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.

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.

End-user perspectives of two mHealth decision support tools: Electronic Community Case Management in Northern Malawi.

BACKGROUND: The introduction of a paper-based Community Case Management (CCM) in Malawi has contributed to a reduction of child morbidity and mortality rates. In addition, the introduction of electronic Community Case Management (eCCM) (smartphones with built in CCM apps) may help to reduce the under-five mortality rates even further. PURPOSE: It is not uncommon for Apps with a similar area of interest to develop different features to assist the end users. Such differences between Apps may have a significant role to play in its overall adoption and integration. The purpose of this research was 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)in Northern Malawi. METHODS: A mixed methods approach was applied, involving a survey of 109 users (106 Health Surveillance Assistants (HSAs), and 3 Integrated Management of Childhood Il6lnesses (IMCI) coordinators). This was followed up with semi-structured interviews with 34 respondents (31 HSAs, and 3 IMCI coordinators). Quantitative data was analyzed using SPSS version 20 where descriptive statistics and Chi-Squared tests were generated. Qualitative data were analyzed based on thematic analysis. RESULTS: Participants reported that both Apps could assist the HSAs in the management of childhood illnesses. However, usability differed between the two apps where the Supporting LIFE eCCM App was found to be easier to use (61%) compared to the Mangologic eCCM App (4%). Both Apps were perceived to provide credible and accurate information. CONCLUSION: It is essential that the quality of the data within Mobile Health (mHealth) Apps is high, however even Apps with excellent levels of data quality may not succeed if the overall usability of the App is low. Therefore it is essential that the Apps has high levels of data quality, usability and credibility. The results of this study will help inform mobile Health (mHealth) App designers in developing future eCCM Apps as well as researchers and policy makers when considering the adoption of mHealth solutions in the future in Malawi and other LMICs.

Sustainability of 'mHealth' interventions in sub- Saharan Africa: a stakeholder analysis of an electronic community case management project in Malawi.

Background: The global health community and funding agencies are currently engaged in ensuring that worthwhile research-based programmes are sustainable. Despite its importance, few studies have analysed the sustainability of global health interventions. In this paper, we aim to explore barriers and facilitators for the wider implementation and sustainability of a mobile health (mHealth) intervention (Supporting LIFE Community Case Management programme) in Malawi, Africa. Methods: Between January and March 2017, a qualitative approach was used to carry out and analyse 13 in-depth semi-structured interviews with key stakeholders across all levels of healthcare provision in Malawi to explore their perceptions with regards to the implementation and sustainability of the mHealth programme. Data were analysed thematically by two reviewers. Results: Overall, our analysis found that the programme was successful in achieving its goals. However, there are many challenges to the wider implementation and sustainability of this programme, including the absence of monetary resources, limited visibility outside the healthcare sector, the lack of integration with community-based and nationwide programmes, services and information and communication technologies, and the limited local capacity in relation to the maintenance, further development, and management. Conclusions: Future developments should be aligned with the strategic goals and interests of the Ministry of Health and engage with national and international stakeholders to develop shared goals and strategies for nationwide scale-up. These developments should also focus on building local capacity by educating trainers and ensuring that training methods and guidelines are appropriately accredited based on national policies. Our findings provide a framework for a variety of stakeholders who are engaged in sustaining mHealth programmes in resource-poor settings and can be used to develop an evidence-based policy for the utilization of technology for healthcare delivery across developing countries.

People Welcomed This Innovation with Two Hands: A Qualitative Report of an mHealth Intervention for Community Case Management in Malawi.

INTRODUCTION: Community Case Management (CCM) aims to improve health outcomes among children under five with malaria, diarrhea, and pneumonia, but its effectiveness in Malawi is limited by inconsistent standards of delivery characteristic of paper-based interventions. This may lead to negative impacts on child health outcomes and inefficient use of health system resources. This study evaluated the acceptability and impact of the Supporting LIFE Community Case Management App (SL eCCM App) by Health Surveillance Assistants (HSAs) and caregivers in two districts of Northern Malawi. METHODS: Data were collected through semi-structured interviews with HSAs and caregivers as part of a nested study within a larger trial. We used deductive and inductive approaches during data analysis. Relevant constructs were identified from the Consolidated Framework for Implementation Research and combined with emerging concepts from the data. The Framework Method was used to chart and explore data, leading to the development of themes. RESULTS: Seventeen HSAs and 28 caregivers were interviewed. Participants were generally enthusiastic about the SL eCCM App. Nearly all HSAs expressed a preference for the App over routine paper-based CCM. Most HSAs claimed the App was more reliable and less error prone, facilitated more accurate diagnoses and treatment recommendations, and enhanced professional confidence and respect in the community. Some HSAs believed additional features would improve usability of the App, others identified mobile network or electricity shortages as barriers. Not all caregivers understood the purpose of the App, but most welcomed it as a health and technological advancement. CONCLUSION: The SL eCCM App is acceptable to both HSAs and caregivers, and in most cases, preferred, as it was believed to foster improvements in CCM delivery. Our findings suggest that mobile health interventions for CCM, such as the SL eCCM App, may have potential to improve the effectiveness and efficiency of care to children under five.

Perceptions of a mobile health intervention for Community Case Management in Malawi: Opportunities and challenges for Health Surveillance Assistants in a community setting.

Background: Improved availability of mobile phones in low- and middle-income countries (LMICs) offer an opportunity to improve delivery of Community Case Management (CCM). Despite enthusiasm for introducing mHealth into healthcare across LMICs, end-user attitudes towards mHealth solutions for CCM are limited. We aimed to explore Health Surveillance Assistants' (HSAs) perceptions of the Supporting LIFE electronic CCM Application (SL eCCM App) and their experiences incorporating it as part of their clinical practice. Methods: This exploratory qualitative study was part of a mixed methods feasibility study investigating whether children under-5 presenting to village clinics could be followed-up to collect patient outcome data. The convenience sample of 12 HSAs enrolled into the feasibility study participated in semi-structured interviews, which were conducted at village clinics after HSAs had field-tested the SL eCCM App over a 10-day period. Interviews explored HSAs perceptions of the SL eCCM App and their experiences in using the App in addition to paper CCM to assess and treat acutely unwell children. Open coding was used to label emerging concepts, which were iteratively defined and developed into six key themes. Results: HSAs' perceived enhanced clinical decision-making, quality of CCM delivery, and work efficiency as opportunities associated with using the SL eCCM App. HSAs believed the inability to retrieve patient records,, cumbersome duplicate assessments/data entry study procedures, and inconsistencies between the SL eCCM App and paper-based CCM guidelines as challenges to implementation. Adding features to the App, such as, permitting communication between colleagues/supervisors, drug stock-out reporting, and community assessments, were identified as potentially supporting HSAs' many roles in the community. Conclusion: This study identified opportunities and challenges associated with using the SL eCCM App in Malawi. This information can be used to inform future development and evaluation of the SL eCCM App, and similar mHealth solutions for CCM in Malawi and other developing countries.

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-randomized controlled trial.

BACKGROUND: There is evidence to suggest that frontline community health workers in Malawi are under-referring children to higher-level facilities. Integrating a digitized version of paper-based methods of Community Case Management (CCM) could strengthen delivery, increasing urgent referral rates and preventing unnecessary re-consultations and hospital admissions. This trial aims to evaluate the added value of the Supporting LIFE electronic Community Case Management Application (SL eCCM App) compared to paper-based CCM on urgent referral, re-consultation and hospitalization rates, in two districts in Northern Malawi. METHODS/DESIGN: This is a pragmatic, stepped-wedge cluster-randomized trial assessing the added value of the SL eCCM App on urgent referral, re-consultation and hospitalization rates of children aged 2 months and older to up to 5 years, within 7 days of the index visit. One hundred and two health surveillance assistants (HSAs) were stratified into six clusters based on geographical location, and clusters randomized to the timing of crossover to the intervention using simple, computer-generated randomization. Training workshops were conducted prior to the control (paper-CCM) and intervention (paper-CCM + SL eCCM App) in assigned clusters. Neither participants nor study personnel were blinded to allocation. Outcome measures were determined by abstraction of clinical data from patient records 2 weeks after recruitment. A nested qualitative study explored perceptions of adherence to urgent referral recommendations and a cost evaluation determined the financial and time-related costs to caregivers of subsequent health care utilization. The trial was conducted between July 2016 and February 2017. DISCUSSION: This is the first large-scale trial evaluating the value of adding a mobile application of CCM to the assessment of children aged under 5 years. The trial will generate evidence on the potential use of mobile health for CCM in Malawi, and more widely in other low- and middle-income countries. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT02763345 . Registered on 3 May 2016.

Merging clinical chemistry biomarker data with a COPD database - building a clinical infrastructure for proteomic studies.

BACKGROUND: Data from biological samples and medical evaluations plays an essential part in clinical decision making. This data is equally important in clinical studies and it is critical to have an infrastructure that ensures that its quality is preserved throughout its entire lifetime. We are running a 5-year longitudinal clinical study, KOL-Örestad, with the objective to identify new COPD (Chronic Obstructive Pulmonary Disease) biomarkers in blood. In the study, clinical data and blood samples are collected from both private and public health-care institutions and stored at our research center in databases and biobanks, respectively. The blood is analyzed by Mass Spectrometry and the results from this analysis then linked to the clinical data. METHOD: We built an infrastructure that allows us to efficiently collect and analyze the data. We chose to use REDCap as the EDC (Electronic Data Capture) tool for the study due to its short setup-time, ease of use, and flexibility. REDCap allows users to easily design data collection modules based on existing templates. In addition, it provides two functions that allow users to import batches of data; through a web API (Application Programming Interface) as well as by uploading CSV-files (Comma Separated Values). RESULTS: We created a software, DART (Data Rapid Translation), that translates our biomarker data into a format that fits REDCap's CSV-templates. In addition, DART is configurable to work with many other data formats as well. We use DART to import our clinical chemistry data to the REDCap database. CONCLUSION: We have shown that a powerful and internationally adopted EDC tool such as REDCap can be extended so that it can be used efficiently in proteomic studies. In our study, we accomplish this by using DART to translate our clinical chemistry data to a format that fits the templates of REDCap.