Study title: Multimorbidity and Learning Health Systems: Optimising Data-to-Action

Principal Investigator(s)

Justin Dixon

Funder(s): Wellcome Trust

Partner(s): Ministry of Health and Child Care, Organisation for Public Health Interventions and Development (OPHID), London School of Hygiene and Tropical Medicine.

Background

OptiMuL (Multimorbidity and Learning Health Systems: Optimising Data-to-Action) builds on the KnowM study by co-developing and implementing a national multimorbidity learning hub in Zimbabwe. It aims to advance the WHO’s Learning Health Systems framework, emphasizing bottom-up perspectives and practical learning to create self-reliant, person-centered health systems that address complex health challenges like multimorbidity.

Study aim(s)

To strengthen capacity for domestic learning around multimorbidity in Zimbabwe

Study design

The study employs a phased approach, beginning with health system and care pathway mapping to identify gaps and opportunities for addressing multimorbidity. This is followed by a co-development phase, where stakeholders collaboratively design the multimorbidity learning hub and define its priority areas, such as policy and strategy, health information systems/electronic health records, training curricula, clinical guidelines, and integrated care models. Implementation includes embedded pilot studies in selected priority areas to refine solutions. A policy and professional fellowship program, inspired by initiatives like the Fleming Fund Fellowships and EMPOWA, will provide training and leadership opportunities for decision-makers and professionals to drive change projects. Evaluation incorporates a learning assessment framework, ethnographic research, and collective sense-making, ensuring iterative feedback and stakeholder engagement. The anticipated outcomes include increased collaboration across historically siloed disease programs, enhanced knowledge and approaches to multimorbidity, strengthened learning capacity and infrastructure, and innovative methods for collaborative evaluation, contributing to broader learning health system goals.

Study dates

2024 - 2030