Mulimorbidity and Learning Health Systems: Optimizing Data-to-Action (KnowM and OptiMul Studies)

Multimorbidity, or having = ≥2 long-term conditions in one person is viewed as the next ‘global pandemic’.
37.2% adults globally and 28% in Africa are living with multimorbidities. By 2035 it is estimated that 59% of people living with HIV in Zimbabwe will have 1 or more non-communicable disease.
This emerging public health threat is complicated further in countries like Zimbabwe with syndemic chronic infectious (HIV & tuberculosis) and non-communicable disease (mental health, alcohol and substance use disorders, hypertension and diabetes) crises.
Multimorbidity challenges the way that resource constrained health systems are built around a single disease model. Calls for person-centred care, but need for multidisciplinary evidence to guide sustainable, context-sensitive responses.

In collaboration with the London School of Hygiene and Tropical Medicine (Principal Investigator Dr Justin Dixon), the University of Zimbabwe and The Health Research Unit Zimbabwe and the University of Zimbabwe, OPHID implemented the KnowM study from 2023-2024. The study sought to formatively assess the challenge of MM for Zimbabwe’s health system.

Want to learn more?  See our publications and presentations

KEY FINDINGS of KnowM:

  • Free, decentralized HIV & TB care contrasts with centralized, expensive care for non-communicable diseases
  • Fragmented care is especially detrimental for clients with multimorbidity
  • Challenges in health service delivery reflect wider system ‘siloes’.

The KnowM study identified enablers and opportunities to strengthen the provision whole person care in Zimbabwe.

“You get tired joining different queues and its time consuming…They should combine especially for those with multiple conditions”
— KnowM participant

In 2024-2030, with further support from Wellcome Trust, KnowM partners will embark on a Phase II study: Multimorbidity and Learning Health Systems: Optimising Data-to-Action (OptiMuL).

OptiMuL will bring together researchers, decision-makers, and stakeholders to form a multimorbidity learning hub. The aim will be to support bi-directional learning for integrated care models.  

The models co-created through OptiMuL will need to be tested in “real world” implementation contexts to determine if they are acceptable to both health care workers and patients, and improve the quality of care received by clients living with multimorbidities with potential to scale.

Want to get involved?

Interested in partnering with OPHID to support incubator projects to test evidence-based models to improve the quality of care for people living with multimorbdities? Visit our get involved section to learn more.
Get Involved