Thanzi La Mawa (TLM) datasets: health worker time and motion, patient exit interview and follow-up, and health facility resources, perceptions and quality in Malawi

The Thanzi La Mawa (TLM) study aims to enhance understanding of healthcare delivery and resource allocation in Malawi by capturing real-world data across a range of health facilities. To inform the Thanzi La Onse (TLO) model, which is the first comprehensive health system model developed for any country, this study uses a cross-sectional, mixed-methods approach to collect data on healthcare worker productivity, patient experiences, facility resources, and care quality. The TLM dataset includes information from 29 health facilities sampled across Malawi, covering facility audits, patient exit interviews, follow-ups, time and motion studies, and healthcare worker interviews, conducted from January to May 2024. Through these data collection tools, the TLM study gathers insights into critical areas such as time allocation of health workers, healthcare resource availability, patient satisfaction, and overall service quality. This data is crucial for enhancing the TLO models capacity to answer complex policy questions related to health resource allocation in Malawi. The study also offers a structured framework that other countries in East, Central, and Southern Africa can adopt to improve their healthcare systems. By documenting methods and protocols, this paper provides valuable guidance for researchers and policymakers interested in healthcare system evaluation and improvement. Given the formal adoption of the TLO model in Malawi, the TLM dataset serves as a foundation for ongoing analyses into quality of care, healthcare workforce efficiency, and patient outcomes. This study seeks to support informed decision-making and future implementation of comprehensive healthcare system models in similar settings.