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Cost-Effectiveness Analysis of Antibiotics in Pneumonia Patients with Diabetes Mellitus Type 2 Victoria, Brigita; Piter, Piter; Aviatin, Memy; Siahaan, Selma Arsit Selto; Maylinda, Tashya Dhela
The Indonesian Journal of Infectious Diseases Vol. 11 No. 2 (2025): The Indonesian Journal of Infectious Diseases
Publisher : Rumah Sakit Penyakit Infeksi Prof Dr. Sulianti Saroso

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32667/ijid.v11i2.553

Abstract

Background: Pneumonia poses a high clinical and economic burden, particularly in patients with type 2 diabetes mellitus (DM). Selecting the appropriate antibiotic is essential to ensure both clinical effectiveness and cost efficiency. This study aimed to evaluate the cost-effectiveness of fluoroquinolone monotherapy compared to beta-lactam–macrolide combination therapy in BPJS inpatients with pneumonia and comorbid type 2 DM at Prof. Dr. Sulianti Saroso Infectious Diseases Hospital (RSPI) during 2023–2024. Methods: This retrospective observational study used a cost-effectiveness analysis (CEA) approach, drawing on medical record data. Effectiveness was measured based on the Pneumonia Severity Index (PSI) and length of stay, while total direct medical costs were analyzed to calculate the Average Cost-Effectiveness Ratio (ACER).   Results: There was no significant difference in effectiveness or total direct medical costs between the two regimens. However, fluoroquinolone monotherapy had lower total costs (Rp10,090,591) and a smaller ACER value than the beta-lactam–macrolide combination (Rp13,386,045), suggesting that monotherapy was more cost-effective despite similar clinical outcomes. Conclusion: Although statistical differences were not significant, fluoroquinolone monotherapy appeared more cost-effective than beta-lactam–macrolide combination therapy for pneumonia patients with comorbid type 2 DM. These findings may support pharmacoeconomic-based decision-making in antibiotic selection. The study’s limitations include a small sample size, a single-center setting, and a retrospective design, which may affect generalizability.