Factors affecting sustainability of mHealth decision support tools and mHealth technologies in Malawi

Chirambo, Griphin Baxter; Muula, Adamson S; Thompson, Matthew

doi:10.1016/j.imu.2019.100261

Cited by 16 publications

(12 citation statements)

References 28 publications

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“…Regarding the factors related to the project design and implementation factors such as barriers associated with usability issues, unavailable and unreliable or expensive internet access, unreliable electricity at the workplace, limited access to computers, extra time involved in using the system, challenges associated with a hybrid system of paper and DHIs, perception of no practical benefits of using the electronic system, insufficient understanding and infrastructure to scale up effectively, and inadequate availability and accessibility of health equipment. These results corroborate those of Chirambo, Muula, & Thompson ( 31 ) for whom the telecommunication infrastructure was also found to be crucial for the mHealth decision-making program to be sustainable in Malawi. Another study noted a similar result ( 32 ).…”

Section: Discussionsupporting

confidence: 87%

“…In addition, stakeholders who are engaged in sustainable mHealth programmes in resource-poor settings can be used to develop an evidence-based policy for the utilization of technology for healthcare delivery across developing countries ( 32 ). Chirambo, Muula, & Thompson ( 31 ) in Malawi revealed that the sustainability of mHealth tools for children under 5 care can depend on a robust level of political commitment from the government working in collaboration with NGOs involved in these technologies. Strong political commitment is more than ever necessary for a better accompaniment and good guidance for the sustainability of DHIs in LMICs.…”

Section: Discussionmentioning

confidence: 99%

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Barriers and facilitators for the sustainability of digital health interventions in low and middle-income countries: A systematic review

Kaboré

Ngangue

Soubeiga

et al. 2022

Front. Digit. Health

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BackgroundDigital health interventions (DHIs) have increased exponentially all over the world. Furthermore, the interest in the sustainability of digital health interventions is growing significantly. However, a systematic synthesis of digital health intervention sustainability challenges is lacking. This systematic review aimed to identify the barriers and facilitators for the sustainability of digital health intervention in low and middle-income countries.MethodsThree electronic databases (PubMed, Embase and Web of Science) were searched. Two independent reviewers selected eligible publications based on inclusion and exclusion criteria. Data were extracted and quality assessed by four team members. Qualitative, quantitative or mixed studies conducted in low and middle-income countries and published from January 2000 to May 2022 were included.ResultsThe sustainability of digital health interventions is very complex and multidimensional. Successful sustainability of digital health interventions depends on interdependent complex factors that influence the implementation and scale-up level in the short, middle and long term. Barriers identified among others are associated with infrastructure, equipment, internet, electricity and the DHIs. As for the facilitators, they are more focused on the strong commitment and involvement of relevant stakeholders: Government, institutional, sectoral, stakeholders' support, collaborative networks with implementing partners, improved satisfaction, convenience, privacy, confidentiality and trust in clients, experience and confidence in using the system, motivation and competence of staff. All stakeholders play an essential role in the process of sustainability. Digital technology can have long term impacts on health workers, patients, and the health system, by improving data management for decision-making, the standard of healthcare service delivery and boosting attendance at health facilities and using services. Therefore, management changes with effective monitoring and evaluation before, during, and after DHIs are essential.ConclusionThe sustainability of digital health interventions is crucial to maintain good quality healthcare, especially in low and middle-income countries. Considering potential barriers and facilitators for the sustainability of digital health interventions should inform all stakeholders, from their planning until their scaling up. Besides, it would be appropriate at the health facilities level to consolidate facilitators and efficiently manage barriers with the participation of all stakeholders.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Barriers and facilitators for the sustainability of digital health interventions in low and middle-income countries: A systematic review

Kaboré

Ngangue

Soubeiga

et al. 2022

Front. Digit. Health

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“…A stepped-wedge design has significant advantages over a simple before and after design as it attempts to minimize potential temporal biases and provides a more powerful study design using a control group. We selected referrals as the main trial outcome as this is a major driver of health care use, and there is currently evidence that underreferral contributes to child morbidity [ 38 , 39 ]. We believe that this study provides a high degree of generalizability to similar settings in sub-Saharan Africa, where CCM is used.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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

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“…Moreover, functioning of HMIS remains ineffective in developing world, and there are still many obstacles to overcome before its effective and successful implementation [9]. Blingaut, 2018, indicated in his study that only 60 % of physicians reported having an effective and fully functional HIS system, while 40 % reported having an average peforming system.…”

Section: Introductionmentioning

confidence: 99%

Users Perception and Factors Affecting Data Quality in Nyarugenge Public Health Facility, Rwanda

Habimana

Rutayisire

2022

JPHI

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The study evaluated the users' opinions on data quality and related characteristics in ten public-health institutions of Nyarugenge district. A study used a cross-sectional design, data was collected through quantitative (n=150) methodology while qualitative data was obtained using interviews (n=20) and focus group talks (n=3). A checklist was utilized to examine the completeness, accuracy, and timeliness of data quality aspects. Collected quantitative data was analyzed through logistic regression by SPSS to examine the association of variables, while qualitative data was analyzed using the summative content analysis (SCA) to summarize the key themes. A 95 percent confidence level, Odds Ratio (AOR) were used to establish the strength of correlation among study variables, while a p-value of less than (p<0.05) was utilized to identify the variables which were statistically significant associated to HMIS data quality. The study finding showed that the majority (53.0%) was female while, 33 years was an average age, the majority of health practitioner (52.7%) had an A1 diploma. Approximately 90.6% of respondents have a positive perceptions on the system usage. Limited ability and a lack of relevant technology equipment such as computers and the internet have been cited as the challenges while using the system. Factors such as training AOR:2.62(95% CI:1.45, supervision AOR:1.81(95% CI:1.02, AOR:2.50(95% CI:0.85 for education background, works-experience AOR:1.60(95% CI:090 are factors associated with data quality. Maintaining, supportive supervision, regular training and refresher courses should be regularly offered to public health professionals to improve their knowledge in order to maximize the use of health information.

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Factors affecting sustainability of mHealth decision support tools and mHealth technologies in Malawi

Cited by 16 publications

References 28 publications

Barriers and facilitators for the sustainability of digital health interventions in low and middle-income countries: A systematic review

Barriers and facilitators for the sustainability of digital health interventions in low and middle-income countries: A systematic review

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

Users Perception and Factors Affecting Data Quality in Nyarugenge Public Health Facility, Rwanda

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