Smart Discharges for Mom & Baby
1 other identifier
observational
7,182
1 country
1
Brief Summary
This study aims to build a predictive algorithm that identifies mother-newborn dyads most at risk of death or complications in the 6 weeks after birth. The investigators will conduct a multi-site cohort study with 7,000 dyads in Uganda and engage with local stakeholders (e.g., patients, healthcare workers, and health policy-makers) to develop an evidence-based bundle of interventions that address key practice gaps and the critical factors leading to death and complications in these dyads. In the investigator's epidemiological study of post-delivery post-discharge outcomes in 3,236 dyads in Uganda (2017-2020), results indicated that most newborn and maternal readmissions were due to infectious illness (i.e. sepsis, surgical site infections, malaria), and primarily occurred early in the post-discharge period. Thus, the focus of this study will be identifying interventions that target these common and early outcomes, for both mothers and newborns, using World Health Organization recommendations, patient and caregiver experiences, and stakeholder recommendations. If successful, results will inform the next steps of this project, which is the external validation of the model and clinical evaluation of a personalized approach to improving health outcomes and health-seeking behaviour for mothers and newborns.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2022
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
April 14, 2022
CompletedFirst Submitted
Initial submission to the registry
December 9, 2022
CompletedFirst Posted
Study publicly available on registry
February 15, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
August 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
April 30, 2024
CompletedResults Posted
Study results publicly available
April 10, 2025
CompletedApril 10, 2025
March 1, 2025
1.4 years
December 9, 2022
February 20, 2025
March 25, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Post-discharge Readmission or Mortality
Composite rate of maternal or neonatal death or re-admission within 6 weeks following delivery
6 weeks following delivery
Secondary Outcomes (2)
Post-natal Care Visits
6 weeks following delivery
Post-discharge Health Seeking
6 weeks following delivery
Study Arms (1)
mother and newborn dyads
We will recruit 6700 mother and newborn dyads from the two participating hospitals. We will continue to follow-up with all patients enrolled in the study until 6 weeks (42 days) post delivery.
Interventions
Eligibility Criteria
The study population represents women living within the catchments of two study hospitals (Mbarara Regional Referral Hospital and Jinja Regional Referral Hospital) in Uganda, who present for delivery.
You may qualify if:
- Women and adolescent girls aged 12 and above delivering a single or multiple babies at the study hospital during the active recruitment phase.
You may not qualify if:
- Inability, for whatever reason, to provide informed consent.
- Language barrier
- Mother is from a refugee camp
- Mother has no access to phone or other means for follow-up
- Mother lives outside of hospital catchment area
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
BC Children's Hospital Research Institute
Vancouver, British Columbia, V5Z 2X8, Canada
Related Publications (1)
Wiens MO, Trawin J, Pillay Y, Nguyen V, Komugisha C, Kenya-Mugisha N, Namala A, Bebell LM, Ansermino JM, Kissoon N, Payne BA, Vidler M, Christoffersen-Deb A, Lavoie PM, Ngonzi J. Prognostic algorithms for post-discharge readmission and mortality among mother-infant dyads: an observational study protocol. Front Epidemiol. 2023 Nov 29;3:1233323. doi: 10.3389/fepid.2023.1233323. eCollection 2023.
PMID: 38455948DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Results Point of Contact
- Title
- Matthew O. Wiens
- Organization
- Institute for Global Health at BC Children's Hospital and BC Women's Hospital + Health Centre
Study Officials
- PRINCIPAL INVESTIGATOR
Matthew O Wiens, PharmD, PhD
University of British Columbia
Publication Agreements
- PI is Sponsor Employee
- No
- Restrictive Agreement
- No
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Assistant Professor
Study Record Dates
First Submitted
December 9, 2022
First Posted
February 15, 2023
Study Start
April 14, 2022
Primary Completion
August 31, 2023
Study Completion
April 30, 2024
Last Updated
April 10, 2025
Results First Posted
April 10, 2025
Record last verified: 2025-03
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP
- Time Frame
- Data will be deposited to an open access repository with moderated access within 2 years of study completion
- Access Criteria
- Moderated access on a case-by-case basis.
After the study period, a de-identified copy of the data will be prepared for deposition in a repository with open access with proper governance mechanisms. We will make every effort to prevent re-identification of subjects by coding data that has the potential of being identifiable. For example, we will convert all dates into meaningful decimal numbers (date of birth into days since birth and date of recruitment will be reduced to month of recruitment) and all locations will be coded into data that is useful but not specific (such as address converted to distance and direction from facility). We will ensure that data elements with small numbers of subjects (less than 10) will be coded or lumped to avoid identification. The de-identified study data will be made available using a data hosting service (e.g., Dataverse, Vivli, etc.)