Feasibility of task-sharing with community health workers for the identification, emergency management and referral of women with pre-eclampsia, in Mozambique
Bibliographic record
Abstract
BACKGROUND: Maternal mortality is an important public health problem in low-income countries. Delays in reaching health facilities and insufficient health care professionals call for innovative community-level solutions. There is limited evidence on the role of community health workers in the management of pregnancy complications. This study aimed to describe the feasibility of task-sharing the initial screening and initiation of obstetric emergency care for pre-eclampsia/eclampsia from the primary healthcare providers to community health workers in Mozambique and document healthcare facility preparedness to respond to referrals. METHOD: The study took place in Maputo and Gaza Provinces in southern Mozambique and aimed to inform the Community-Level Interventions for Pre-eclampsia (CLIP) cluster randomized controlled trial. This was a mixed-methods study. The quantitative data was collected through self-administered questionnaires completed by community health workers and a health facility survey; this data was analysed using Stata v13. The qualitative data was collected through focus group discussions and in-depth interviews with various community groups, health care providers, and policymakers. All discussions were audio-recorded and transcribed verbatim prior to thematic analysis using QSR NVivo 10. Data collection was complemented by reviewing existing documents regarding maternal health and community health worker policies, guidelines, reports and manuals. RESULTS: Community health workers in Mozambique were trained to identify the basic danger signs of pregnancy; however, they have not been trained to manage obstetric emergencies. Furthermore, barriers at health facilities were identified, including lack of equipment, shortage of supervisors, and irregular drug availability. All primary and the majority of secondary-level facilities (57%) do not provide blood transfusions or have surgical capacity, and thus such cases must be referred to the tertiary-level. Although most healthcare facilities (96%) had access to an ambulance for referrals, no transport was available from the community to the healthcare facility. CONCLUSIONS: This study showed that task-sharing for screening and pre-referral management of pre-eclampsia and eclampsia were deemed feasible and acceptable at the community-level, but an effort should be in place to address challenges at the health system level.
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.
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 | 0.030 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".