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

<ns3:p>This paper provides an overview of the Thanzi La Mawa (TLM) survey, data collection methods and procedures, data modules and core variables, and quality assurance measures and expected analytical outputs from the TLM survey. The TLM survey is part of the Thanzi la Onse (TLO) model initiative. This is the first comprehensive health system model developed for any country, and aims to enhance understanding of healthcare delivery and resource allocation by capturing real-world data across the levels of healthcare delivery. The study seeks to support informed decision-making and future implementation of comprehensive healthcare system models in similar settings. The study uses a cross-sectional, mixed-methods approach to collect data on healthcare workers use of time, patient experiences, facility resources, and quality of care. The TLM dataset is based on a sample of 30 health facilities across Malawi comprising facility audits, patient interviews, and health worker use of time collected through time and motion studies. Data collection was conducted from January-May 2024. The analyses from this dataset provide insights into health workers’ time allocation to different activities, availability and use of healthcare resources at facilities, patient satisfaction, and overall service quality. This data is crucial for enhancing the TLO model’s capacity to answer complex policy questions related to health resource allocation in Malawi. The study also offers a structured framework that other countries, especially in East, Central, and Southern Africa that have expressed strong demand for the TLO model, can adopt as part of efforts to improve healthcare systems. By documenting methods and datasets, this paper provides guidance and tools 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.</ns3:p>