A mixed-methods quasi-experimental evaluation of a mobile health application and quality of care in the integrated community case management program in Malawi

Abstract

Background The use of mobile health (mHealth) technology to improve quality of care (QoC) has increased over the last decade; limited evidence exists to espouse mHealth as a decision support tool, especially at the community level. This study presents evaluation findings of using a mobile application for integrated community case management (iCCM) by Malawi’s health surveillance assistants (HSAs) in four pilot districts to deliver lifesaving services for children. Methods A quasi-experimental study design compared adherence to iCCM guidelines between HSAs using mobile application (n = 137) and paper-based tools (n = 113), supplemented with 47 key informant interviews on perceptions about QoC and sustainability of iCCM mobile application. The first four sick children presenting to each HSA for an initial consultation of an illness episode were observed by a Ministry of Health iCCM trainer for assessment, classification, and treatment. Results were compared using logistic regression, controlling for child-, HSA-, and district-level characteristics, with Holm-Bonferroni-adjusted significance levels for multiple comparison. Results HSAs using the application tended to assess sick children according to iCCM guidelines more often than HSAs using paper-based tools for cough (adjusted proportion, 98% vs 91%; P < 0.01) and five physical danger signs – chest in-drawing; alertness; palmar pallor; malnourishment; oedema (80% vs 62%; P < 0.01), but not for fever (97% vs 93%; P = 0.06), diarrhoea (94% vs 87%; P = 0.03), and three danger signs – not able to eat or drink; vomits everything; has convulsions (88% vs 79%; P = 0.01). Across illnesses and danger signs, 81% of HSAs using the application correctly classified sick children, compared to 58% of HSAs using paper-based tools ( P < 0.01). No differences existed for their treatment ( P = 0.27). Interview respondents corroborated these findings that using iCCM mobile application ensures protocol adherence. Respondents noted barriers to its consistent and wide use including hardware problems and limited resources. Conclusion Generally, the mobile application is a promising tool for improving adherence to the iCCM protocol for assessing sick children and classifying illness by HSAs. Limited effects on treatments and inconsistent use suggest the need for more studies on mHealth to improve QoC at community level.

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“…Another quasi-experimental study in Malawi comparing adherence to iCCM guidelines by CHWs using mHealth- and paper-based tools demonstrated increased quality of care (QoC) in under five children with pneumonia, diarrhoea, and malaria whereby 80% of the CHWs in intervention group using the mHealth tool managed illnesses according to a gold standard as compared to 50% in control group [ 41 ].…”

Long-term quality of integrated community case management care for children in Bugoye Subcounty, Uganda: a retrospective observational study

“…Some have documented correct care for 70%–90% of encounters 18 26–28. Others have documented lower quality of care overall19 29 or in the control group or preassessment evaluation in several intervention studies 30 31. Local context might explain some of the variation in quality of care.…”

eHealth Tools That Assess and Track Health and Well-being in Children and Young People: Systematic Review

“…Of the 23% (9/39) of studies that solely assessed mental health, 33% (3/9) focused on suicide prevention [8,39,40], 22% (2/9) focused on early intervention and prevention of mental illness [7,17], and 44% (4/9) focused on multidimensional assessment or management of mental health symptoms [41][42][43][44]. Of the 23% (9/39) of studies that solely assessed general health, 22% (2/9) focused on symptom detection and monitoring [9,45], 22% (2/9) provided a platform for patients to view and monitor their health information [46,47], 33% (3/9) focused on digitalized tracking of clinical decision-making [19,48,49], and 22% (2/9) were primarily for assessment [50,51].…”

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