scholarly journals Effectiveness of smartphone-based Community Case Management on urgent referral, re-consultation and hospitalization of children under-5 in Malawi: Results of a cluster-randomized, stepped-wedge trial (Preprint)

2020 ◽  
Author(s):  
Griphin Supporting LIFE ◽  
Griphin Baxter Chirambo ◽  
Matthew Thompson ◽  
Victoria Hardy ◽  
Nicole Ide ◽  
...  
Keyword(s):  
Case Management ◽  
Hospital Admissions ◽  
Digital Health ◽  
Random Effect ◽  
Stepped Wedge ◽  
Community Case Management ◽  
Calendar Time ◽  
Intervention Phase ◽  
Cluster Randomized ◽  
The Impact

BACKGROUND Integrated community case management (CCM) has led to reductions in child mortality in Malawi from illnesses such as malaria, pneumonia and diarrhoea. However, adherence to CCM guidelines is often poor, potentially leading to inappropriate clinical decisions and outcomes. OBJECTIVE We determined the impact of an electronic version of CCM (eCCM) application on referral, re-consultation and hospitalization rates of children presenting to village clinics in Malawi. METHODS A stepped-wedge cluster-randomized trial compared paper-based CCM (control) with and without use of an eCCM app on smartphones from November 2016 to April 2017.A total of 102 village clinics from two districts in Northern Malawi were assigned to one of six clusters which were randomized to the sequencing of crossover from the control to the intervention phases, as well as the duration of exposure in each phase. Children ≥2 months to <5 years presenting with acute illness were enrolled consecutively by Health Surveillance Assistants (HSAs). The primary outcome of urgent referrals to higher-level facilities was evaluated using multi-level mixed effects models. A logistic regression model with random effect of cluster and fixed effect for each step was fitted. Adjustment for potential confounders included baseline factors, such as patient’s age, sex, and geographical location of village clinics. Calendar time was adjusted for in the analysis. RESULTS A total of 6965 children were recruited, 3421 in the control and 3544 in the intervention phase. After adjusting for calendar time, children in the intervention phase were more likely to be urgently referred to a higher-level health facility compared with children in the control phase (OR 2.02, 95% CI 1.27-3.23; p<0.01). Overall, children in the intervention arm had lower odds of attending a repeat HSA consultation (OR 0.45, 95% CI 0.34-0.59; p<0.01) or hospital admission (OR 0.75, 95% CI 0.62-0.90; p<0.01), but after adjusting for time these differences were not significant (p>0.05). CONCLUSIONS Addition of eCCM decision support led to a greater proportion of children being referred to higher-level facilities, with no apparent increase in hospital admissions or repeat consultations in village clinics. Our findings provide support for the implementation of eCCM tools in Malawi and other Low and Middle Income Countries (LMIC), with a need for ongoing assessment of effectiveness and integration with national digital health strategies. CLINICALTRIAL ClinicalTrials.gov; NCT02763345. Registered 3 May 2016

scholarly journals Effectiveness of smartphone-based Community Case Management on urgent referral, re-consultation and hospitalization of children under-5 in Malawi: Results of a cluster-randomized, stepped-wedge trial

2020 ◽  
Author(s):  
Griphin Baxter Chirambo ◽  
John Martin Odonoghue ◽  
Matthew Thompson ◽  
Adamson S Muula ◽  
Ciara Heavin ◽  
...  
Keyword(s):  
Case Management ◽  
Hospital Admissions ◽  
Digital Health ◽  
Random Effect ◽  
Stepped Wedge ◽  
Community Case Management ◽  
Calendar Time ◽  
Intervention Phase ◽  
Cluster Randomized ◽  
The Impact

Background: Integrated community case management (CCM) has led to reductions in child mortality in Malawi from illnesses such as malaria, pneumonia and diarrhea. However, adherence to CCM guidelines is often poor, potentially leading to inappropriate clinical decisions and outcomes. We determined the impact of an electronic version of CCM (eCCM) application on referral, re-consultation and hospitalization rates of children presenting to village clinics in Malawi. Methods: A stepped-wedge cluster-randomized trial compared paper-based CCM (control) with and without use of an eCCM app on smartphones from November 2016 to April 2017.A total of 102 village clinics from two districts in Northern Malawi were assigned to one of six clusters which were randomized to the sequencing of crossover from the control to the intervention phases, as well as the duration of exposure in each phase. Children ≥2 months to <5 years presenting with acute illness were enrolled consecutively by Health Surveillance Assistants (HSAs). The primary outcome of urgent referrals to higher-level facilities was evaluated using multi-level mixed effects models. A logistic regression model with random effect of cluster and fixed effect for each step was fitted. Adjustment for potential con-founders included baseline factors, such as patients age, sex, and geographical location of village clinics. Calendar time was adjusted for in the analysis. Results: A total of 6965 children were recruited, 3421 in the control and 3544 in the intervention phase. After adjusting for calendar time, children in the intervention phase were more likely to be urgently referred to a higher-level health facility compared with children in the control phase (OR 2.02, 95% CI 1.27-3.23; p<0.01). Overall, children in the intervention arm had lower odds of attending a repeat HSA consultation (OR 0.45, 95% CI 0.34-0.59; p<0.01) or hospital admission (OR 0.75, 95% CI 0.62-0.90; p<0.01), but after adjusting for time these differences were not significant (p>0.05). Conclusions: Addition of eCCM decision support led to a greater proportion of children being referred to higher-level facilities, with no apparent increase in hospital admissions or repeat consultations in village clinics. Our findings provide support for the implementation of eCCM tools in Malawi and other Low and Middle Income Countries (LMIC), with a need for ongoing assessment of effectiveness and integration with national digital health strategies.

scholarly journals Point-of-care molecular testing and antiviral treatment of influenza in residents of homeless shelters in Seattle, WA: study protocol for a stepped-wedge cluster-randomized controlled trial

Trials ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Kira L. Newman ◽  
◽  
Julia H. Rogers ◽  
Denise McCulloch ◽  
Naomi Wilcox ◽  
...  
Keyword(s):  
Point Of Care ◽  
Antiviral Treatment ◽  
Homeless Shelters ◽  
Molecular Testing ◽  
Symptom Duration ◽  
Homeless Shelter ◽  
Stepped Wedge ◽  
Site Testing ◽  
Cluster Randomized ◽  
The Impact

Abstract Introduction Influenza is an important public health problem, but data on the impact of influenza among homeless shelter residents are limited. The primary aim of this study is to evaluate whether on-site testing and antiviral treatment of influenza in residents of homeless shelters reduces influenza spread in these settings. Methods and analysis This study is a stepped-wedge cluster-randomized trial of on-site testing and antiviral treatment for influenza in nine homeless shelter sites within the Seattle metropolitan area. Participants with acute respiratory illness (ARI), defined as two or more respiratory symptoms or new or worsening cough with onset in the prior 7 days, are eligible to enroll. Approximately 3200 individuals are estimated to participate from October to May across two influenza seasons. All sites will start enrollment in the control arm at the beginning of each season, with routine surveillance for ARI. Sites will be randomized at different timepoints to enter the intervention arm, with implementation of a test-and-treat strategy for individuals with two or fewer days of symptoms. Eligible individuals will be tested on-site with a point-of-care influenza test. If the influenza test is positive and symptom onset is within 48 h, participants will be administered antiviral treatment with baloxavir or oseltamivir depending upon age and comorbidities. Participants will complete a questionnaire on demographics and symptom duration and severity. The primary endpoint is the incidence of influenza in the intervention period compared to the control period, after adjusting for time trends. Trial registration ClinicalTrials.gov NCT04141917. Registered 28 October 2019. Trial sponsor: University of Washington.

scholarly journals The influence of changes in activity-based financing on hospital readmissions for the elderly

2016 ◽  
Vol 4 (2) ◽  
pp. 72-81 ◽  
Author(s):  
Jun Yin ◽  
Fredrik A. Dahl ◽  
Terje P. Hagen ◽  
Hilde Lurås
Keyword(s):  
Readmission Rate ◽  
Hospital Admissions ◽  
Cox Regression ◽  
Average Length ◽  
Hospital Readmissions ◽  
Random Effect ◽  
The Elderly ◽  
Patient Specific ◽  
Readmission Rates ◽  
The Impact

Activity-based financing of Norwegian hospitals was implemented in 1997. An earlier study shows that when the activity-based component increases, the average length of stay for the elderly is reduced. If this reduction entails premature discharge, an increased activity-based component may have the undesirable side effect of increasing readmission rates. Yearly the Norwegian government decides the size of the activity-based component, and all hospitals face the same size. In this paper, we investigate whether the level of activity-based financing is associated with the readmission rates for acute-care patients above 70 years of age. The sample consisted of 468 010 hospital admissions among elderly patients in the period from 2000 to 2007. Using repeated cross-sectional data extracted from the Norwegian Patient Registry, a Cox regression model was used to estimate factors that may influence the hazard rate of a readmission within 30 days. The overall 30-day readmission rate was 6.6%. The results demonstrate that the activity-based component had no significant effect on the readmission rate. Patient-specific factors such as age, gender, diagnoses, comorbidities, as well as the time trend, were important predictors of readmission rates. We also found a statistically significant random effect of hospitals, although this effect was less substantial than the impact of patient characteristics. Our results show that the effect of the activity-based component on the readmission rate was negligible when it varied between 40% and 60%.Published: Online May 2016. In print August 2016.

scholarly journals Full title: My Baby’s Movements: a stepped-wedge cluster-randomised controlled trial of a fetal movement awareness intervention to reduce stillbirths

2021 ◽  
Author(s):  
Vicki Flenady ◽  
Glen Gardener ◽  
David Ellwood ◽  
Michael Coory ◽  
Megan Weller ◽  
...  
Keyword(s):  
Randomised Controlled Trial ◽  
Controlled Trial ◽  
Cluster Randomised Controlled Trial ◽  
Stillbirth Rate ◽  
Stepped Wedge ◽  
Calendar Time ◽  
Cluster Randomised ◽  
Maternity Hospitals ◽  
Randomised Controlled ◽  
The Impact

Objective The My Baby’s Movements (MBM) trial aimed to evaluate the impact on stillbirth rates of a multifaceted awareness package (MBM intervention). Design Stepped-wedge cluster-randomised controlled trial. Setting Twenty-seven maternity hospitals in Australia and New Zealand. Population Women with a singleton pregnancy without major fetal anomaly ≥28 weeks’ gestation from August 2016-May 2019. Methods The MBM intervention was implemented at randomly assigned time points with sequential introduction into 8 clusters of 3-5 hospitals at four-monthly intervals. The stillbirth rate was compared in the control and intervention periods. Generalised linear mixed models controlled for calendar time, clustering, and hospital effects. Outcome Measures Stillbirth at ≥28 weeks’ gestation. Results There were 304,853 births with 290,219 meeting inclusion criteria: 150,079 in control and 140,140 in intervention periods. The stillbirth rate during the intervention was lower than the control period (2.2/1000 births versus 2.4, odds ratio [OR] 0.91, 95% Confidence Intervals [CI] 0.78-1.06, p=0.22). The decrease was larger across calendar time with 2.7/1000 in the first 18 months versus 2.0/1000 in the last 18 months (OR 0.74; 95% CI 0.63-0.86; p≤0.01). Following adjustment, stillbirth rates between the control and intervention periods were not significantly different: (aOR 1.18, 95% CI 0.93-1.50; p=0.18). No increase in secondary outcomes, including obstetric intervention or adverse neonatal outcome, was evident. Conclusion The MBM intervention did not reduce stillbirths beyond the downward trend over time, suggesting hospitals may have implemented best practice in DFM management outside their randomisation schedule. The role of interventions for raising awareness of DFM remains unclear

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