Ignite Creation Date:
2024-05-06 @ 6:39 PM
Last Modification Date:
2024-10-26 @ 2:51 PM
Study NCT ID:
NCT05730387
Status:
RECRUITING
Last Update Posted:
2023-06-01
First Post:
2022-12-09
Brief Title:
Smart Discharges for Mom Baby
Sponsor:
University of British Columbia
Organization:
University of British Columbia
Study Overview
Official Title:
Smart Discharges for Mom Baby Saving Mother-newborn Dyads by Developing a Predictive Risk Model to Identify Vulnerable Dyads and Guide Delivery of Evidence-based Locally-informed Interventions for Targeted Post-discharge Care
Status:
RECRUITING
Status Verified Date:
2023-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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 7000 dyads in Uganda and engage with local stakeholders eg 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 investigators epidemiological study of post-delivery post-discharge outcomes in 3236 dyads in Uganda 2017-2020 results indicated that most newborn and maternal readmissions were due to infectious illness ie 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 WHO 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
Detailed Description:
PURPOSE
Neonatal outcomes are highly correlated with the health of the mother an example of this is shown repeatedly by poor rates of survival of infants after maternal death Prediction of risk based on the mother and infant as a pair is a major gap in current research and yet vital to the survival of both the mom and the infant Thus maternal and child health outcomes can be improved by identifying both mothers and babies at increased risk of mortality or serious morbidity after hospital discharge and allocating scarce resources for targeted follow-up to those most vulnerable This allows the investigators to not only improve health outcomes but benefits the health system with efficient use of resources
JUSTIFICATION
Since 2011 the investigators have been working with partners in Uganda to develop validate and implement an innovative program for children under 5 years who have been discharged following hospitalization for suspected sepsis In this research and implementation program called Smart Discharges healthcare workers use an individualized risk prediction score to identify children at high risk of death or complications after discharge from a hospital following treatment for suspected sepsis They can then use this score to guide the intensity of a counselling and community-referral program While all participants receive counselling only those above a certain risk threshold receive down-referrals to community health facilities The investigators have shown that this approach may reduce post-discharge child mortality after in-hospital treatment for suspected sepsis by as much as 30 Now the investigators are working to expand their innovative precision public health approach to improving post-discharge care for mother-newborn dyads
Findings will inform the development an evidence-based bundle of care for both the mother and newborn This package will ensure that low-risk mother-infant pairs receive less burdensome yet pragmatic and feasible postpartum care while high risk pairs receive a more extensive bundle of interventions such as education nutrition healthcare interaction and community support The Smart Discharges for Mom Baby package will include support targeting aspects of both clinical and emotional wellbeing Additional extensions of this work will include validating the risk models in women who deliver at home or suffer a stillbirth to ensure that more women and babies can benefit from the proposed intervention
HYPOTHESIS
Maternal and infant characteristics collected at the time of discharge following a facility delivery can predict the risk of maternal or neonatal death or need for re-admission within six weeks of birth
OBJECTIVE
The primary objective is to inform the development of an integrated maternal and newborn risk-based post-discharge care program Specifically the study aims to 1 develop and internally validate clinical risk prediction models for identifying dyads at high-risk of death or hospital readmission in the 6-week post-delivery post-discharge period and 2 identify gaps and opportunities during in-hospital discharge and post-discharge care to inform the future development of an evidence-and risk-based bundle of interventions to improve postnatal care PNC for dyads
DESIGN
This is a mixed-methods study using both quantitative and qualitative techniques to explore and map the current postnatal discharge processes in Uganda using data from two distinct hospital settings
Phase I The team will conduct an observational cohort study informed through direct observation of the mother and newborn dyad prior to facility discharge and after delivery and follow-up telephone interviews conducted at six-weeks post-discharge
Phase II The team will conduct journey mapping with a subset of dyads enrolled in the observational cohort using direct observation and follow-up telephone interviews
Phase III The team will conduct a process mapping exercise using focus group discussion methodology with select facility staff
Phase IV The team will conduct focus group discussions with a subset of mothers enrolled in the observational cohort as well as their family members
STATISTICAL ANALYSIS
Quantitative analysis The investigators will summarize all risk factors for mothers and newborns that do and do not experience poor outcomes and estimate univariate associations For newborns data will be reported by sex Derivation of prediction models will be based on optimization of the area under the receiver operating curve AUROC and specificity across a variety of modeling and variable selection approaches eg logistic regression elastic net support vector machines Model performance will be based on appropriate re-sampling techniques for internal validation eg cross-validation bootstrapping Focus will be on developing parsimonious predictive models eg 5-10 predictor variables with high sensitivity 80 AUROC sensitivity and specificity will be reported for each model along with positive and negative predictive values Site specific metrics will be compared to ensure consistency across settings and re-calibration may be considered if individual site performance is lower than expected Finally the investigators will assess combined sensitivity and specificity when each individual model is applied to the dyad Outside of prediction modelling the sample size will allow the investigators to detect an odds ratio of at least 130 for a given risk factor with 80 power and 5 significance and relative precision of 25 Statistical analysis of quantitative data from journey mapping observation surveys and patient interviews will be performed using R Statistical software to obtain descriptive statistics of the frequency and distribution of each variable
Qualitative Analysis the investigators will analyze data collected descriptively and report summary statistics A diagram of the discharge process will be developed identifying key areas for improvement during the peri-discharge and post-discharge process FGD data will be analyzed using a framework method which allows themes to be developed inductively from participants and deductively from existing literature Through an iterative process transcripts will be coded and analyzed for descriptive and interpretive themes using NVivo Descriptive themes include barriers to care and post-discharge health-seeking behaviour while interpretive themes focus on caregiver perspectives of maternal and neonatal death and the role of the health system The investigators will generate frequencies to describe reported medical symptoms health-seeking behaviour and barriers to care and summarize common themes Member checking will be used to improve the validity of the results creating a summary document of the main findings that will be reviewed by health workers who participated in the focus groups Feedback from patients and families will be obtained over telephone with research nurses who will explain the main findings verbally
Neonatal outcomes are highly correlated with the health of the mother an example of this is shown repeatedly by poor rates of survival of infants after maternal death Prediction of risk based on the mother and infant as a pair is a major gap in current research and yet vital to the survival of both the mom and the infant Thus maternal and child health outcomes can be improved by identifying both mothers and babies at increased risk of mortality or serious morbidity after hospital discharge and allocating scarce resources for targeted follow-up to those most vulnerable This allows the investigators to not only improve health outcomes but benefits the health system with efficient use of resources
JUSTIFICATION
Since 2011 the investigators have been working with partners in Uganda to develop validate and implement an innovative program for children under 5 years who have been discharged following hospitalization for suspected sepsis In this research and implementation program called Smart Discharges healthcare workers use an individualized risk prediction score to identify children at high risk of death or complications after discharge from a hospital following treatment for suspected sepsis They can then use this score to guide the intensity of a counselling and community-referral program While all participants receive counselling only those above a certain risk threshold receive down-referrals to community health facilities The investigators have shown that this approach may reduce post-discharge child mortality after in-hospital treatment for suspected sepsis by as much as 30 Now the investigators are working to expand their innovative precision public health approach to improving post-discharge care for mother-newborn dyads
Findings will inform the development an evidence-based bundle of care for both the mother and newborn This package will ensure that low-risk mother-infant pairs receive less burdensome yet pragmatic and feasible postpartum care while high risk pairs receive a more extensive bundle of interventions such as education nutrition healthcare interaction and community support The Smart Discharges for Mom Baby package will include support targeting aspects of both clinical and emotional wellbeing Additional extensions of this work will include validating the risk models in women who deliver at home or suffer a stillbirth to ensure that more women and babies can benefit from the proposed intervention
HYPOTHESIS
Maternal and infant characteristics collected at the time of discharge following a facility delivery can predict the risk of maternal or neonatal death or need for re-admission within six weeks of birth
OBJECTIVE
The primary objective is to inform the development of an integrated maternal and newborn risk-based post-discharge care program Specifically the study aims to 1 develop and internally validate clinical risk prediction models for identifying dyads at high-risk of death or hospital readmission in the 6-week post-delivery post-discharge period and 2 identify gaps and opportunities during in-hospital discharge and post-discharge care to inform the future development of an evidence-and risk-based bundle of interventions to improve postnatal care PNC for dyads
DESIGN
This is a mixed-methods study using both quantitative and qualitative techniques to explore and map the current postnatal discharge processes in Uganda using data from two distinct hospital settings
Phase I The team will conduct an observational cohort study informed through direct observation of the mother and newborn dyad prior to facility discharge and after delivery and follow-up telephone interviews conducted at six-weeks post-discharge
Phase II The team will conduct journey mapping with a subset of dyads enrolled in the observational cohort using direct observation and follow-up telephone interviews
Phase III The team will conduct a process mapping exercise using focus group discussion methodology with select facility staff
Phase IV The team will conduct focus group discussions with a subset of mothers enrolled in the observational cohort as well as their family members
STATISTICAL ANALYSIS
Quantitative analysis The investigators will summarize all risk factors for mothers and newborns that do and do not experience poor outcomes and estimate univariate associations For newborns data will be reported by sex Derivation of prediction models will be based on optimization of the area under the receiver operating curve AUROC and specificity across a variety of modeling and variable selection approaches eg logistic regression elastic net support vector machines Model performance will be based on appropriate re-sampling techniques for internal validation eg cross-validation bootstrapping Focus will be on developing parsimonious predictive models eg 5-10 predictor variables with high sensitivity 80 AUROC sensitivity and specificity will be reported for each model along with positive and negative predictive values Site specific metrics will be compared to ensure consistency across settings and re-calibration may be considered if individual site performance is lower than expected Finally the investigators will assess combined sensitivity and specificity when each individual model is applied to the dyad Outside of prediction modelling the sample size will allow the investigators to detect an odds ratio of at least 130 for a given risk factor with 80 power and 5 significance and relative precision of 25 Statistical analysis of quantitative data from journey mapping observation surveys and patient interviews will be performed using R Statistical software to obtain descriptive statistics of the frequency and distribution of each variable
Qualitative Analysis the investigators will analyze data collected descriptively and report summary statistics A diagram of the discharge process will be developed identifying key areas for improvement during the peri-discharge and post-discharge process FGD data will be analyzed using a framework method which allows themes to be developed inductively from participants and deductively from existing literature Through an iterative process transcripts will be coded and analyzed for descriptive and interpretive themes using NVivo Descriptive themes include barriers to care and post-discharge health-seeking behaviour while interpretive themes focus on caregiver perspectives of maternal and neonatal death and the role of the health system The investigators will generate frequencies to describe reported medical symptoms health-seeking behaviour and barriers to care and summarize common themes Member checking will be used to improve the validity of the results creating a summary document of the main findings that will be reviewed by health workers who participated in the focus groups Feedback from patients and families will be obtained over telephone with research nurses who will explain the main findings verbally
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None