Timothy Tuti

Timothy Tuti is an informatics researcher with a focus on health systems research in LMICs. He holds a master’s degree in Social Research Methods and Statistics (University of Manchester, United Kingdom) and is currently pursuing doctoral studies in the area of Learning and New Technologies at the University of Oxford. Previously, he held a Wellcome Trust research fellowship with the Health Services Research Group (KEMRI-Wellcome Trust Research Programme), where his work looked into the potential role and acceptability of performance dashboards as part of clinical quality improvement and audit cycles, with consideration of how they might be designed to meet user needs in the organisational context of clinical practice in Kenyan district hospitals.

Currently, his research is exploring the potential for using VR using mobile platforms utilizing serious gaming strategies to provide initial and continuing training to health workers in Sub-Saharan Africa (SSA).

He has a number of publications exploring the role of health data science in decision support of frontline workers in LMICs; Implementation of digital strategies and platforms to support improvement of quality of health service delivery in routine hospital settings using clinical information networks.

PRESENTATION

Serious gaming in health: a theory-informed data-driven approach to learning

“The global need for more better-trained health workers is well established. Sub-Saharan Africa (SSA) produces over 24% of the global disease burden but only has 3% of the global health workforce. This severe workforce shortage, coupled with skill imbalance and maldistribution of health workforce, and lack of training opportunities are major contributors to the poor quality of maternal and child care outcomes in this region. Of the 2.9 million neonatal lives still being lost annually globally, SSA has the highest overall risk of death within the first 24hrs of life, having 38% of global neonatal deaths. Costs of face-to-face training in this region are prohibitively high and efforts are further constrained by the socio-economic, political and institutional landscape.

Solutions to address the demand for better, more accessible training are scarce, and models of context that might effectively support the development of digital learning platforms cognisant of the medical education needs and resources available to SSA do not yet exist, this presents a clear research gap in understanding how digital-based technologies for supporting medical training can be developed and implemented in a socially embedded manner.

This presentation aims to outline ongoing research exploring how gamified medical education content delivered through virtual reality and mobile training might be configured to support self-regulated learning behaviors in medical training of clinicians in SSA to deliver better neonatal care. This research is exploring how data-driven approaches supporting scaffolded learning in serious gaming on mobile environments might be designed to support adaptive learning at scale in SSA.”