Health economic analysis of organizational models for breast cancer surgery: a bottom-up micro-costing and cost-minimization approach

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Authors: Johan G Eriksson, Kaspar Walter Meili, Lena Lindholm, Micael Appelblad, Malin Sund
Cited by: 0
References: 31

Abstract

BACKGROUND: Healthcare systems face challenges in optimizing resources while maintaining high-quality care. Breast cancer surgery represents a substantial share of elective surgery and provides an opportunity to evaluate different organizational models. This study presents a health economic analysis comparing two models for breast cancer surgery at the same hospital. METHODS: A bottom-up micro-costing approach was employed to evaluate potential cost-savings of breast cancer surgeries performed at a general surgical department (GS) versus a cardiothoracic surgery department (CT). We analyzed 543 consecutive patients undergoing elective breast cancer surgery between January 2014 and September 2016. Resource use was identified through direct observation, hospital administrative systems, and operating room logs. Personnel, disposables, medications, and facility costs were quantified based on observed resource use within the study dataset; no external benchmarking was performed. RESULTS: CT was less expensive, with an average saving of 3,547 Swedish krona (SEK) per operation (95% CI: -674 to 7,510 SEK). Bootstrap analysis with 1,000 iterations showed CT was less costly in 96.2% of samples. Procedures were shorter at CT (170.8 vs. 221.3 min), enabling more operations per day (3.2 vs. 2.4). In our deterministic simulation, removing CT capacity increased waiting times by 15%, from 39 to 45.1 days, conditional on steady inflow and constant OR availability. Annual savings at the observed annual volume (~ 192 patients) were 681,104 SEK and could reach ~ 1.77 million SEK if volumes increased to 500 patients/year. CONCLUSIONS: The CT organizational model was more likely to be less costly while maintaining shorter waiting times. These findings suggest that CT capacity may be prioritized, particularly at higher patient volumes, to support both economic efficiency and patient access.

Fields of Study & Subjects

Health Systems Economic Evaluations Quality of Life Economic and Financial Impacts of Cancer Healthcare Operations and Scheduling Optimization

Publication details

Journal / source
Health Economics Review
Volume
16
Issue
1
Publication date
12 February 2026
Language
EN