BackgroundEffective drug procurement guarantees the sustainable supply of products for health and eliminates excessive costs. However, there is limited information on the area of pharmaceutical procurement practice in Ethiopia. Thus, this study aimed at assessing the procurement practices of program drugs and its challenges at the Ethiopian Pharmaceuticals Supply Agency.MethodsA cross-sectional study accompanied by qualitative assessment was conducted between February 21 and April 20/2020 to examine the procurement practice of the Ethiopian pharmaceutical supply agency. The quantitative data were gathered by reviewing documents and electronic records. Mean forecast error, price paid to international price reference, number of emergency orders placed, and lead time variability were the measurements used to assess the procurement practice. A statistical package for the social sciences version 23 was used to analyze the data. The results were then summarized using tables and texts. The qualitative data were collated through face-to-face in-depth interviews to explore the challenges behind the procurement practice. And the data were analyzed manually using the thematic analysis technique.ResultsThe agency had its own procurement list which defines the items to be procured. The overall mean forecast error in the 2018/19 budget year was 27.8%. Of the 70 program commodities included in the study, 52 (74.3%) items had a mean price less than the international price reference. Three of the 14 orders (21.4%) placed in the aforementioned year were emergency purchases made through direct procurement. The mean lead time for the suppliers of the agency was 137.3 days. Poor data quality from service delivery points, staff capacity constraints, communication problems, and policy issues became the major challenges to implement an effective procurement system in the agency.ConclusionThe procurement practice at the agency has strong side. However, it was not without weaknesses. Using a procurement list is a worthwhile practice. Despite this, much remains to improve lead times and forecasting accuracy.