Abstract

BackgroundOur aim was to examine whether the length of stay, hospital charges and in-hospital mortality attributable to healthcare- and community-associated infections due to antimicrobial-resistant bacteria were higher compared with those due to susceptible bacteria in the Lebanese healthcare settings using different methodology of analysis from the payer perspective .MethodsWe performed a multi-centre prospective cohort study in ten hospitals across Lebanon. The sample size consisted of 1289 patients with documented healthcare-associated infection (HAI) or community-associated infection (CAI). We conducted three separate analysis to adjust for confounders and time-dependent bias: (1) Post-HAIs in which we included the excess LOS and hospital charges incurred after infection and (2) Matched cohort, in which we matched the patients based on propensity score estimates (3) The conventional method, in which we considered the entire hospital stay and allocated charges attributable to CAI. The linear regression models accounted for multiple confounders.ResultsHAIs and CAIs with resistant versus susceptible bacteria were associated with a significant excess length of hospital stay (2.69 days [95% CI,1.5–3.9]; p < 0.001) and (2.2 days [95% CI,1.2–3.3]; p < 0.001) and resulted in additional hospital charges ($1807 [95% CI, 1046–2569]; p < 0.001) and ($889 [95% CI, 378–1400]; p = 0.001) respectively. Compared with the post-HAIs analysis, the matched cohort method showed a reduction by 26 and 13% in hospital charges and LOS estimates respectively. Infections with resistant bacteria did not decrease the time to in-hospital mortality, for both healthcare- or community-associated infections. Resistant cases in the post-HAIs analysis showed a significantly higher risk of in-hospital mortality (odds ratio, 0.517 [95% CI, 0.327–0.820]; p = 0.05).ConclusionThis is the first nationwide study that quantifies the healthcare costs of antimicrobial resistance in Lebanon. For cases with HAIs, matched cohort analysis showed more conservative estimates compared with post-HAIs method. The differences in estimates highlight the need for a unified methodology to estimate the burden of antimicrobial resistance in order to accurately advise health policy makers and prioritize resources expenditure.

Highlights

  • Our aim was to examine whether the length of stay, hospital charges and in-hospital mortality attributable to healthcare- and community-associated infections due to antimicrobial-resistant bacteria were higher compared with those due to susceptible bacteria in the Lebanese healthcare settings using different methodology of analysis from the payer perspective

  • We aimed to quantify the excess healthcare costs, length of stay, and in-hospital mortality associated with antimicrobial-susceptible versus -resistant infections from the payer perspective using a conventional method for studying the costs of community-associatedinfections (CAIs) and two different methodologies of analysis previously adapted in the literature [53, 54] for estimating the costs of healthcare-associated- infections (HAIs) and compare attributable results

  • We assumed that infections due to resistant- compared with –susceptible bacteria were the independent exposure of interest, and we evaluated their impact on excess length of stay (LOS), excess hospital charges, and in-hospital mortality

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Summary

Introduction

Our aim was to examine whether the length of stay, hospital charges and in-hospital mortality attributable to healthcare- and community-associated infections due to antimicrobial-resistant bacteria were higher compared with those due to susceptible bacteria in the Lebanese healthcare settings using different methodology of analysis from the payer perspective. Accurate estimates of the economic burden of antimicrobial resistance (AMR) provide a baseline tool to study the cost-effectiveness of interventions to mitigate this global crisis and gives policymakers the incentives needed to invest in research and funding programs that track and prevent the spread of resistance [10,11,12,13,14,15,16,17,18,19]. In a country struggling for cost containment, the estimates of the economic and healthcare burden of AMR needed from multiple perspectives

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