1,720,983 research outputs found
Smart Discharges Transition to Scale
No full textDataset Description: This dataset contains materials from a the Smart Discharges Transition to Scale parent study within the Smart Discharges program of research. Materials include the parent study protocol and associated documents. See the Metadata section below for links to related publications and datasets.
Background: In Uganda, approximately 5% of children admitted with severe infections die after they have been discharged from the hospital, mostly at home. Most of these deaths are preventable as they are largely due to the way that discharges are done and how follow-ups are planned. Health workers and caregivers are often unaware of this period of vulnerability and are poorly equipped to identify and handle this critical situation. Our previous work focused on developing and evaluating 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. The goal of this project is to determine how best to scale the Smart Discharges Program through a four-phased approach, each corresponding to a specific objective. Phase I : aims to understand the reasons for suboptimal discharge by evaluating the pediatric discharge process from hospital admission through the transition to care within the community. Phase II : aims to assess pediatric discharge policies and facility readiness for change in a nationally representative sample of health facilities in Uganda. Phase III : aims to evaluate the effects of the Smart Discharges Health Worker Training Program on discharge care practices and procedures. Phase IV : aims to complete the facility-based linkage to care through the use of a community-based follow-up system.
Methods: Each of the four project phases utilizes different research methodologies. Phase I is a mixed methods prospective study utilizing patient journey mapping, discharge process mapping, and focus group discussions at 3 Ugandan Hospitals. Phase II is a cross-sectional, survey-based study conducted at 36 health facilities providing in-patient pediatric care in Uganda. Phase III and IV : (implemented together) is a quality improvement intervention at 16 health facilities in Uganda.
Discussion: Ultimately this work is focused on ensuring widespread adoption of Smart Discharges practices throughout Uganda by building capacity that ensures sustainability. Exploring and characterizing the existing pediatric discharge process, including human and health system factors that impact this process, will allow us to operationalize the Smart Discharges innovation into an effective health-systems approach to this neglected issue.
Ethics Declaration: Ethics approvals have been obtained from the Makerere University School of Public Health (MakSPH) Institutional Review Board (PI: 850; PII: 851; PIII/IV: 836), the Uganda National Council of Science and Technology (UNCST) in Uganda (PI: HS929ES; PII: HS928ES; PIII/IV: HS926ES) and the University of British Columbia in Canada (PI-IV: H20-02519). NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab Coordinator at [email protected] or visit our website
Transitions from hospital to home: A mixed methods study to evaluate pediatric discharges in Uganda
No full textBackground: The World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) guidelines recognize the importance of discharge planning to ensure continuation of care at home and appropriate follow-up. However, insufficient attention has been paid to post discharge planning in many hospitals contributing to poor implementation. To understand the reasons for suboptimal discharge, we evaluated the pediatric discharge process from hospital admission through the transition to care within the community in Ugandan hospitals.
Methods: This mixed methods prospective study enrolled 92 study participants in three phases: patient journey mapping for 32 admitted children under-5 years of age with suspected or proven infection, discharge process mapping with 24 pediatric healthcare workers, and focus group discussions (FDGs) with 36 primary caregivers and fathers of discharged children. Data were descriptively and thematically analyzed.
Findings: The typical discharge process is often not centered around the needs of the child and family. Discharge planning often does not begin until immediately prior to discharge and generally does not include caregiver input. Discharge education and counselling are generally limited, rarely involves the father, and does not focus significantly on post-discharge care or follow-up. Delays in the discharge process itself occur at multiple points, including while awaiting a physical discharge order and then following a discharge order, mainly with billing or transportation issues.
Data Collection Methods: Journey mapping data were collected using the REDCap Mobile App and were then uploaded to a REDCap database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). Study nurses conducted direct observation during in-hospital care as well as caregiver interviews at admission and 72 hours post-discharge using a series of checklists and close-ended questions with some open-entry questions to identify process outcomes as well as barriers and facilitators to the patient’s journey. Healthcare provider working groups engaged in two brainstorming sessions per hospital to develop a process map of each hospital’s current pediatric discharge process and to identify inefficiencies to care and potential solutions. Using paper, pens, and sticky notes, group members jointly mapped out the discharge pathways of their respective facilities and jointly identified all stages of the process. Data were captured using worksheets and audio recordings. A trained research assistant facilitated FGD two weeks after direct observation concluded with patient caregivers. Participants were asked to respond to open-ended questions that focused on their experiences regarding their child’s admission, hospital stay, discharge and post-discharge. All FGDs were digitally recorded, transcribed verbatim and translated into English by external individuals fluent in the languages. Healthcare provider working groups engaged in two brainstorming sessions per hospital to develop a map of each hospital’s current pediatric discharge process and to identify inefficiencies to care and potential solutions.
Ethics Declaration: Ethical approvals were obtained from Makerere University (HDREC #850), Uganda National Council for Science and Technology (#HS929ES) and the University of British Columbia (UBC C&W REB # H20-02519).
Study Protocol & Supplementary Materials:
Smart Discharges Transition to ScaleNOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at [email protected] or visit our website
Pediatric post-discharge mortality in resource-poor countries: a systematic review and meta-analysis
No full textBackground:
Under-five mortality remains concentrated in resource-poor countries. Post-discharge mortality is becoming increasingly recognized as a significant contributor to overall child mortality. With a substantial recent expansion of research and novel data synthesis methods, this study aims to update the current evidence base by providing a more nuanced understanding of the burden and associated risk factors of pediatric post-discharge mortality after acute illness.
Methods: Eligible studies published between January 1, 2017 and January 31, 2023, were retrieved using MEDLINE, Embase, and CINAHL databases. Studies published before 2017 were identified in a previous review and added to the total pool of studies. Only studies from countries with low or low-middle Socio-Demographic Index with a post-discharge observation period greater than seven days were included. Risk of bias was assessed using a modified version of the Joanna Briggs Institute critical appraisal tool for prevalence studies. Studies were grouped by patient population, and 6-month post-discharge mortality rates were quantified by random-effects meta-analysis. Secondary outcomes included post-discharge mortality relative to in-hospital mortality, pooled risk factor estimates, and pooled post-discharge Kaplan–Meier survival curves. PROSPERO study registration: #CRD42022350975.
Findings: Of 1963 articles screened, 42 eligible articles were identified and combined with 22 articles identified in the previous review, resulting in 64 total articles. These articles represented 46 unique patient cohorts and included a total of 105,560 children. For children admitted with a general acute illness, the pooled risk of mortality six months post-discharge was 4.4% (95% CI: 3.5%–5.4%, I2 = 94.2%, n = 11 studies, 34,457 children), and the pooled in-hospital mortality rate was 5.9% (95% CI: 4.2%–7.7%, I2 = 98.7%, n = 12 studies, 63,307 children). Among disease subgroups, severe malnutrition (12.2%, 95% CI: 6.2%–19.7%, I2 = 98.2%, n = 10 studies, 7760 children) and severe anemia (6.4%, 95% CI: 4.2%–9.1%, I2 = 93.3%, n = 9 studies, 7806 children) demonstrated the highest 6-month post-discharge mortality estimates. Diarrhea demonstrated the shortest median time to death (3.3 weeks) and anemia the longest (8.9 weeks). Most significant risk factors for post-discharge mortality included unplanned discharges, severe malnutrition, and HIV seropositivity.
Interpretation:
Pediatric post-discharge mortality rates remain high in resource-poor settings, especially among children admitted with malnutrition or anemia. Global health strategies must prioritize this health issue by dedicating resources to research and policy innovation.
Data Processing Methods:
Data were extracted using a standard data extraction form developed by the review authors. Kaplan–Meier survival curves, where provided, were extracted using a plot digitizer. The data extraction file, “PDMSR2024_DataExtraction_Dataset_SD” was generated as described above and analyzed as is.
Co-ordinates were extracted from the survival curves in their original, published form, using a plot digitizer (https://automeris.io/WebPlotDigitizer/). The co-ordinates for each survival curve were then cleaned up to:
1. Re-scale the time points to weeks
2. Curves which reported % mortality were converted to % survival (1 – mortality)
3. First co-ordinate was set to (0, 1), i.e., survival is 100% at time-point 0
4. Include the numbers at risk (if reported), primary reference, and subgroup information
Using these cleaned co-ordinates, individual-level patient data were extracted (see Guyot et al, 2012, doi.org/10.1186/1471-2288-12-9) and the survival curves re-constructed to obtain the survival and number at risk at specified time-points (0-52 weeks). Where possible, disease and age subgroups were combined to create all admissions curves by combining the individual-level patient data from multiple curves in the same study.
Additional data from the survival curves were extracted to produce the “PDMSR2024_AdditionalDataSurvivalCurves6M_Dataset_SD” and “PDMSR2024_AdditionalDataSurvivalCurves12M_Dataset_SD” files by extracting the survival rate at 6 and 12 months.
Previously unpublished hazards ratios were extracted from the dataset used in the Wiens et al (2015) study on post-discharge mortality (doi:10.1136/bmjopen-2015-009449) to produce the “PDMSR2024_Wiens2015HazardsRatios_Dataset_SD.xlsx” file. These original data are published on Dataverse at: doi.org/10.5683/SP2/VBPLRM
Analyses were in R version 4.3.0 (R Foundation for Statistical Computing, Vienna, Austria), and RStudio version 2023.6.1 (RStudio, Boston, MA).
Additional Files:
Survival curves in their original, published form, as well as survival curve coordinates files can be made available by request.NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at [email protected] or visit our website
Epidemiology of pediatric post-discharge mortality in Rwanda
No full textBackground:In Sub-Saharan Africa, pediatric post-discharge death is increasingly recognized as an important contributor to mortality. To address morbidity and mortality during this period, it is critical to generate a representative evidence base throughout sub-Saharan Africa to inform resource prioritization, as well as policy and guideline development. To date, no studies have been conducted in Rwanda, limiting the understanding of the epidemiology of post-discharge mortality in this region. This study aims to describe the epidemiology of post-discharge mortality in a group of children admitted for suspected sepsis in Rwanda.
Methods: We prospectively recruited children aged 0-60 months admitted for suspected sepsis at two sites in Rwanda: Ruhengeri Referral Hospital in Musanze, Rwanda (rural) and University Hospital of Kigali in Kigali, Rwanda (urban) from May 2022 - February 2023. Clinical, laboratory and social variables were collected at admission. Following discharge, participants were followed up to 6 months to determine vital status and health-seeking. We analyzed data in two age-specific cohorts, defined a priori: 0-6m and 6-60m. Multivariate logistic regression was used to identify risk factors. Age-stratified Kaplan-Meier curves were used to estimate the cumulative hazard of 6-month post-discharge mortality.
Findings:Of 1218 children enrolled, 115 died (11%): 50% in-hospital (n=57) and 50% after discharge (n=58). Post-discharge mortality was higher in 0-6m cohort (n=28/274, 10%) than in those 6-60m (30/850, 4%), and in Kigali (n=37/413, 9%) vs Ruhengeri (n=21/805, 3%). Median time to post-discharge death was ~1 month (38d in 0-6m; 33d in 6-60m). In both cohorts, increased odds of post-discharge death were associated with weight-for-age z-score 2h (OR=4.63 (1.40-15.22)) and being referred for higher level of care (OR=4.09 (1.04-16.12)) were significant in 6-60 months. Younger children were at highest risk of cumulative mortality.
Ethics Declaration: Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795).<br /
Validation of a risk-prediction model for pediatric post-discharge mortality at two hospitals in Rwanda
No full textBackground:Mortality following hospital discharge remains a significant threat to child health, particularly in resource-limited settings. In Uganda, the Smart Discharges risk-prediction models have demonstrated success in their ability to predict those at highest risk of death after discharge and use this to guide a risk-based approach to post-discharge care in children admitted with suspected sepsis. Respective prediction models for post-discharge mortality in ages 0-6 months and ages 6-60 months were developed in this cohort but have not yet been validated outside of Uganda. This study aimed to externally validate existing risk prediction models for pediatric post-discharge mortality within the Rwandan context.
Methods: Prospective cohort of children 0d-60 mos admitted with suspected sepsis at two hospitals in Rwanda: Ruhengeri Referral Hospital in Musanze (rural) and University Hospital of Kigali in Kigali (urban) from May 2022 to February 2023. Vital status follow up was conducted at 2-, 4- and 6-months post-discharge.
Five existing models from Smart Discharges Uganda were validated in this cohort: two models for children 0-6 months, and three for children 6-60 months. Models were applied to each participant in the Rwanda cohort to obtain a risk score which was then used to calculate predicted probability of post-discharge death. Model performance was evaluated by comparing to observed outcomes and to determine sensitivity, specificity, and AUROC. Threshold was set at 80% sensitivity.
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Findings:In a cohort of 1218 children, 1123 children (96.7%) completed follow up. The overall rate of post-discharge mortality was 4.8% (n=58). The highest performing models had an AUROC of 0.75 (0-6 mos) and 0.74 (6-60mos), respectively. All five prediction models tested achieved an AUROC greater than 0.7 (range 0.706 - 0.738). Model degradation (determined by the percent reduction in AUC between the original model and the derived model) was relatively low, ranging from from 1.1% to 7.7%. Calibration plots showed good calibration for all models at predicted probabilities below 10%. There were too few outcomes to assess calibration among those at higher levels of predicted risk.
Data Processing Methods:
Ethics Declaration: Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795).NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at [email protected] or visit our website
PRIME-IPD SERIES Part 3. The PRIME-IPD tool fills a gap in guidance for preparing IPD for analysis
No full textThis is the accepted manuscript version of the work published in its final form as Dewidar, Omar; Riddle, Alison; Ghogomu, Elizabeth; Hossain, Alomgir; Arora, Paul; Bhutta, Zulfiqar A; Black, Robert E; Cousens, Simon; Mathew, Christine; Trawin, Jessica; Tugwell, Peter; Welch, Vivian; Wells, George A. Plant Breeding; Volume: 136; Pages: 224-226; https://doi.org/10.1016/j.jclinepi.2021.05.001
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<6m Observation - Pulse Oximetry (dataset) ~ Smart Discharges
No full textPulse oximetry dataset from Smart Discharges NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab.
Smart Discharges Uganda Under 5: Phase II clinical data of children 6-60 months - pulse oximetry
No full textThis data is a subset of the Smart Discharges Uganda Under 5 years parent study and is specific to the Phase II interventional cohort of children aged 6-60 months containing pulse oximetry data.
Background: Substantial mortality occurs after hospital discharge in children under 5 years old with suspected sepsis. This study aimed to refine and externally validate a previously developed post-discharge mortality prediction model.
Methods: In this prospective observational cohort study, we recruited 0-6-month-old children admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. The primary outcome was six-month post-discharge mortality among those discharged alive.
Data Collection Methods: All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge.
Ethics Declaration: This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE).NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at [email protected] or visit our website
Smart Discharges Uganda Under 5: Phase I clinical data of children 0-6 months
No full textThis data is a subset of the Smart Discharges Uganda Under 5 years parent study and is specific to the Phase I observational cohort of children aged 0-6 months.
Objective(s): Used as part of the Smart Discharge prediction modelling for adverse outcomes such as post-discharge death and readmission.
Data Description: All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge. .
Data Processing: Created z-scores for anthropometry variables using height and weight according to WHO cutoff. Distance to hospital was calculated using latitude and longitude. Extra symptom and diagnosis categories were created based on text field in these two variables. BCS score was created by summing all individual components.
Limitations: There are missing dates and the admission, discharge, and readmission dates are not in order.
Ethics Declaration: This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE).NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab.
Smart Discharges to improve pediatric post-discharge survival
No full textBackground: In Sub-Saharan Africa, pediatric post-discharge death is increasingly recognized as an important contributor to mortality. Current studies evaluating interventional approaches for post-discharge mortality focus on pharmacologic therapy, though only malaria prophylaxis post-discharge appears effective. Approaches to reduce vulnerability through health system strengthening approaches may further help to improve outcomes. This study aimed to evaluate the impact of a risk-differentiated approach to improved peri-discharge care on post-discharge mortality among children under 60 months.
Methods: We conducted a prospective parallel cluster crossover trial at 6 hospitals in Uganda. Children
Findings: 13,050 patients were enrolled (phase 1: n=6954; phase 2: n=6096) and had complete 6-month follow-up. Baseline characteristics were similar between groups. The median age was 0.8 months (IQR: 0.2-1.7), with 56% of participants male. The multivariable risk algorithm gave a mean predicted risk of post-discharge mortality of 6.1% in phase 1 and 5.9% in phase 2. The rate of post-discharge mortality was 6.0% during phase 1 and 4.9% during phase 2, with an adjusted hazard ratio of 0.77 (95% CI – 0.90), favoring the intervention. Additional sensitivity analysis using different sets of covariates in the model showed similar results.
Ethics Declaration: These studies were approved by the Mbarara University of Science and Technology (No. 15/10-16), the Uganda National Council for Science and Technology (HS 2207), and the University of British Columbia (H16-02679).NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at [email protected] or visit our website
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