Data Cannot Wait (DCW)

A mobile learning platform for antimicrobial resistance(AMR) that captures AMR surveillance data for geospatial analysis on smartphones and basic phones. 

Natalie Tegama

Antimicrobial resistance (AMR) is socioeconomic and global health threat. Globally, at least 700,000 people die each year from drug resistant infections including tuberculosis and HIV/AIDS. AMR occurs naturally, but this has been accelerated by the misuse and overuse of antibiotics in human and animal health. Representing a real challenge that could push the world into a ‘post-antibiotic era’ where common infections could kill again, potentially resulting in 10 million deaths per annum by the year 2050. Central to effectively tackling AMR are effective surveillance systems that provide alerts of the emergence of novel strains, allow rapid identification and control of outbreaks across human health and agriculture including animals. This is known as a One Health approach. Whilst low-and-middle income countries, where the infectious disease burden is higher have adopted One Health, surveillance systems remain relatively limited and fragmented. This is true of Kenya where DCW intends to deliver AMR education to health professionals’ mobile phones, smart or basic. This will impact AMR practice a key component to changing overuse and misuse. Additionally, health workers will be able to securely report cases of resistance using their phones, enabling the collection of health intelligence data to inform evidence-based interventions locally and nationally.

At local level, the target audience are health professionals; clinicians, lab personnel and pharmacists working across health facilities in Kenya (with the view to expand to other countries in the region). DCW seeks to identify  knowledge gaps and improve Antimicrobial stewardship (AMS) - ensuring the right antibiotic for the right patient is given at the right dose, for the right duration at the right time, and through the right route. This would positively impact AMR rates and minimise harm to patients. DCW has conducted contextual analysis research in resource constrained settings using participatory methods, this has enabled DCW develop an in-depth understanding of practitioners’ needs and interacting local practices and policies that impact AMS. DCW uses an iterative co-design method, known as Design Based Research that engages health workers in the development process through surveys, interviews and in piloting the app and platform in iterative cycles that afford changes based on user experience and learning analytics. Through geo-spatial analysis, DCW will be able to provide practitioners greater access to local AMR data and policy makers with mapping of AMR hot spots using clustering analysis.

DCW increases equity in data ecosystems and provides key data on AMR hotspots to policy makers for greater efficiency in resource allocation. DCW provides free to use dashboards of AMR data. DCW will contribute to wider body of literature on AMR learning and surveillance through peer-reviewed publication. 

The WHO AMR Competency framework for health workers' education and training on AMR, identifies a lack of understanding and inadequate expertise in human health as a major cause of the misuse of antibiotics. DCW makes  AMR related learning accessible from any mobile device for health workers. Increased understanding of antibiotic stewardship - giving patients the right dose, at the right time, for the right duration causes least harm to patients, present and future and contributes to communities of effectively tackling AMR. Enabling health workers to report AMR data from any mobile device creates more equitable data ecosystems that are inclusive of marginalised communities. DCW uses geo-spatial analysis to map potential AMR hotspots providing key data on marginalised communities to policy makers, empowering them to make data-driven decisions on resource allocation. 

Over the next year, we will pilot app/platform across 10 health facilities across 10 counties in Kenya. Our model uses a site in the county as a primary site, piloting at primary sites and using a train-the-trainer model by identifying potential leaders and training them to become AMR champions on site, championing stewardship and app/platform use. In year 2, we will add facilities from 20 more counties. In year 3 we will add the remaining 17 counties at the beginning of the year, giving us total coverage. We will then begin scoping expanding into Tanzania. 

For the educational component of the app/platform we use learning analytics to asses participants  knowledge. In addition we capture data on knowledge, confidence and attitude,  at baseline and postintervention and collect and analyse qualitative data.

We will measure the number of raw downloads, engagement with AMR dashboard, rate of course completion, frequency of engagement in learning, numbers of AMR cases identified, rates of AMR in counties, number of policy decisions linked to DCW data.

The Open University, UK

Kenya Medical Research Institute - Wellcome Trust

Lancaster University

Ministry of Health, Community Development, Gender, Elderly and Children Tanzania 

Trinity will help us to overcome financial barriers as we need investment in both the platforms. 

We would like to partner with organisations that specialise in technology and health, this would enable us to leverage their knowledge on software development and health data.