INTRODUCTION:
Strengthening health systems in low- and middle-income countries requires accurate, timely data for evidence-based decision-making. Digitization of routine maternal, newborn, and child health (MNCH) data can improve collection, processing, interpretation, and use, yet county-level capacity within health information systems in Kenya is poorly documented. This study examines how routine MNCH data are digitized and used for timely healthcare decisions.

METHODS:
Qualitative key informant interviews were conducted between April and August 2025 with 23 stakeholders, including Health Records Information Officers, medical officers, pharmacists, and county health managers from Siaya and Kisumu counties. Interviews, conducted in person or virtually, explored MNCH data digitization, processing, interpretation, and use within county health information systems. They were transcribed verbatim, and analyzed thematically using an inductive approach guided by Braun and Clarke’s framework.

RESULTS:
Respondents reported strong capacity for MNCH data collection, digitization, and reporting, yet digital system implementation was uneven. Antenatal care and delivery systems were fully functional in Siaya but largely non-functional in Kisumu. Other service areas were partially digitized in both counties. Financial constraints, limited human resources, and reliance on hybrid paper–digital systems were major challenges. Routine data analysis enabled monitoring of service delivery trends and guided targeted interventions. Although data submission was generally timely, inconsistent use of data for decision-making revealed a persistent data-to-action gap. During the COVID-19 pandemic, respondents highlighted how routine data tracked temporary disruptions in service utilization, such as declines in antenatal care attendance and immunizations, and informed evidence-based responses to mitigate these disruptions.

CONCLUSIONS:
Counties in western Kenya have substantial human capacity for MNCH data digitization, but infrastructural and resource limitations restrict full system functionality and data use. Strengthening digital infrastructure, sustainable financing, and workforce capacity is critical to optimize MNCH data systems and support evidence-based decision-making.