Keen to learn how to use existing insurance claim data bases in their countries to make policies that effectively improve their health systems, over 50 delegates packed the room during the in Bangkok.
Large amounts of data, especially insurance claims for health service utilization, are routinely collected by health systems in many low-and middle-income countries. They are a valuable source of real-time information on the state of the population¡¯s health, as well as a useful tool for policymakers. But, for a variety of reasons, these data are often not utilized to the full extent.
The PMAC workshop covered a wide range of topics including assessing length of stay for inpatient episodes, calculating hospitalization rates for ambulatory care sensitive conditions, assessing high-need high-cost utilization of services, analyzing incidence of C-section rates among deliveries, as well as examples of using healthcare claims data for assessing the impact of heatwaves on utilization of healthcare services. The goal of the training was to turn raw data into actionable information that strengthens universal health coverage. For example, use existing data to identify disease patterns, assess quality of care, support resource allocation, predict future expenditures and sustainability, and guide budget proposals and priorities.
An optional second day of training was also organized on January 24 at the World Bank¡¯s office in Bangkok to provide ¡°hands-on¡± introduction to coding and analysis using the STATA statistical software on a synthetic claims database. Participants of the PMAC side session came from various regions of the world and included health researchers, policymakers, and healthcare data analysts. ľ¹ÏÓ°Ôº and DFAT held a similar workshop in Da Nang, Vietnam in July 2023. The plan is to take the training to Indonesia and other countries in the East Asia and Pacific region in the near future.