End-user perspectives of two mHealth decision support tools: Electronic Community Case Management in Northern Malawi
Introduction
Many low- and middle-income countries (LMICs) experience high mortality rates among children under-five [1]. Although childhood mortality rates in Malawi have steadily declined over the last decade, under-five mortality rates remain high at 54 per 1000 in 2018 [2].
To improve access to essential healthcare services for the marginalized Malawian communities, Health Surveillance Assistants (HSAs) were recruited. HSAs are allocated to hard-to-reach remote locations and serve a population of approximately 1,000 citizens [3]. Their role involves family planning, environmental health, HIV counselling as well as acute care of children under five years of age [4] through a Community Case Management (CCM) approach. CCM is a paper-based decision aid for management of children under 5 years with acute illness that uses simple signs and symptoms. HSAs are supervised by Integrated Management of Childhood Illness (IMCI) coordinators in a district.
There are concerns about inconsistent standards of delivery of CCM as some HSAs do not always adhere to all the steps in the protocol, potentially resulting in inappropriate clinical management decisions [5,6]. As such eCCM was introduced to circumvent the problem[7,8]. Two eCCM Apps have thus far been evaluated for use in Malawi; the Supporting LIFE electronic Community Case Management Application (SL eCCM App) [7,9] and D-Tree International’s Mangologic eCCM App [10]. Although both Apps are configured to support the delivery of CCM (i.e. they both are required to be used in conjunction with paper-based CCM), they have markedly different interfaces and functionality and are deployed on different types of mobile phones, potentially conferring very different end-user experiences.
Several published studies support the acceptability of using mHealth decision making tools [11], the perceptions of HSAs and community on using these mHealth decision making tools[9] and their added value for CCM in Malawi [12]. However, end-users appraisal of differing design features and functionality between available mHealth decision tools for CCM delivery, remains poorly understood. Therefore, this study aimed to explore end users perspectives of two eCCM decision support tools developed and implemented by the Supporting LIFE project (SL eCCM App) and D-Tree International’s (Mangologic eCCM App) and their implications for CCM in Northern Malawi.
This study applied a modified Mobile App Rating Scale (MARS) (Appendix 1) to evaluate two apps used in CCM. MARS is an evaluation toolkit developed to enable potential end-users to assess and rate the quality of an mHealth App [13,14].
Section snippets
Study design
A mixed method approach was used where interviews were conducted and a questionnaire was used to explore the functionality of the SL eCCM App and Mangologic eCCM App.
Study setting and Population
The study was conducted in Mzimba North, Nkhata Bay, and Rumphi districts of Northern Malawi where both SL eCCM App and Mangologic eCCM App were implemented at the time of this study. The study population were HSAs, and IMCI coordinators
Sampling and Sample size
A convenience sampling technique was used to select a total of 109 participants: 106 HSAs and 3
Participants Characteristics
109 participants completed the paper-based survey tool, this included the 34 interviewees. Of the total participants, of 106 HSAs - 53 completed SL eCCM App questionnaire and 53 completed Mangologic eCCM App questionnaire. The three IMCI coordinators completed both questionnaires. Appendix 3 provides an overview of all participants.
For the qualitative data, a total of 34 interviews were conducted of which 31 were HSAs (Nkhata Bay district 13, Mzimba North 7, and Rumphi district 11) and 3 IMCI
Discussion
This study provides an opportunity to examine two Apps which were designed for the identical purpose and deployed in the same northern region of Malawi. This paper presents evidence of end-user perspectives of these mHealth Apps and provides implications for other mHealth decision support tools relating to issues of user friendliness, technical intelligence, and practical implications.
The quantitative data suggest that there was no significant difference between both Apps. Our analysis revealed
Conclusion
Two different Apps, each developed to reproduce CCM guidelines for care of under 5 children with acute illness, provided HSA users with contrasting experiences. Each App had various positive and negative attributes. There were key issues highlighted that could affect their ongoing adoption by these users. Overall both Apps lead to identical diagnosis and treatment recommendations for sick children, which suggests fidelity to the original CCM clinical algorithm. We suggest developing a “best of
Data Availability
Data underlying the findings of the study will be made available on request through the College of Medicine, School of Public Health. The chairman can be contacted through the following email address: [email protected]
Author Contributions
All authors have made a substantial, direct, intellectual contributions to this study. Griphin Baxter Chirambo: study concept and design, data collection, data analysis and manuscript writing. Adamson S. Muula: analysis and interpretation of data, direction on manuscript writing, critical revision of the manuscript for important intellectual content. Matthew Thompson: direction on manuscript writing, critical revision of the manuscript for important intellectual content. John O, Donoghue:
Sources of funding for your research
This study received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 305292. The funder of this study had no role in the design of the study, analysis of the results, and preparation of the manuscript or decision to publish.
The statements made and views expressed are solely the responsibility of the authors.
Consent
The study was approved by COMREC and the certificate number is P.05/17/2191
Acknowledgements
The authors would like to thank the Supporting LIFE project consortium for the support rendered during the period of this study, the University of Malawi (College of Medicine) and Mzuzu University for allowing the authors to conduct the study and the Malawi Ministry of Health for supporting implementation of the study. We equally would like to acknowledge the time and effort made by all the study participants, which provided valuable insights making this research possible.
References (36)
- et al.
Electronic clinical decision algorithms for the integrated primary care management of febrile children in low-resource settings: review of existing tools
Clin. Microbiol. Infect.
(2018) Assessment of Malawi’s success in child mortality reduction through the lens of the Catalytic Initiative Integrated Health Systems Strengthening programme: Retrospective evaluation
J. Glob. Health
(2020)- Mortality rate, under-5, male (per 1,000 live births) - Malawi | Data. [Online]. Available:...
- et al.
Motivation of health surveillance assistants in Malawi: A qualitative study
Malawi Med. J.
(2016) - et al.
The Role of Heath Surveillance Assistants (HSAs) in the Delivery of Health Services and Immunization in Malawi - Eldis
(2001) - et al.
A mixed-methods quasi-experimental evaluation of a mobile health application and quality of care in the integrated community case management program in Malawi
J. Glob. Health
(2019) The importance of form field validation: Lessons learnt from a feasibility study of an mHealth application in Malawi, Africa
(2016)The added value of a mobile application of Community Case Management on referral, re-consultation and hospitalization rates of children aged under 5 years in two districts in Northern Malawi: Study protocol for a pragmatic, stepped-wedge cluster-randomize
Trials
(2017)- et al.
Reaching remote health workers in Malawi: Baseline assessment of a pilot mhealth intervention
J. Health Commun
(2012) Perceptions of a mobile health intervention for Community Case Management in Malawi : Opportunities and challenges for Health Surveillance Assistants in a community setting
Malawi Med. J.
(2018)
360 mHealth Analysis Technical Deep Dive
The added value of a mobile application of Community Case Management on referral, re-consultation and hospitalization rates of children aged under 5 years in two districts in Northern Malawi: study protocol for a pragmatic, stepped-wedge cluster-randomize
Trials
Mobile app rating scale: a new tool for assessing the quality of health mobile apps
JMIR mHealth uHealth
Mobile app rating scale: a new tool for assessing the quality of health mobile apps
JMIR mHealth uHealth
The importance of form field validation: Lessons learnt from a feasibility study of an mHealth application in Malawi, Africa
Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings
D-Tree: Examining the efficacy of a Community Case Management mobile medical diagnostic tool
Qualitative Research : Validity
Cited by (10)
Lessons Learned in Improving the Quality of a Free Reproductive Health Hotline in Benin
2023, Global Health Science and PracticePaediatric digital clinical decision support for global health
2023, Revue Medicale SuisseScoping review of health information technology usability methods leveraged in Africa
2023, Journal of the American Medical Informatics Association