuses on the tangible inputs addressed by the service delivery lens, though these are often measured inadequately or through incomparable ways. Though less studied, the societal and health system factors show that people and their relationships, motivations, implementation climate and ability to communicate influence implementation processes; yet their subjective experiences and relationships are inadequately explored. MPDSR implementation contributes to accountability and benefits from a culture of learning, continuous improvement and accountability, but few have studied the complex interplay and change dynamics involved. Better understanding MPDSR will require more research using health policy and systems approaches, including the use of implementation frameworks.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".