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Record W2951165673 · doi:10.1186/s13012-019-0917-z

Scaling Up Safer Birth Bundle Through Quality Improvement in Nepal (SUSTAIN)—a stepped wedge cluster randomized controlled trial in public hospitals

2019· article· en· W2951165673 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueImplementation Science · 2019
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersGrand Challenges CanadaLaerdal Foundation for Acute Medicine
KeywordsMedicineNeonatal resuscitationPublic healthCluster randomised controlled trialRandomized controlled trialPsychological interventionEmergency medicinePediatricsMedical emergencyResuscitationNursingSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Each year, 2.2 million intrapartum-related deaths (intrapartum stillbirths and first day neonatal deaths) occur worldwide with 99% of them taking place in low- and middle-income countries. Despite the accelerated increase in the proportion of deliveries taking place in health facilities in these settings, the stillborn and neonatal mortality rates have not reduced proportionately. Poor quality of care in health facilities is attributed to two-thirds of these deaths. Improving quality of care during the intrapartum period needs investments in evidence-based interventions. We aim to evaluate the quality improvement package-Scaling Up Safer Bundle Through Quality Improvement in Nepal (SUSTAIN)-on intrapartum care and intrapartum-related mortality in public hospitals of Nepal. METHODS: We will conduct a stepped wedge cluster randomized controlled trial in eight public hospitals with each having least 3000 deliveries a year. Each hospital will represent a cluster with an intervention transition period of 2 months in each. With a level of significance of 95%, the statistical power of 90% and an intra-cluster correlation of 0.00015, a study period of 19 months should detect at least a 15% change in intrapartum-related mortality. Quality improvement training, mentoring, systematic feedback, and a continuous improvement cycle will be instituted based on bottleneck analyses in each hospital. All concerned health workers will be trained on standard basic neonatal resuscitation and essential newborn care. Portable fetal heart monitors (Moyo®) and neonatal heart rate monitors (Neobeat®) will be introduced in the hospitals to identify fetal distress during labor and to improve neonatal resuscitation. Independent research teams will collect data in each hospital on intervention inputs, processes, and outcomes by reviewing records and carrying out observations and interviews. The dose-response effect will be evaluated through process evaluations. DISCUSSION: With the global momentum to improve quality of intrapartum care, better understanding of QI package within a health facility context is important. The proposed package is based on experiences from a similar previous scale-up trial carried out in Nepal. The proposed evaluation will provide evidence on QI package and technology for implementation and scale up in similar settings. TRIAL REGISTRATION NUMBER: ISRCTN16741720 . Registered on 2 March 2019.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.426
Teacher spread0.384 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it