OBJECTIVES: To present a real-world micro-costing analysis of bariatric surgery in the Australian public healthcare system.

METHODS: In this retrospective cohort study, patients undergoing primary bariatric surgery (gastric banding [GB], gastric bypass [GBP] and sleeve gastrectomy [SG]) for the fiscal years 1^st-July-2013 to 30^th-June-19 were identified through the Tasmanian Department of Health’s administrative databases. Disaggregated, average-per-patient, and overall costs (2019 AU$) were presented. Subgroup analyses by surgical type were conducted. Annual population-based costs were calculated to capture longitudinal trends. A generalized linear model (GLM) was performed to predict the total costs for a base case scenario.

RESULTS: 240 patients were included. Mean direct costs were $11,269 (US$7,799). The operating theatre cost bucket constituted the largest component of bariatric surgery-related costs, followed by costs for medical supplies, salaries, CCU use, and labour on-costs. Average costs for SG ($12,632) and GBP ($15,041) were higher than those for GB ($10,049). Operating theatre-related costs accounted for the largest component for SG and GBP, whilst medical supplies were the largest for GB. We observed an increase in SG/GBP and a decrease in GB procedures over time. Correspondingly, the main cost driver changed from medical supplies in 2014-2015 for GB procedures to operating theatre after 2014-2015 for SG/GBP procedures. In addition to surgery type, CCU use, number of comorbidities and the presence of complications were also associated with bariatric expenditures. GLM modelling of these parameters showed that the average cost for a representative cohort ranged from $7,580 to $36,633.

CONCLUSIONS: This analysis presented the first detailed characterisation of the scale, disaggregated profile and determinants of costs of bariatric surgery and examined the evolution of resource utilization patterns and costs, reflecting the shift in Australian bariatric surgery landscape overtime. Understanding these patterns and forecasting of future changes are critical for healthcare resource allocation and sustainable budgetary planning.