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Dr Katherine Kalaris

Dr Katherine Kalaris

Contact information

Email
katherine.kalaris@ndm.ox.ac.uk

Research groups

NDM Centre for Global Health Research

Colleges

Kellogg College

Katherine Kalaris

Postdoctoral Research Assistant

Katherine Kalaris completed her DPhil with the Health Systems Collaborative and is now a postdoc in the group. Her DPhil work explored how and why health system networks form, function, and perform to change practices to improve service delivery and quality of care in LMIC health systems, using Realist approaches. In her postdoc work, she continues to use a Realist approach to explore technology use in Kenyan newborn units and supports the HIGH-Q Exchange project and HSIE Masters. Katherine’s research interests include health system improvement, the relational aspects of health systems, and maternal and newborn health. She has been a consultant for the WHO and UNFPA and prior to her DPhil was based in West and Central Africa supporting Ministry of Health programmes in reproductive health, HIV, malaria, and supply chain for 10 years.

DPhil Project Overview

Recent publications

Understanding the initiation, formation, functioning, and performing of networks to change practices – Realist evaluation of a programme to improve newborn care in Kenya

Kalaris K. et al, (2025), SSM - Health Systems, 5, 100101 - 100101

Developing an understanding of networks in LMIC health systems: how and why networks change practices to improve service delivery and quality of care

Kalaris K., (2025)

Developing an understanding of networks with a focus on LMIC health systems: How and why clinical and programmatic networks form and function to be able to change practices: A realist review

Kalaris K. et al, (2023), SSM - Health Systems, 1, 100001 - 100001

Understanding how and why networks improve and provide high-quality healthcare and services in LMIC health systems: a realist review

Kalaris K. et al, (2023), Global Health Network Collections

Networks of care to strengthen primary healthcare in resource constrained settings.

Agyekum EO. et al, (2023), BMJ (Clinical research ed.), 380