Smart Discharges to Improve Post-discharge Health Outcomes in Children
3 other identifiers
interventional
11,700
1 country
1
Brief Summary
In Uganda, about 5% of children discharged after hospitalization for a serious infection will die in the weeks after returning home. Doctors and parents are often unaware of this period of vulnerability and are poorly equipped to identify or handle this critical situation. This project builds on past work to develop and evaluate models and technology to predict, before discharge, an individual child's risk of recurrent illness, as well as to provide additional post-discharge support to at-risk children. This study seeks to evaluate the effect of a novel "Smart Discharges" approach on childhood mortality and health seeking behaviour.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable sepsis
Started Jul 2017
Longer than P75 for not_applicable sepsis
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
July 16, 2017
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
January 31, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
March 31, 2024
CompletedFebruary 15, 2023
February 1, 2023
6.5 years
December 9, 2022
February 14, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Post-discharge mortality
Rate of all-cause mortality within 6-months post-discharge
From discharge until 6 months post-discharge
Secondary Outcomes (2)
Post-discharge re-admission
From discharge until 6 months post-discharge
Post-discharge health seeking
From discharge until 6 months post-discharge
Study Arms (2)
Phase 1: Observational, children 0-59 months of age
NO INTERVENTIONPhase 1: Observational only
Phase 2: Interventional, children 0-59 months of age
EXPERIMENTALPhase 2: Intervention
Interventions
Interventional intensity is based on predicted risk. Predicted risk based on previously developed prediction algorithms. Low risk: receive discharge education and counselling only; Moderate risk: Discharge education and counselling + 1 post-discharge follow-up referral at day 7; High risk: Discharge education and counselling + 3 post-discharge follow-up referrals (D2, D7, D14); Very high risk: Discharge education and counselling + 3 post-discharge follow-up referrals (D2, D7, D14, D28)
Eligibility Criteria
You may qualify if:
- Children under five years of age
- Admission with a proven or suspected infection
- Provide written informed consent
You may not qualify if:
- Refusal to participate
- Previous enrolment in the study
- Outside of hospital catchment
- Language barrier
- Direct admission following birth without having been discharged
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University of British Columbialead
- Walimucollaborator
- Mbarara University of Science and Technologycollaborator
- Grand Challenges Canadacollaborator
- Thrasher Research Fundcollaborator
- British Columbia Childrens Hospital Foundationcollaborator
Study Sites (1)
BC Children's Hospital Research Institute
Vancouver, British Columbia, V5Z 2X8, Canada
Related Publications (6)
Nemetchek B, English L, Kissoon N, Ansermino JM, Moschovis PP, Kabakyenga J, Fowler-Kerry S, Kumbakumba E, Wiens MO. Paediatric postdischarge mortality in developing countries: a systematic review. BMJ Open. 2018 Dec 28;8(12):e023445. doi: 10.1136/bmjopen-2018-023445.
PMID: 30593550BACKGROUNDWiens MO, Kissoon N, Kumbakumba E, Singer J, Moschovis PP, Ansermino JM, Ndamira A, Kiwanuka J, Larson CP. Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project. Afr Health Sci. 2016 Mar;16(1):162-9. doi: 10.4314/ahs.v16i1.22.
PMID: 27358628BACKGROUNDNemetchek BR, Liang LD, Kissoon N, Ansermino JM, Kabakyenga J, Lavoie PM, Fowler-Kerry S, Wiens MO. Predictor variables for post-discharge mortality modelling in infants: a protocol development project. Afr Health Sci. 2018 Dec;18(4):1214-1225. doi: 10.4314/ahs.v18i4.43.
PMID: 30766588BACKGROUNDWiens MO, Kumbakumba E, Larson CP, Ansermino JM, Singer J, Kissoon N, Wong H, Ndamira A, Kabakyenga J, Kiwanuka J, Zhou G. Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models. BMJ Open. 2015 Nov 25;5(11):e009449. doi: 10.1136/bmjopen-2015-009449.
PMID: 26608641BACKGROUNDEnglish LL, Dunsmuir D, Kumbakumba E, Ansermino JM, Larson CP, Lester R, Barigye C, Ndamira A, Kabakyenga J, Wiens MO. The PAediatric Risk Assessment (PARA) Mobile App to Reduce Postdischarge Child Mortality: Design, Usability, and Feasibility for Health Care Workers in Uganda. JMIR Mhealth Uhealth. 2016 Feb 15;4(1):e16. doi: 10.2196/mhealth.5167.
PMID: 26879041BACKGROUNDWiens MO, Kumbakumba E, Larson CP, Moschovis PP, Barigye C, Kabakyenga J, Ndamira A, English L, Kissoon N, Zhou G, Ansermino JM. Scheduled Follow-Up Referrals and Simple Prevention Kits Including Counseling to Improve Post-Discharge Outcomes Among Children in Uganda: A Proof-of-Concept Study. Glob Health Sci Pract. 2016 Sep 29;4(3):422-34. doi: 10.9745/GHSP-D-16-00069. Print 2016 Sep 28.
PMID: 27628107BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Matthew O Wiens, PharmD, PhD
University of British Columbia
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- NONE
- Purpose
- TREATMENT
- Intervention Model
- SEQUENTIAL
- 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
July 16, 2017
Primary Completion
January 31, 2024
Study Completion
March 31, 2024
Last Updated
February 15, 2023
Record last verified: 2023-02
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.
At each stage of the analysis and data preparation all of the study data will be prepared for public distribution. 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 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 study data will be made publically available using a reputable data hosting service (e.g. INDEPTH Data Repository, Dataverse etc.). During the data analysis stage, data lacking patient identifiers will be accessed from REDCap by team members involved in the statistical analysis.