Accepted Manuscript

Is Antimicrobial Stewardship Cost-Effective? A Narrative Review of the Evidence

Nichola R. Naylor, Nina Zhu, Marlies Hulscher, Alison Holmes, Raheelah Ahmad,Julie V. Robotham

PII: S1198-743X(17)30330-0

DOI: 10.1016/j.cmi.2017.06.011

Reference: CMI 978

To appear in: Clinical Microbiology and Infection

Received Date: 31 March 2017

Revised Date: 10 June 2017

Accepted Date: 11 June 2017

Please cite this article as: Naylor NR, Zhu N, Hulscher M, Holmes A, Ahmad R, Robotham JV, IsAntimicrobial Stewardship Cost-Effective? A Narrative Review of the Evidence, Clinical Microbiology andInfection (2017), doi: 10.1016/j.cmi.2017.06.011.

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Is Antimicrobial Stewardship Cost-Effective? A Narrative Review of the Evidence

Nichola R Naylor1*, Nina Zhu1, Marlies Hulscher2, Alison Holmes1, Raheelah Ahmad1, Julie V Robotham3,1

1. National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infection and

Antimicrobial Resistance at Imperial College London, United Kingdom.

2. Radboud university medical center, Radboud Institute for Health Sciences, IQ healthcare, Nijmegen, The

Netherlands

3. Modelling and Economics Unit, Public Health England, United Kingdom.

* Corresponding author: N. Naylor, email; n.naylor@imperial.ac.uk, phone; +4420 3313 2732, address; The NIHR

Health Protection Research Unit In Healthcare Associated Infections and Antimicrobial Resistance, 8th Floor,

Commonwealth Building, Imperial College London, Hammersmith Campus, W12 0NN

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Abstract

Aims: This narrative review aimed to collate recent evidence on the cost-effectiveness and

cost-benefit of antimicrobial stewardship (AMS) programmes, to address the question “is AMS

cost-effective?”, whilst providing resources and guidance for future research in this area.

Sources: PubMed was searched for studies assessing the cost-effectiveness, cost-utility or

cost-benefit of AMS interventions in humans, published from January 2000 to March 2017, with

no setting inclusion/exclusion criteria specified. Reference lists of retrieved reviews were

searched for additional articles.

Content: Recent evidence on the cost-effectiveness and cost-benefit of AMS is described, studies

suggest persuasive and structural AMS interventions may provide health economic benefits to

the hospital setting. However overall, cost-effectiveness evidence for AMS is severely limited,

especially for the community setting. Recommendations for future research in this area are

therefore provided, including discussion of appropriate health economic methodological choice.

Implications: Health systems have a finite and decreasing resource, decision makers currently do

not have necessary evidence to assess whether AMS programmes provide sufficient benefits.

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While the evidence-base of the cost-effectiveness of AMS is increasing, it remains inadequate for

investment decision-making. Robust health economics research needs to be completed to

enhance the generalisability and usability of cost-effectiveness results.

Introduction

Antimicrobial resistance (AMR) has been estimated to cause great current and potential harm to

population health and the global economy [1,2]. Many programmes designed to tackle AMR aim

to decrease selection pressure, based on the premise that the consumption of antimicrobials and

level of resistance are associated [3], these include antimicrobial stewardship (AMS)

programmes. AMS programmes use a coherent set of interventions that promote the responsible

use of antimicrobials to decrease the development and spread of resistant organisms, thus

reducing infections and improving patient outcomes [3,4].

The categorization of AMS interventions for this review used AMS ‘type’ definitions taken from

a recent Cochrane Review [5], see Table 1. [Table 1 near here]

Most health economic evaluations aim to provide outcomes by which decision-makers can

attempt to maximize population health gain given a limited financial resource. Generally, all

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such evaluations compare the costs and benefits associated with a new intervention to those of

standard/current practice, providing an estimate of cost per benefit gained associated with

implementing the new policy. Dependent on the outcome measure desired, a cost-effectiveness,

cost-utility or cost-benefit analysis may be performed (see Table 2). In cost-effectiveness

analyses benefits are expressed as some form of ‘natural unit’ (e.g. deaths averted, infections

prevented or life years gained). By comparing costs and benefits of alternative interventions an

incremental cost-effectiveness ratio can be determined e.g. cost per life year gained. A

cost-utility analysis, regarded as a subset of cost-effectiveness analysis, expresses benefits in

‘natural units’ that are quality adjusted. Quality adjusted life years (QALYs) are a health status

measure which incorporate ‘quality’ and length of life, ranging from zero to one (one

representing a year in full health and zero representing death). The outcome of such an

evaluations is a cost per QALY gained (which can still be referred to as an incremental

cost-effectiveness ratio). The use of QALYs enables the incorporation of both morbidity and

mortality, making it possible to compare health-related interventions with very different effects,

across disease areas. In a cost-utility model a QALY value is attached to a specific health state

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(e.g. a urinary tract infection may be associated with a 0.02 QALY detriment compared to

‘normal’ health [6]), therefore the total number of QALYs gained from a particular intervention

is dependent on how it affects the patient flow between such health states.

It is still the responsibility of the acting decision-maker to determine whether the cost-utility ratio

is acceptable, i.e. whether this intervention is worth investing in given the cost per QALY gained.

In the UK the acting health technology appraisal body (NICE) uses £20,000 - £30,000 per QALY

gained as their willingness to pay threshold, meaning an intervention should theoretically be

accepted if under this threshold [7]. However academic debates surrounding the choice and use

of this threshold are ongoing [8]. Finally, if all outcomes (costs and benefits) can be measured in

monetary terms a cost-benefit analysis may be employed, providing a cost-benefit ratio and

allowing for comparison against non-health related interventions such as education or

environmental policies. However, theoretical and ethical issues regarding the feasibility of

directly monetising the value of life and health should be noted [9].

Both the cost and benefit outcomes described in Table 2 can be estimated from the payer

perspective (for example from costs to the National Health Service in England or Medicare in the

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United States) or the societal perspective (including productivity losses). [Table 2 near here]

Empirical consensus on the cost-effectiveness or cost-benefit of different AMS programmes has

unfortunately not yet been reached, though previous reviews have summarised the available

evidence on the financial impact and/or effectiveness of interventions [5,10–12] . The two

reviews focusing on economic evaluations of AMS programmes found, between them, more

costing studies comparative to cost-effectiveness (with less than four cost-effectiveness studies in

each) [10,11]. These reviews indicate that AMS programmes could be cost-effective, though both

calling for more evidence [10,11]. Given the increased policy focus on AMR and AMS in recent

years, with a number of new tools and initiatives [13], an up-to-date review is needed, focusing

on evaluations incorporating both costs and effects concurrently. To establish whether AMS

programmes are cost-effective, and thus provide an economic argument for implementation, this

review aimed to collate and discuss the recent health economic evidence. A secondary aim was to

provide resources and guidance for cost-effectiveness evaluations of AMS, to promote robust

future research.

Methods

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PubMed was searched for literature published from Jan 2000 to March 2017, with the three main

types of health economic evaluations used as search terms [14]; ((cost-effectiveness) OR

(cost-benefit) OR (cost-utility) OR (cost effectiveness) OR (cost benefit) OR (cost utility)) AND

((antimicrobial stewardship) OR (antibiotic stewardship)), limited to “human”. Title/abstracts

and full texts of retrievals were reviewed (See Supplementary Material Table I for

inclusion/exclusion criteria). Reference lists of retrieved reviews were searched for additional

articles.

Current Evidence on the Cost-Effectiveness of AMS Programmes

55 articles were found, resulting in six studies being included in this review [15–20]. Four

studies calculated the cost-effectiveness or cost-utility of AMS programmes [15–18] (both

cost-effectiveness and cost-utility studies from now on referred to as ‘cost-effectiveness’ studies),

whilst two additional studies calculated cost-benefit [19,20].

Table 3 highlights the lack of evidence on the health economic benefit of restrictive AMS

programmes, with all evidence found investigating persuasive or structural programmes (as

defined in Table 1). Two studies within the “structural” category evaluated the cost-effectiveness

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of rapid diagnostics, whilst the other investigated the implementation of an AMS team [16–18].

The remainder of studies included in this review evaluated multiple AMS programmes together,

making it hard to disentangle what is driving the cost-effectiveness/cost-benefit of these bundled

interventions [15,19,20]. There was no evidence found evaluating AMS in the community or

long-term care setting, with all studies evaluating AMS in hospitals. Additionally, despite AMR

being a global issue that could severely impact low- and middle-income countries [1], only one

study explored the cost-effectiveness/cost-benefit of AMS outside the ‘western’ world [15].

Four of the six studies found estimated the cost-effectiveness of different AMS programmes,

with estimates ranging from $415 savings per patient to $19,287.54 per averted death in 30-days,

across the different intervention types being evaluated (Table 3). This limited evidence may

suggest that persuasive and structural AMS programmes in hospitals could potentially provide

“value for money” in comparison to “standard care”. However, the heterogeneity in study design

and included costs/effects (Table 3) makes it hard to summarise across measures. These studies

also had limitations. One study investigating antifungal stewardship did not state clearly how the

estimate of $415 net saving per patient was derived, but did state that only drug costs and

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diagnostic costs were taken into account, meaning this may not be a true cost-effectiveness study

(as stated by authors) but rather a cost-comparison [18] (which compares only costs and has no

evaluation of benefits (as defined in Table 2)). Only one of the cost-effectiveness studies

included utility in their effectiveness measure (estimating cost per QALY) [16], whilst two others

included mortality as their effectiveness measure [15,17].

The two cost-benefit studies estimated policies including AMS programmes to be cost-saving,

with estimates of cost-savings of €2,575 per month for hospitals and $2.5 billion for Medicare

[19,20]. However, the former study did not seem to account for all benefits in a monetary terms

and did not provide a cost-benefit ratio [20]. This study instead compared direct healthcare costs

(of antibiotics, cultures and the intervention) and discussed health gain in parallel [20]. The

cost-benefit evaluation of Clostridium difficile infection control measures did create a model

which incorporated labour costs, illness costs and excess length of stay in its cost estimation,

though did not evaluate AMS alone [19].

None of the studies found employed time-horizons longer than 5 years and no evidence was

found describing the potential health economic benefit of AMS programmes from the societal

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perspective, which could be important in comparing AMS to other infection prevention control

studies for national rollout.

In conclusion, there is insufficient evidence to empirically state whether AMS is cost-effective,

with more research needed following the below recommendations. [Table 3 near here]

Future AMS Cost-Effectiveness Research

Figure 1 outlines some of the basic concepts that should be considered when estimating the

cost-effectiveness of AMS. Recent literature has offered more specific guidance on the potential

clinical outcomes and process indicators for AMS policy evaluation in terms of costs and effects,

highlighting the need to include more than just the difference in antimicrobial consumption

across interventions and to choose such parameters based on specific AMS programme type

[10,21–24]. To provide health economic outcomes, enabling AMS to be rationally compared

against other potential resource use across the health sector, a cost-utility study can be performed,

whereby the costs of the intervention (including implementation and any cost-savings resulting

from its effects) are weighed against health benefits in terms of QALYs gained. The cost per

QALY gained associated with intervention options can then be compared against a

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predetermined threshold of ‘willingness to pay’ for health benefits. A recent report details good

research practices for such parameter estimation in clinical studies [25]. Costs considered should

be real-world associated unit costs (for example an estimated cost per bed day or per prescription)

that are discounted at 3.5% annually [7,26]. Health effects should also be discounted, with

recommendations that the same discount rate as that applied to costs [7]. If it is intended for

these cost and health outcomes to be evaluated alongside a trial, trial design is also highly

important, with cluster-randomised control trials or controlled interrupted time series analyses

being recommended for AMS intervention evaluation within another review [24]. Valid cost and

effect data are also needed for the comparator (for example establishing current costs and effects

of standard care), since any incremental cost-effectiveness ratio reported is in relation to the

chosen comparator.

Alongside the base model, sensitivity analysis should be performed to incorporate uncertainty in

model parameters [26]. It has also been recommended that health economic evaluations of AMR

interventions incorporate disease transmission by utilising a dynamic rather than a static model

structure to allow the wider ‘knock-on’ costs and health benefits associated with infectious

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diseases to be taken into account [27], however these models require information on

transmissibility and persistence in regards to pre- and post-intervention [27].

Using cost-effectiveness/cost-utility models to ration healthcare resources assumes the preferred

policy is one that maximises the health of the overall population. Whilst accepted by many

policy makers, this assumptions has been questioned in terms of ethics and equity in academic

work [28]. Whether you should even perform a cost-utility analysis is also dependent on your

objectives relating to a reduction in antibiotic usage. If the goal is to preserve the ability of

antibiotics to treat a patient, therefore improving health outcomes [5,10], then measuring impact

in QALYs is theoretically feasible [16]. Measuring any health improvement over someone’s

lifetime, including any years gained from reduced mortality events or quality gained from

reduced time spent in related health conditions, enables measurement of the impact of AMS

interventions over the lifetime horizon. However, this poses two main challenges: firstly in the

estimation of the long-term effects of responsible use of antibiotics on resistance (which is

currently largely unknown) and secondly in identifying and quantifying the short and long-term

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health and cost consequences that different levels of resistance will have on individuals and the

population, though recent work has attempted to estimate the potential impact of resistance on

such outcomes [2,29–31]. Most studies estimating the cost of resistance also tend to ignore

potential costs of inaction i.e. costs in a scenario where antibiotics are no longer viable, and

therefore potentially severely underestimate the problem [31].

Indeed, though it is recommended that future research be conducted from the payer perspective

in the base-case scenario, additional scenarios which incorporate societal perspectives (through

capturing productivity impact of interventions) and ‘cost of inaction’ would give additional

insight into the societal benefit of AMS. [Figure 1 inserted near here]

Conclusion

This review discusses the most recent evidence on the health economic benefit of AMS

programmes. Estimates of the cost-effectiveness of persuasive or structural AMS programmes,

from the limited studies available, would indicate cost-effectiveness according to the threshold

used by UK Heath Technology Appraisal bodies, in comparison to “standard care” [7]. However,

these were mainly evaluating rapid diagnostics or a bundle of interventions, with only one

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performing a cost-utility analysis, and so any conclusions drawn should be treated with caution.

This review clearly reiterates previous calls for more research into the cost-effectiveness of AMS

[11,32], but also provides resources and guidance for future research.

A previous review on the cost and clinical outcomes of AMS, by Coulter et al. suggested that

research is lacking due to the complexity of such evaluations (due to variability in AMS policy

type and heterogeneity in cost/resource inclusion decisions) [11]. However this information is

still needed to make informed resource allocation decisions, and therefore hopefully the

recommendations provided in this review can aid such future research.

This narrative review is structured in nature, and thus has limitations in comparison to a

systematic review, for example, individual rapid diagnostics or named programmes may not be

picked up due to the utilised search string, only one scientific database (with references) was

searched and quality was not formally assessed. However, this study enables discussion of the

recent published evidence, whilst also offering clear recommendations for future research in this

field.

This review particularly highlights the need for research on the impact of AMS interventions in

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the community, where the majority of antibiotic prescriptions occur [4]. We also call for a more

systematic approach to evaluating the cost-effectiveness of individual AMS programmes. Robust

health economic evaluations provide a rational basis for decision-making and facilitate the

optimal allocation of scarce resources in the fight against AMR, and are clearly much needed in

the area of AMS.

Transparency declaration

The authors have nothing to disclose.

Funding

The research was funded by the National Institute for Health Research Health Protection

Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance

at Imperial College London in partnership with Public Health England (PHE). .RA is supported

by a NIHR Fellowship in knowledge mobilisation. The views expressed are those of the author(s)

and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health

England. More information on HPRU and current projects can be found on

https://www1.imperial.ac.uk/hpruantimicrobialresistance/.

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Acknowledgements

The authors would like to acknowledge Prof Céline Pulcini for guidance in the direction of this

review.

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Table 1: Antimicrobial Stewardship Intervention Types, by Cochrane Review Groupings

Types as defined in Davey et al (2017) [5].

Type Examples

Persuasive Educational programmes, reminders, audit and feedback.

Restrictive Formulary restrictions, authorization requirements and antibiotic cycling.

Structural Computerization of records, rapid diagnostics and decision support systems.

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Table 2: Summary of Health Economic Evaluation Types

Type Description Common Outcomes

Cost-Effectiveness

Analysis

All (monetary) costs for interventions

are calculated, all benefits are

calculated in non-monetary (health)

benefit. A comparison of the

associated costs and benefits is then

made.

The incremental cost-effectiveness ratio (ICER)

refers to the cost per benefit gained, e.g. cost per life

year gained or cost per case averted. It is calculated

utilising the following logic; (cost of AMS – cost of

comparator) divided by (benefit of AMS – benefit of

comparator. The decision rule is that the

intervention should be accepted if the ICER is

below a certain threshold, e.g. $10,000 per life year

gained from AMS.

Cost-Utility

Analysis

All (monetary) costs for interventions

are calculated, all benefits are

calculated in terms of health utility

benefit (measuring quality and

quantity of life). A comparison of the

associated costs and benefits is then

made. A cost-utility analysis is a type

of cost-effectiveness analysis, and is

often referred to in the literature as

such.

The incremental cost-utility ratio (a type of ICER)

refers to the cost per quality adjusted life year

(QALY) gained, cost per healthy-adjusted life year

gained or cost per disability adjusted life year

(DALY) averted. E.g. $10,000 per QALY gained

means that to gain one more year of full health from

the AMS intervention requires $10,000 more

investment relative to your comparator (e.g. no

intervention). The decision rule is that the

intervention should be accepted if the ratio is below

a certain threshold.

Cost-Benefit

Analysis

All costs and benefits for

interventions are calculated in

monetary terms and compared.

The incremental benefit-cost ratio refers to the

monetary gain/return per relevant monetary

currency unit spent. E.g. $10,000 returned per $1

invested means you will receive $10,000 worth of

benefit per dollar spent. The decision rule is that the

intervention should be accepted if the ratio is

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Type Description Common Outcomes

positive, i.e. there is a net positive benefit associated

with the intervention.

Abbreviations: DALY- disability adjusted life year, ICER – incremental cost-effectiveness ration, QALY – quality

adjusted life year.

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Table 3: Summary of Studies Estimating the Cost-Effectiveness, Cost-Utility and Cost-Benefit of Antimicrobial Stewardship

Programmes

Study

Analysis

Method

Specific interventions & comparators Type of

intervention

Country Setting

(Year)

Results

Cost-Effectiveness & Cost-Utility Analyses

[15]

Markov

model (and

probabilistic

sensitivity

analysis)

Bundled stewardship (prospective auditing,

feedback, education, microbiological data

discussion with laboratory staff), compared to

conventional stewardship (pharmacist

screening for problems, discussions and

telephone interventions)

Persuasive Brazil Hospital

(2013)

Cost per averted death in 30 days was estimated at US$ 19,287.54 for the

bundled intervention (2013 USD). The absolute risk of mortality was 0.6209

and 0.7308 for the conventional and bundled programmes respectively. Direct

costs were estimated at $18,013.22 and $20,132.92 respectively. Probabilistic

sensitivity analysis suggested that this result was robust.

[16] Decision tree

modelling

(and

probabilistic

sensitivity

analysis)

Antimicrobial stewardship teams in treating

bloodstream infections, compared to standard

care (with no antimicrobial stewardship

team).

Structural United

States

Hospital

(2008)

The ICER was estimated at $2367 per QALY, probabilistic sensitivity analysis

suggested that this result was robust (year of dollar estimates unclear, study

completed in 2008). Antimicrobial stewardship teams were associated with

8.01 QALYs and cost $40,144, whereas standard care was associated with 7.92

QALYs and cost $39,776.

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[17] Decision tree

modelling

Rapid diagnostic for Methicillin-Resistant

Staphylococcus aureus for bloodstream

infections, compared to traditional empiric

antibiotic therapy (empiric vancomycin and

.empiric semi-synthetic penicillin treatment

protocols were separate comparators).

Structural United

States

and

Europe

Union

(EU)

Hospital

(2009)

Dominance was shown for PCR testing (2009 USD) against both comparators

(ICERs estimated at 24 EUR per life year gained and 26.8 EUR per life year

gained compared to empiric vancomycin and empiric semi-synthetic penicillin

treatment respectively). In the European setting, PCR was associated with 28.7

life years and a cost of 18,253 EUR, empiric vancomycin with 26.2 life years

and 18,193 EUR and empiric semi-synthetic penicillin with 26.5 life years and

18,194 EUR.

[18] Unclear Rapid diagnostic for Candida infections,

compared to standard care with no test.

Structural United

States

Hospital

(2009-20

11)

An estimate of $415 net saving per patient is given (year of dollar estimates

unclear, study conducted 2009-2011).

Cost-Benefit Analyses

[19] Markov

modelling

A CDI control program that included the

Antimicrobial Use option of the

Antimicrobial Use and Resistance module of

the National Healthcare Safety Network,

compared to no intervention.

Persuasive

and Structural

United

States

(Medicar

e)

Hospital

(2011)

With 50% intervention effectiveness, the cost savings were estimated at $2.5

billion (95% credible interval: $1.2 billion to $4.0 billion) nationally (2011

USD).

[20] Interrupted

time-series

analysis

Promotion of local and international

guidelines, appointment of an infectious

disease specialist, infectious disease rounds,

audit and feedback of antimicrobial use,

compared to no intervention.

Persuasive

and Structural

Germany Hospital

(2012-20

15)

Net cost savings of € 2,575 per month (p = 0.005) (year of EUR estimation

unclear, 2012-2015 data), in a large orthopaedic surgical department in a

community-based hospital.

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Abbreviations: CDI – Clostridium difficile infection, EU – European Union, EUR – Euro, ICER – incremental cost-effectiveness ratio, PCR – polymerase chain

reaction, MRSA - Methicillin resistant Staphylococcus aureus, QALY – quality adjusted life year, USD – United States Dollars

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Figure 1: Recommendations for Cost-Effectiveness Studies for Antimicrobial Stewardship

Programmes

*The CHEERS checklist was developed by Drummond et al. and offers a comprehensive checklist regarding health

economic models [26].