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Accepted Paper:

Making multimorbidity (un)doable: a participatory ethnographic study in/of the Zimbabwean healthcare system  
Justin Dixon (LSHTM) Efison Dhodho (Organization for Public Health Interventions and Development) Clare Chandler (London School of Hygiene and Tropical Medicine) Fionah Mundoga (Organization for Public Health Interventions and Development (OPHID)) Karen Webb (OPHID) Rashida Ferrand Chiratidzo Ndhlovu (University of Zimbabwe Faculty of Medicine and Health Sciences)

Paper short abstract:

This paper explores the do-ability multimorbidity in Zimbabwe. We discuss how multimorbidity is made (un)knowable within single disease data infrastructures, struggles to make multimorbidity known, and the potential of a ‘learning health systems’ approach for collective sense-making and action.

Paper long abstract:

Multimorbidity, commonly defined of as the experience of two-or-more long-terms conditions by one person, has been framed as among the most pressing challenges facing health systems globally. How to make multimorbidity knowable (and thus ‘doable’) within particular health system contexts, however, presents a profound challenge given the evolution of national and transnational data infrastructures around single disease categories, particularly communicable diseases. With multimorbidity currently emerging on the radars of many low-resource health systems, how do differently positioned actors within such systems make multimorbidity knowable and doable through (or despite) existing knowledge infrastructures? This paper presents findings from a participatory ethnographic study in Zimbabwe that sought to characterise the challenge of multimorbidity from multiple perspectives across Zimbabwe’s health system, including policymakers, programme managers, researchers, medical educators, health informaticians, clinicians and patients. We advance three points: (1) within existing data infrastructures, multimorbidity becomes increasingly unknowable through the process of abstraction from clinical reality, to the detriment of patient care; (2) what is known and knowable about multimorbidity stems primarily from ‘vertical’ programme datasets, favouring expansion (rather than disruption) of vertical programming and research; (3) nonetheless, actors across the health system find ways of making multimorbidity knowable beyond current parameters, often through informal workarounds. We explore the concept of a ‘learning health system’, drawn from health policy and systems research (HPSR), as a possible conceptual lens for making multimorbidity actionable, collectively, in ways that continue to elude the knowledge hierarchies, flows, and binaries of verticalized, evidence-based global health.

Panel P185
What is to be done? Data infrastructures and doable problems in epidemiology, biomedicine, and beyond
  Session 1 Friday 19 July, 2024, -