326 Table 8. Estimated Economic Burden of AMR Infections, Australia 2014 Hospital Costs, AUD (95% UI) Organism
Ceftriaxone-resistant E. coli BSI Ceftriaxone-resistant KP BSI Ceftazidime-resistant PA BSI Ceftazidime-resistant PA RTI VRE BSI
MRSA BSI MRSA RTI
Antibiotic Cost, AUD (95% UI) $161,601 (133,011–193,316) $36,601 (22,839–53,577) $17,670 (11,237–25,382) N/A
$213,335 (136,355–307,969) $288,477 (249,335–330,954) N/A
Cost per Infectiona $9,200 (3,716–17,381) $9,248 (3,597–17,470) $792 (405–1,327) $562 (200–1,113)
$10,682 (3,500–23,223) $4,929 (297–19,933) $1,364 (649–2,458)
S. aureus; N/A. not available. aCalculated as the total costs divided by the number of resistant infections. The number of resistant infections can be found in Table 6.
Total Cost
$5,839,782 (2,288,318–11,176,790) $1,351,360 (358,717–3,158,370) $108,581 (48,551–202,756)
$1,296,324 (456,198–2,577,397) $1,404,064 (415,766–3,287,542) $5,546,854 (339,633–22,688,754) $1,525,552 (726,903–2,791,453)
Note. UI, uncertainty interval; BSI, bloodstream infection; RTI, respiratory tract infection; KP, K. pneumoniae; PA, P. aeruginosa; VRE, vancomycin-resistant E. faecium; MRSA, methicillin-resistant
Teresa M. Wozniak et al
To date,we have identified only ‘one’ estimate of the cost ofAMR
in Australia. Using international data and assuming comparable AMR rates and healthcare costs between the United States and Australia, the Expert Advisory Group on Antimicrobial Resistance have report an additionalAUD$250 millionper year.26Hence,within the context of such estimates, our measure of additional combined estimate AUD$16.8 million per year (for the five organisms ana- lyzed) may be a conservative underestimate. This underestimation may be attributable to a several key factors discussed below. First, our economic model includes hospital patients with bac-
teremia only, with the exception of respiratory P. aeruginosa and MRSAinfection where high-quality estimates ofAMR-attributable morbidity were reported. However, excluding highly prevalent infections (eg, UTIs27) based on lack of evidence would inevitably impact the overall costs of infection. Second, our estimates only include direct costs of infection and do not consider personal costs, the cost of premature death, nor any estimate of productivity loss.9,10 Last, we focused on five clinically important infections that consti- tute the majority of but not all, hospital-associated infections. We applied Monte Carlo simulation to propagate forward, to
the results, the effect of uncertainties in the model parameters. For each sample, a different set of random values from the prob- ability functions were selected. The advantage of using a Monte Carlo simulation method over a single-point estimate is that the results show not only what could happen but also how likely each outcome is at providing a result.28 Anumber of limitations should be considered when interpreting
the results of this study. First, we assumed that every infection had a specimen collected that grew the organism, and that each one of these had sensitivity testing performed. Second, we used Queensland-specific data and extrapolated these to the Australian population.Withan area of 1,727,000 square kilometers,Queensland is the second largest state in Australia. As a comparator to national rates of hospital-acquired infection, the Queensland rate of S. aureus cases (MRSA and MSSA) in 2014 was equivalent to the national rate of 0.07 cases per 1,000 days of patient care.29 At the time of requesting data for this study, Australia did not have a routine surveillance system for AMR; hence, we assessed Queensland-specific data that uses a single reliable testing method- ology and covered all public hospitals in an entire state, was the best data source. Third, treatment data were only available for BSIs and do not include other sites of infection or costs associated with staff time, equipment or any additional aspects of treating a
patient in hospital. However, auxiliary costs are often considered when estimating the average cost of a bed day and thus may in part be reflected in the overall cost estimate. We did not consider the loss of productivity or the societal perspective. Lastly, the under- lying model assumes that resistant infections replace susceptible infections; however, others suggest that resistance has an additive effect as well.30 If this is the case, our estimates of cost on the health- care system are likely to be larger than reported. We have provided an evidence-based, locally informed estimate
of the cost of AMR in Australian hospitals, which has also been developed into an online open-access tool.31 Together these esti- mates and tool aims impact the clinicalmanagement of patients with resistant infection, to inform current AMR strategy and implemen- tation plans,2 and to raise awareness of the significant knowledge gaps and the need for future investments in this important issue.
Author ORCIDs. Teresa Maria Wozniak, 0000-0003-3182-8348
Acknowledgments. Authorship and manuscript preparation. TW and NG conceptualised the economic model. TW wrote the first draft. TW, EB and NG reviewed the manuscript and provided feedback.
Financial support. The work was supported by the National Health and Medical Research Council-funded Centre for Research Excellence in Reducing Healthcare Associated Infections (grant no. GNT1030103). TW was supported by a Fellowship from the NHMRC-funded ‘Improving Health Outcomes in the Tropical North: A multidisciplinary collaboration (Hot North)’, grant identification number 1131932.
Conflicts of interest. All authors report no conflicts of interest relevant to this article.
References
1. Press release: High-level meeting on antimicrobial resistance. World Health Organization website.
http://www.un.org/pga/71/2016/09/21/press-release-hl- meeting-on-antimicrobial-resistance/. Published September 21, 2016. Accessed January 9, 2019.
2. Australian Department of Health. National Antimicrobial Resistance Strategy 2015–2019. Canberra: Australian Department of Health; 2015.
3. Wozniak TM, Paterson D, Halton K. Review of the epidemiological data regarding antimicrobial resistance in gram-negative bacteria in Australia. Infect Dis Health 2017;22:8.
4. Gandra S, Barter DM, Laxminarayan R. Economic burden of antibiotic resistance: how much do we really know? Clin Microbiol Infect 2014;20: 973–980.
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