Multimorbidity: a core priority for learning health systems amidst vertical disease programme cuts

Area of Science:

• Health Systems Research
• Public Health
• Health Informatics

Background:

• Global health systems face complex challenges, with multimorbidity being a significant cross-cutting issue.
• Recent funding shifts necessitate more integrated, adaptive, and self-reliant health systems.
• Multimorbidity requires a paradigm shift from vertical disease programs to integrated approaches.

Purpose of the Study:

• To propose Learning Health Systems (LHS) as a framework for addressing multimorbidity.
• To operationalize LHS principles with multimorbidity as a core priority.
• To illustrate the application of LHS through an interdisciplinary initiative in Zimbabwe.

Main Methods:

• An interdisciplinary initiative in Zimbabwe to establish a multimorbidity-learning health system.
• Focus on three sociotechnical infrastructure domains: reengineered electronic health records (EHR), deliberative platforms, and learning sites.
• EHR integration for research, data, and decision support; platforms for knowledge translation; learning sites for integrated care models.

Main Results:

• Demonstrated a model for integrating research, data, and decision support through reengineered EHR.
• Facilitated multi-condition sense-making and knowledge translation via deliberative platforms.
• Enabled practical development and iteration of integrated treatment and prevention models at service delivery levels.

Conclusions:

• LHS provide a viable framework for health systems to become more integrated, adaptive, and self-reliant in managing multimorbidity.
• The Zimbabwean initiative highlights key infrastructural domains and mechanisms applicable to lower-income countries.
• Developing in-house learning capabilities is crucial for addressing the needs of aging, multimorbid populations with reduced external funding.