Effectiveness of Smartphone-Based Community Case Management on the Urgent Referral, Reconsultation, and Hospitalization of Children Aged Under 5 Years in Malawi: Cluster-Randomized, Stepped-Wedge Trial

Author:

Chirambo Griphin BaxterORCID,Thompson MatthewORCID,Hardy VictoriaORCID,Ide NicoleORCID,Hwang Phillip HORCID,Dharmayat KanikaORCID,Mastellos NikolaosORCID,Heavin CiaraORCID,O'Connor YvonneORCID,Muula Adamson SORCID,Andersson BoORCID,Carlsson SvenORCID,Tran TammyORCID,Hsieh Jenny Chen-LingORCID,Lee Hsin-YiORCID,Fitzpatrick AnnetteORCID,Joseph Wu Tsung-ShuORCID,O'Donoghue JohnORCID

Abstract

Background Integrated community case management (CCM) has led to reductions in child mortality in Malawi resulting from illnesses such as malaria, pneumonia, and diarrhea. However, adherence to CCM guidelines is often poor, potentially leading to inappropriate clinical decisions and poor outcomes. We determined the impact of an e-CCM app on the referral, reconsultation, and hospitalization rates of children presenting to village clinics in Malawi. Objective We determined the impact of an electronic version of a smartphone-based CCM (e-CCM) app on the referral, reconsultation, and hospitalization rates of children presenting to village clinics in Malawi. Methods We used a stepped-wedge, cluster-randomized trial to compare paper-based CCM (control) with and without the use of an e-CCM app on smartphones from November 2016 to February 2017. A total of 102 village clinics from 2 districts in northern Malawi were assigned to 1 of 6 clusters, which were randomized on the sequencing of the crossover from the control phase to the intervention phase as well as the duration of exposure in each phase. Children aged ≥2 months to <5 years who presented with acute illness were enrolled consecutively by health surveillance assistants. The primary outcome of urgent referrals to higher-level facilities was evaluated by using multilevel mixed effects models. A logistic regression model with the random effects of the cluster and the fixed effects for each step was fitted. The adjustment for potential confounders included baseline factors, such as patient age, sex, and the geographical location of the village clinics. Calendar time was adjusted for in the analysis. Results A total of 6965 children were recruited—49.11% (3421/6965) in the control phase and 50.88% (3544/6965) 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 than children in the control phase (odds ratio [OR] 2.02, 95% CI 1.27-3.23; P=.003). Overall, children in the intervention arm had lower odds of attending a repeat health surveillance assistant consultation (OR 0.45, 95% CI 0.34-0.59; P<.001) or being admitted to a hospital (OR 0.75, 95% CI 0.62-0.90; P=.002), but after adjusting for time, these differences were not significant (P=.07 for consultation; P=.30 for hospital admission). Conclusions The addition of e-CCM decision support by using smartphones 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 e-CCM tools in Malawi and other low- and middle-income countries with a need for ongoing assessments of effectiveness and integration with national digital health strategies. Trial Registration ClinicalTrials.gov NCT02763345; https://clinicaltrials.gov/ct2/show/NCT02763345

Publisher

JMIR Publications Inc.

Subject

Health Informatics

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