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      Quantifying the Economic and Clinical Value of Reducing Antimicrobial Resistance in Gram-negative Pathogens Causing Hospital-Acquired Infections in Australia

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          Abstract

          Introduction

          Antimicrobial resistance (AMR) is a global public health challenge requiring a global response to which Australia has issued a National Antimicrobial Resistance Strategy. The necessity for continued-development of new effective antimicrobials is required to tackle this immediate health threat is clear, but current market conditions may undervalue antimicrobials. We aimed to estimate the health-economic benefits of reducing AMR levels for drug-resistant gram-negative pathogens in Australia, to inform health policy decision-making.

          Methods

          A published and validated-dynamic health economic model was adapted to the Australian setting. Over a 10-year time horizon, the model estimates the clinical and economic outcomes associated with reducing current AMR levels, by up to 95%, of three gram-negative pathogens in three hospital-acquired infections, from the perspective of healthcare payers. A willingness-to-pay threshold of AUD$15,000—$45,000 per quality-adjusted life-year (QALY) gained and a 5% discount rate (for costs and benefits) were applied.

          Results

          Over ten years, reducing AMR for gram-negative pathogens in Australia is associated with up to 10,251 life-years and 8924 QALYs gained, 9041 bed-days saved and 6644 defined-daily doses of antibiotics avoided. The resulting savings are estimated to be $10.5 million in hospitalisation costs, and the monetary benefit at up to $412.1 million.

          Discussion

          Our results demonstrate the clinical and economic value of reducing AMR impact in Australia. Of note, since our analysis only considered a limited number of pathogens in the hospital setting only and for a limited number of infection types, the benefits of counteracting AMR are likely to extend well beyond the ones demonstrated here.

          Conclusion

          These estimates demonstrate the consequences of failure to combat AMR in the Australian context. The benefits in mortality and health system costs justify consideration of innovative reimbursement schemes to encourage the development and commercialisation of new effective antimicrobials.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s40121-023-00835-9.

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          Most cited references30

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          Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

          (2022)
          Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
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            The antibiotic resistance crisis: part 1: causes and threats.

            Decades after the first patients were treated with antibiotics, bacterial infections have again become a threat because of the rapid emergence of resistant bacteria-a crisis attributed to abuse of these medications and a lack of new drug development.
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              Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock*

              Critical Care Medicine, 34(6), 1589-1596
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                Author and article information

                Contributors
                David.Grolman@pfizer.com
                Journal
                Infect Dis Ther
                Infect Dis Ther
                Infectious Diseases and Therapy
                Springer Healthcare (Cheshire )
                2193-8229
                2193-6382
                21 June 2023
                21 June 2023
                July 2023
                : 12
                : 7
                : 1875-1889
                Affiliations
                [1 ]GRID grid.512413.0, Health Economics and Outcomes Research Ltd., ; Cardiff, UK
                [2 ]GRID grid.418566.8, ISNI 0000 0000 9348 0090, Pfizer Ltd, ; Tadworth, UK
                [3 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, Centre for Superbug Solutions, Institute for Molecular Bioscience, , The University of Queensland, ; St Lucia, QLD 4072 Australia
                [4 ]GRID grid.476921.f, Centre for Infectious Diseases and Microbiology, , Westmead Institute, WestmeadHospital/University of Sydney, ; Sydney, NSW 2145 Australia
                [5 ]GRID grid.1010.0, ISNI 0000 0004 1936 7304, Adelaide Medical School and School of Biological Sciences, , University of Adelaide, ; Adelaide, SA Australia
                [6 ]European Committee on Antimicrobial Susceptibility Testing (EUCAST), Basel, Switzerland
                [7 ]GRID grid.467667.2, ISNI 0000 0001 2019 1105, Australian Commission on Safety and Quality in Health Care, ; Sydney, Australia
                [8 ]GRID grid.1025.6, ISNI 0000 0004 0436 6763, Antimicrobial Resistance and Infectious Diseases (AMRID) Research Laboratory, , Murdoch University, ; Perth, WA Australia
                [9 ]GRID grid.467540.4, ISNI 0000 0004 0618 9828, Hospital Medical Affairs, Pfizer Australia, ; Level 15-18/151 Clarence Street, Sydney, 2021 Australia
                [10 ]GRID grid.467540.4, ISNI 0000 0004 0618 9828, Health Economics and Outcomes Research, Pfizer Australia, ; Sydney, 2021 Australia
                Article
                835
                10.1007/s40121-023-00835-9
                10390426
                37341866
                971d86a0-b18b-4ad1-a9b6-a57023d96297
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 14 March 2023
                : 7 June 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000948, Pfizer Australia;
                Categories
                Original Research
                Custom metadata
                © Springer Healthcare Ltd., part of Springer Nature 2023

                antimicrobial resistance,hospital-acquired infections,gram-negative,economic evaluation,decision making

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