Incorporating environmental impacts into the economic evaluation of health care systems: Perspectives from ecological economics

Resources, Conservation & Recycling 154 (2020) 104623

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Incorporating environmental impacts into the economic evaluation of health care systems: Perspectives from ecological economics

T

Martin Henshera,b,* a

Associate Professor of Health Systems, Financing and Organisation, Deakin Health Economics, Deakin University, Building BC3, 221, Burwood Highway, Burwood, VIC, 3125, Australia b Adjunct Associate Professor, School of Medicine, University of Tasmania, Level 1, Medical Science 1, 17 Liverpool Street, HobartTAS 7000 Australia

A R T I C LE I N FO

A B S T R A C T

Keywords: Health care Environmental impacts Externalities Economic evaluation Health economics Ecological economics

Health care is responsible for a range of negative environmental impacts, including greenhouse gas emissions, air pollution, plastics waste, and pharmaceutical pollution of ecosystems through excretion and inappropriate disposal. Evidence on the scale of these impacts has been growing in high-income countries. To date, there has been only limited discussion of how environmental impacts might be incorporated into economic evaluations of health care programs, including health technology assessment. This paper considers why and how this aim might be achieved, using perspectives from both mainstream and ecological economics. There are strong arguments for using economic evaluation to internalise the negative environmental externalities currently being generated by health care, as well as precautionary arguments for health systems to better understand their exposure to their environmental impacts. The paper tests the feasibility of incorporating the costs of greenhouse gas emissions within costing for economic evaluation, and concludes that the use of shadow prices to achieve this aim is feasible. It suggests that this cost-based approach is preferable to more convoluted attempts to incorporate environmental impacts in the outcome component of health economic evaluations. The interaction between overuse, antimicrobial resistance and environmental harms of health care is identified as an area that would benefit from investigation using innovative economic methods.

1. Introduction In many countries around the world, the attention of health professionals and of the health care systems and organisations within which they work is being increasingly drawn to questions of environmental sustainability, planetary boundaries and anthropogenic climate change. As evidence continues to grow on the grave risks and costs of inaction, authoritative calls for urgent action become stronger: most recently the IPCC’s recent call for greenhouse gas emissions (GHG) to be reduced to 45% of 2010 levels by 2030 (IPCC, 2018), and the IPBES global assessment report on biodiversity and ecosystem services (IPBES, 2019). The significant negative impacts of anthropogenic climate change on human health have been understood for some time (Haines et al., 2006; Costello et al., 2009), with climate change having been regarded as the biggest global health threat of the 21st Century for over a decade (Costello et al., 2009; WHO, 2019). The emerging “planetary health” movement (Whitmee et al., 2015; Myers, 2017) has sought to direct research, policy and professional

attention to the deeply intertwined relationships between human health and the health of the natural environment and the planet, with recent calls for health professionals to embrace this perspective in their advocacy and in their clinical practice (Veidis et al., 2019). Meanwhile, work has been underway for some years in different health systems around the world examining how health care delivery might itself be made more sustainable through reducing its negative impact on the natural environment (e.g. Schroeder et al., 2012; Pencheon, 2013), with growing evidence on issues such as reducing waste and improving reuse (Campion et al., 2015; Unger et al., 2016; Willskytt and Tillman, 2019), and on the carbon footprint of health services. In particular, a number of studies have now provided estimates of the total greenhouse gas emissions of national health systems (NHSSDU, 2014b; Malik et al., 2018; Eckelman and Sherman, 2016; Eckelman et al., 2018; Pichler et al., 2019; Karliner et al., 2019; Nansai et al., 2020), indicating that health systems in high income countries generate non-trivial portions of total national GHG emissions. Given the size of health care as a proportion of the economy – 10.8% of Gross Domestic Product (GDP)

⁎ Corresponding author at: Associate Professor of Health Systems, Financing and Organisation, Deakin Health Economics, Deakin University, Building BC3, 221, Burwood Highway, BurwoodVIC, 3125, Australia. E-mail addresses: [email protected], [email protected].

https://doi.org/10.1016/j.resconrec.2019.104623 Received 1 June 2019; Received in revised form 28 November 2019; Accepted 29 November 2019 0921-3449/ © 2019 Elsevier B.V. All rights reserved.

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“extra-welfarist” – in essence, concerned only with the evaluative space of health itself, rather than broader welfare (Birch and Donaldson, 2003; Brouwer et al., 2008; Coast, 2009). At the same time, textbooks and guidelines often exhort analysts to ensure that economic evaluation in health care incorporates a broader “societal perspective” on costs and outcomes, rather than just concerning themselves with health system costs and outcomes (the extra-welfarist approach), yet this appears to be honoured mainly in the breach (e.g. Drummond et al., 2015; Sanders et al., 2016). We will return later to the significance of these debates in relation to the environmental impacts of health programs. Economic evaluation can be applied to almost any variety of health care program or level of a health care system. Applications might include any of the following: economic appraisal of alternative options for a major capital project (e.g. building a new hospital, or introduction of a national electronic medical record scheme); allocating resources within the overall health budget between different programs (e.g. the Ministry of Health in a low income country considering how much to allocate to rural maternal and child health services versus how much to allocate to a new neurosurgical service in the capital city); a local health funder wishing to understand whether to invest in additional acute psychiatric beds or community-based crisis intervention services; or a national agency deciding whether or not to include a new pharmaceutical product in the publicly funded drugs schedule. In low and middle income countries, there has been extensive use of sectoral costeffectiveness analysis by both national governments and international agencies, focusing on the use of economic evaluation to make optimal high-level allocation and prioritisation decisions between populations and programs (e.g. Jamison et al., 2006, 2018). Yet despite ubiquitous calls for “value based healthcare”, in high-income countries the reality is that the main effort in economic evaluation has been focused overwhelmingly on Health Technology Assessment (HTA). Broadly, HTA refers to the multidisciplinary analysis of the medical, economic, social and ethical implications of new health technologies (Luce et al., 2010). In some countries (e.g. England, Australia, Sweden), HTA has been institutionalised as part of the process of approving drugs and/or medical devices for public funding and reimbursement, requiring the presentation of an economic evaluation (often, but not everywhere, a CUA) as a core part of the evidence under consideration. Countries which have formalised economic evaluation for HTA generally use either an explicit or an implicit “cost-effectiveness threshold”, expressed in terms of a cost per QALY that technologies are expected to sit below in order to represent a cost-effective use of public health funding. For example, in the UK, National Institute for Health and Care Excellence (NICE, 2008) guidance states that, while it has never explicitly set a threshold, most interventions it approves generally lie within the range of GBP20,000–30,000 (NICE, 2008), although in recent years it has moved to allow significantly more generous thresholds in for certain special criteria, such as end of life care (Paulden, 2017). At the same time, evidence has grown that NICE’s standard guidelines may well be too generous, with estimates that new technologies approved through HTA might be displacing substantially more cost-effective standard treatments in practice (Claxton et al., 2015). Nevertheless, the introduction of a formal requirement for economic evaluation to support HTA in several jurisdictions has focused much of the practical effort in applying health economic evaluation firmly on this area, possibly to the detriment of other applications.

across high income countries on average (Chang et al., 2019) – this is scarcely surprising. However, health economists appear to have had only a limited degree of engagement with this growing focus on health, health care and the environment. In particular, there has been little attempt to consider the incorporation of environmental costs or benefits in economic evaluations of health care interventions or programs (the stock in trade of most health economists). The honourable exceptions to this charge are the work of Marsh, Ganz and colleagues (Marsh et al., 2016a, b), de Preux and Rizmie (2018), and the recommendation in recent US guidelines that cost-effectiveness analyses should include a “societal reference case” with an impact inventory that includes a section on “Environment: production of toxic waste pollution by intervention” (Sanders et al., 2016). It is therefore the objective of this paper to explore the theoretical and practical considerations involved in incorporating environmental sustainability more directly within the economic evaluation of health care systems, programs and interventions. This will be done not only with reference to existing health economics theory and the evidence on health, health care and the natural environment; but also by introducing a number of concepts and perspectives from the discipline of ecological economics, which have thus far not been applied to health care. The existing evidence will be used to construct a small number of illustrative estimates of the potential materiality of incorporating environmental impacts in the economic evaluation of health care. 2. Economic evaluation of health care – Overview Drummond et al. (2015) define economic evaluation in health care as follows: “…the comparative analysis of alternative courses of action in terms of both their costs and consequences. Therefore, the basic tasks of any economic evaluation are to identify, measure, value and compare the costs and consequences of the alternatives being considered.” (Drummond et al., 2015: 4) The economic evaluation of health care dates back at least to the Second World War, although “health economics” only began to take clear shape as a specific sub-discipline of economics in the late 1950s (Mushkin, 1958). From the 1970s, economic evaluation has become one of the key activities within health economics, and has grown in sophistication and formalisation over the years. While all economic evaluations in health care involve estimating the costs associated with the interventions or programs under investigation, three main forms of economic evaluation have emerged which differ primarily in how they measure and express the outcomes (or consequences) of these programs (Drummond et al., 2015). Cost-Effectiveness Analysis (CEA) uses measures of outcome that can compare the particular interventions in question (for example by using a specific disease-related measure, e.g. reduction in blood cholesterol levels). Cost-Utility Analysis (CUA), by contrast, uses generic measures of health-related quality of life, such as Quality Adjusted Life Years (QALYs) or Disability Adjusted Life Years (DALYs), which are designed to allow comparison of cost-utility across different health programs. Cost-Benefit Analysis (CBA) uses monetary valuations of health states and outcomes (often generated by different techniques of willingness to pay analysis) to allow a direct monetary comparison of costs and benefits; and (in principle, at least) allows direct comparison of the costs and benefits of health interventions with completely different activities (e.g. education or environmental programs). CBA has traditionally been less widely used in health care than in other sectors, but there has been an increasing trend towards applying monetary valuations to the QALY gains estimated via CUA, to generate estimates of Net Monetary Benefit (e.g. Eckerman, 2017) which look a lot like a form of CBA. A philosophical debate amongst health economists has queried whether economic evaluation in health care is concerned with wider “utility” of all forms (the fundamental basis of welfare economics, health economics’ direct ancestor), or whether it is

3. Environmental economics and ecological economics – Overview Some health economists may have some familiarity with the discipline of environmental economics, a branch of neoclassical welfare economics which focuses particularly on incorporating nature as a form of capital, and which takes the view that sustaining that natural capital is a precondition for economic sustainability (Thampapillai and Sinden, 2013). Environmental economics therefore sees the natural world and 2

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Standard theory is also very clear that the presence of negative externalities is an example of market failure, and should be rectified as far as possible by internalising such spillover costs back onto the original parties to the transaction (Mishan, 1988), giving rise to familiar concepts such as the “polluter pays” principle. Ecological economics provides a helpful way of visualising the potential presence of negative environmental externalities through its approach to the production function. The standard treatment of the production function in mainstream economic textbooks is of the following form, simply including two factors of production, where K is capital and L is labour (eq. 1). The frequently used Cobb-Douglas production function (eq. 2) incorporates total factor productivity (A) and the output elasticities of capital and labour (α, β):

environment primarily in terms of resources as capital: natural resources with direct market values (such as forests, fisheries, mineral deposits etc.), ecosystem services which have not been correctly valued by markets (e.g. clean air, clean water etc.), or spillover effects such as pollution. This leads to a strong focus on property rights and on the appropriate treatment of negative externalities (Tietenberg and Lewis, 2015). Environmental economists certainly see the natural environment as of very great importance, and recognise that markets frequently fail to value the environment correctly; but they do so within the wider framework of the economy as the containing vessel which frames all such valuations. Perhaps less familiar to health economists and other health researchers is the discipline of ecological economics. Ecological economists start from a different premise regarding the relationship of the natural world to the economy than do neoclassical economists. The “pre-analytic vision” of ecological economics sees the human economy as an open sub-system of a larger ecosystem (the planet Earth) which is effectively materially closed and finite, other than in its receipt of solar energy (Daly, 2004; Daly and Farley, 2011). In ecological economics, the laws of thermodynamics will ultimately trump the laws of economics (Georgescu-Roegen, 1971). Thus, while ecological economics is very much concerned with allocative efficiency and just distribution in pursuit of human flourishing, its crucial point of difference with environmental and neoclassical economics is its concern with scale (Daly, 2004) – the physical scale of the economy, often described as “material throughput” (Daly, 1977) or “ecological footprint” (Wackernagel and Rees, 1997). Core questions of overall economic scale which this raises are firstly whether an economy of a given size can in fact be sustained in the long-run given its use of and impact on the wider environment, and second, whether growth in scale of the economy is actually generating “goods” faster than it is undermining welfare through generating “bads” (pollution, resource depletion, social harms etc) – and thus whether economic growth may in fact have become uneconomic growth (Daly, 2013). Ecological economists have devoted significant time to considering the macroeconomic models and conditions which might allow for a level of economic activity which can both promote human well-being, justice and flourishing, while also being environmentally sustainable for the long-term. Specific models include the steady state economy (Daly, 1977; Lawn, 2010; Jackson, 2009) and degrowth (Kallis et al., 2012; Klitgaard and Krall, 2012), and ecological economists have been closely involved with emerging movements towards a sustainable “well-being” or “post-growth” economy (Kubiszewski et al., 2013; Raworth, 2017; Jackson, 2019) and the debate on whether “green growth” is actually possible (Bowen and Hepburn, 2014; Hickel and Kallis, 2019).

1 Q = F(K,L) or 2 Q = A(Kα,Lβ) By contrast, the ecological economics production function (eq. 3) embodies a wider range of funds and flows (Daly and Farley, 2011: 158), more fully capturing the interaction of production with the wider world of ecosystems and natural resources: 3 q + w = F(N, K, L; r, e) In this production function, q represents flows of products and w represents flows of waste as outputs of the production process, N represents natural capital (both a stock and a flow), while K and L are funds of labour and capital, r represents flows of natural resources and e flows of energy (Daly and Farley, 2011). In this formulation, it becomes much clearer how production processes are using natural resources and energy, and generating negative waste pollution – when these effects are obscured in a simple Cobb-Douglas production function. It therefore provides a helpful starting point for considering more systematically how to internalise negative externalities so that resource allocation decisions can more fully reflect the true costs of health care (both societal and ecological), and so that producers can optimise their production processes. While the argument from negative externalities provides an extremely strong theoretical case for incorporating environmental impacts into the economic evaluation of health care, there is also a strong pragmatic and precautionary case to argue. As the scale and urgency of the required transition to a low or net zero carbon economy becomes clearer and starker almost by the month (IEA, 2019; IPCC, 2018), the possibility of more concerted national and international policy responses cannot be ruled out, despite limited progress to date. One obvious risk to the health care sector is that more assertive policy efforts to drive progress on decarbonisation will one day directly raise energy and product prices, either through meaningful carbon taxes, carbon pricing through emissions trading schemes (e.g. Barron et al., 2018), or even through direct quantity controls. Indeed, the International Monetary Fund (IMF) has recently called for a global carbon tax of US $75 per tonne of CO2eq (IMF, 2019). The ecological macroeconomics literature suggests that, if “green growth” and the sufficient absolute decoupling of material throughput from GDP growth that it requires (Stoknes and Rockstrom, 2018) proves not to be achievable in practice, then more aggressive direct controls on resource extraction, energy and material use will become unavoidable (Hickel and Kallis, 2019). Health care funders, organisations and suppliers might therefore need to consider incorporating the risk of increased prices to their business models in advance of such policy changes occurring. Far from being a radical move, this would simply see health care catching up with other major businesses (especially those in the energy and natural resources sectors), many of whom already use shadow carbon pricing in their own investment appraisal processes, and who are under ever greater pressure from financial regulators in many countries to disclose their exposure to climate risks more fully (e.g. Potter and Fernyhough, 2019).

4. Why address environmental impacts in economic evaluation of health care? Marsh et al. (2016b) suggest two reasons why HTA methods might be expanded to incorporate environmental impacts: first, that there is a link between the environment and health outcomes, and second that health care decision makers’ objectives include broader social welfare concerns. Both are uncontentious; indeed, since their article was published, evidence from the USA has started to quantify the significant negative health impacts of environmental pollution caused by the health sector itself (Eckelman and Sherman, 2016, 2018), which will be considered further below. However, the reasons cited by Marsh and Ganz in fact ignore two rather stronger economic arguments for the incorporation of environmental impacts within all forms of economic evaluation for health. A standard element of mainstream economic theory is the concept of the negative externality, whereby costs related to a transaction or exchange fall on actors who were not party to that exchange – i.e. some costs are externalised onto other parties. Indeed, pollution is one of the typical textbook examples used to illustrate negative externalities. 3

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Table 1 Primary mechanisms of health care impact on the natural environment. Pollutant:

Manufacturing and Supply Chain

Health Care Infrastructure

Clinical Care

– – – –

– – –

–

Greenhouse Gases Particulate matter/air pollution Plastic waste Pharmaceutical/chemical contamination

Patient Metabolism / Excretion

– –

5. What are the environmental impacts of health care? Evidence and measurement

pharmaceutical manufacturers (Belkhir and Elmeligi, 2019); and a comparative study of the carbon footprint of operating theatres in Canada, the USA and the UK (MacNeill et al., 2017). A number of examples of studies evaluating the GHG intensity of specific services, service models or interventions are also now available, including renal services (Connor et al., 2010) and service model changes for patients with acute myocardial infarction (Zander et al., 2011). Marsh et al. (2016a) explore how environmental factors might be incorporated into HTA, providing a case study comparing CO2 emissions under two treatment regimens for diabetes (oral antidiabetic medication only versus oral antidiabetic medication plus basal insulin). Unger and Landis (2016) and (Unger et al., 2016) compare the environmental impacts (including CO2e intensity) of a range of common single-use versus re-usable health care supplies. Meanwhile, the NHS Sustainable Development Unit has published studies on the carbon footprint of certain key health care inputs, such as commonly prescribed drugs and other commonly procured supplies (NHSSDU, 2014a, 2017). There is thus no question that the production of estimates of GHG emissions for health care is technically possible at any level of granularity of the health care system. Within their estimates of the environmental impacts of the US and Canadian national health care systems, Eckelman and Sherman go further and derive estimates of the harms to human health flowing from health care-generated pollution. They estimate that the likely global DALY loss resulting from US health care-related GHG emissions (Eckelman and Sherman, 2018) will be between 123,000 and 381,000 DALYs annually, although their similar estimate for the health impact of GHG emissions from the Canadian health care system lay in a much more uncertain range between 373 (i.e. almost none) and 581,000 DALYs lost globally per year (Eckelman et al., 2018). In the USA, they estimated that, on a life cycle basis, particulate matter (PM) pollution exposure attributable to the health care sector could cause an annual

The key mechanisms by which health care production and consumption impacts upon the natural environment through pollution are summarised in Table 1 below: Greenhouse gas emissions are currently the best understood and most readily quantified route by which health care systems impact upon the natural environment. In recent years, a number of studies have used similar economic input-output (EIO) methods (Leontief, 1970) to estimate the overall carbon footprint of several national health systems in high income countries; two very recent studies have provided transnational estimates. Table 2 summarises some of their results in terms of the relative contribution of health care to overall national GHG emission. Two features of the estimates in Table 2 are important to note. First, they make clear that the carbon footprint of healthcare is significant, both in absolute terms and as a contributor to overall emissions. Second, though, it is clear that the technique of input-output analysis (based on emissions intensities of health care expenditure) is not a precise science; there are substantial differences between some of the estimates (most notably for the USA and China, the largest emitters overall). While these estimates are important as guides for macro-level policy, the endogeneity of health care expenditure to their methods, and their degree of uncertainty, both suggest that EIO techniques may not be suitable as a source of data on GHG emissions at service level of the type needed for economic evaluations. A growing number of smaller-scale studies are now available which use life-cycle assessment or bottom-up estimation methods to examine GHG intensity of different levels of the health care sector. These include studies of whole hospitals (e.g. Bambaren-Alatrista and AlatristaGutierrez, 2016); a study of the carbon footprint of major global

Table 2 Selected estimates of national health care greenhouse gas emissions. Country

Year

Total GHG (Mt CO2e)

Health Care as % National GHG

Reference

Global OECD + China + India USA USA USA Australia Australia Australia Canada Canada Canada England England Japan Japan China China India India

2014 2014 2014 2013 2014 2014-15 2014 2014 2015 2014 2014 2017 2012 2011 2015 2014 2014 2014 2014

2000 1654 547 655 480 36 20 ns 33 ns 30 27 32 62 72 342 601 39 74

4.4% 5.5% 7.6% 9.8% 7.9% 7.0% 4.2% 5.1% 4.6% 5.2% 5.1% 6.3% 3.6% 4.6% 5.2% 3.0% 6.6% 1.5% 3.5%

Karliner et al. (2019) Pichler et al. (2019) Karliner et al. (2019) Eckelman and Sherman (2016) Pichler et al. (2019) Malik et al. (2018) Pichler et al. (2019) Karliner et al. (2019) Eckelman et al. (2018) Karliner et al. (2019) Pichler et al. (2019) NHSSDU (2018)a NHSSDU (2014b)a Nansai et al. (2020) Nansai et al. (2020) Karliner et al. (2019) Pichler et al. (2019) Karliner et al. (2019) Pichler et al. (2019)

a The difference between the 2012 and 2017 estimates for England is due primarily to the use of different methods for estimating the overall England national footprint denominator (NHSSDU, personal communication).

4

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6. Valuing the environmental impacts of health care

loss of 370,000 DALYs, with another 35,000 DALYs lost due to other categories of pollutant (Eckelman and Sherman, 2016); they estimated that PM pollution from the Canadian health system caused between 3900 and 23,500 DALYs to be lost annually (Eckelman et al., 2018). While their work currently appears to be unique, Eckelman and Sherman have shown clearly that EEIO models can be harnessed to generate estimates of key pollutants from health care and of their direct and indirect adverse impacts on human health. Global public concern has grown in recent years concerning the environmental impacts of the large quantities of plastic waste pollution that have accumulated across the planet since the widespread introduction of plastics some 60–70 years ago (e.g. Malizia and Monmany-Garzia, 2019). One estimate suggests that, between 1950 and 2015, 7800 Megatonnes of plastics had been produced globally (3900 Mt in the last 13 years of that period), some 60% of which had been discarded in landfill or the natural environment (Geyer et al., 2017). Concerns over the impacts of plastics involve both ecosystem and human health, especially given the emerging evidence that plastics do not degrade fully, yet do break up into micro- and nano-particles which appear to be ingested or absorbed by a wide range of living organisms, including humans (Galloway, 2015). Health care has become an enthusiastic consumer and discarder of plastics, especially since the advent of single-use disposable plastic items as an adjunct for hygiene and infection control (Hodges, 2017). However, while there is considerable interest in reducing medical plastics waste and in developing viable approaches for its recycling (e.g. Schroeder et al., 2012; Pencheon and Dalton, 2017), it is less clear that estimates are yet available for both the scale and impact of health care plastics use that might practically inform economic evaluations of services or developments. Amongst researchers and policy makers, concern has risen over the last two decades regarding the level of pharmaceutical pollution reaching ecosystems, and its potential impacts on ecosystem and human health. Pharmaceuticals enter the natural environment through three main routes: poor pollution control at manufacturing plants (UNEP, 2017), excretion of active ingredients by patients (human and livestock), and inappropriate disposal of unused medications by patients and health care facilities (Bound and Voulvoulis, 2005). While rates vary significantly between different compounds, significant quantities of the active ingredient of many orally administered medications are excreted by humans and animals, often between 30% and 90% of the original dose (bioIS, 2013; Bound and Voulvoulis, 2005). Only around 10% of pharmaceutical compounds show “reasonable biodegradability” in the short term (Straub, 2016). A significant number of studies have investigated the level and range of pharmaceutical compounds detectable in treated water exiting Wastewater Treatment Plants (WWTPs) in many countries (e.g. Zuccato et al., 2006; Bellver-Domingo et al., 2017; Kumar and Xagoraraki, 2010), while others have investigated their presence in natural environments (e.g. Richmond et al., 2018); all find large numbers of different pharmaceutical compounds present. Documented impacts on ecosystem health include feminizing effects of hormonal contraceptives and other endocrine disruptors impacting reproduction in fish, antibiotics impacting environmental bacteria and algae populations, and impacts of antiparasitics on soil and dung fauna (bioIS, 2013; Bound and Voulvoulis, 2005); evidence of impacts on human health is less clear, but there is significant concern that environmental pollution with antibiotics is driving increased antimicrobial resistance (AMR) (Pencheon and Dalton, 2017; UNEP, 2017). Unsurprisingly, scale is a key issue in considering the risks and impacts of pharmaceutical pollution; while they may not have the highest individual risk of toxicity, clearly it is those drugs which are most widely prescribed and used (including over the counter medications) which are present in ecosystems in the highest concentrations (Donnachie et al., 2016).

A large and diverse literature exists on the valuation of ecosystems and on valuing harms to the environment. Some of it has close parallels with techniques employed in health economics; but it comprises many other approaches and concepts with which health economists (the author included) are unlikely to be familiar. Techniques frequently encountered in the environmental and ecological economics literature include stated preference methods such as contingent valuation, choice experiments, environmental damage schedules and multicriteria decision analysis (Adamowicz et al., 2008), and other approaches such as avoided costs, replacement costs, factor income, travel cost and hedonic pricing (Farber et al., 2002). No attempt will be made here to review this literature in anything other than the most fleeting of terms; rather, the focus will be on providing a brief summary of the valuation literature as it relates to the key environmental impacts of health care described above. At the macro scale, increasing attention has been paid over the last two decades to the valuation of ecosystem services. The “value” of ecosystem services refers to the benefits that people derive from ecosystems and the support for sustainable human wellbeing that ecosystems provide (Costanza et al., 2014; Farber et al., 2002), or “valuing nature’s contribution to people” while accepting the wide diversity of values that must be incorporated in that effort (Pascual et al., 2017). This approach has in some places given rise to experiments with “Payment for Ecosystem Services” (PES), whereby the owners / suppliers of ecosystem services are provided with compensation to promote continued provision of those services (Bennett and Gosnell, 2015) or as a way of internalising negative environmental externalities on a routine basis (Bellver-Domingo et al., 2016). Yet valuation of ecosystem services tends to be easier at a very large scale, is increasingly data intensive to apply at more local levels (Pandeya et al., 2016), and is not in itself directly applicable to decision-making on specific environmental externalities, such as those generated by health care (Costanza et al., 2014). However, an area of environmental valuation which is far advanced is very directly relevant to health care, namely the development of estimates of the “social cost of carbon”. The social cost of carbon (SCC) represents in monetary terms the damage caused by emitting an additional ton (or tonne, depending on jurisdiction) of CO2e (van den Bijgaart et al., 2016) – “…the change in the discounted value of economic welfare from an additional unit of CO2 equivalent emissions” (Nordhaus, 2017). Estimates of the SCC are usually generated from Integrated Assessment Models (IAM), that incorporate modules projecting population and economic factors, the likely trajectory of climate change, damages and benefits from climate change, and discounting of future benefits and costs – often over long time periods. Debate continues over many aspects of these IAMs and the SCCs they generate – for example, their tendency to underestimate more extreme outcomes and potential climate tipping points and hence to understate the SCC (Lontzek et al., 2015); inherent uncertainty in IAMs (Pezzey, 2019); the impact of lower or higher discount rates on future generations (Nordhaus, 2017); and the need to use SCCs that incorporate global impacts rather than purely national factors (Revesz et al., 2017). SCCs are in fact in widespread use in many countries and by international organisations, often with explicit advice that the relevant SCC should be used for project appraisal in public investment projects or as part of the environmental impact assessment of major private projects. This is crucial for any consideration of economic evaluation in health care, and the consequences of the accomplished fact of official SCCs will be returned to below. Table 3 provides a few examples of SCCs and policy guidance from around the world (n.b. SCCs rise progressively over time, and the different guidance expresses different ranges, e.g. low / central / high or low / high etc.). It is, of course, important to note that United States President Donald Trump issued a Presidential Executive Order on March 28th 2017 disbanding the US Government working group that 5

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Table 3 Official Guidance on Social Cost of Carbon in Selected Countries. Country/Institution

SCC range - Cost per Tonne CO2e (Year)

Guidance/Uses

References

UK

£0 - £14 - £28 (2020) £40 - £81 - £121 (2030)

Public policy and project appraisal

Canada

C$41 – C$167 (2020) Central – 95

HMT (2018) DBEIS (2019) ECCC (2016)

World Bank

$40-$80 (2020) $78-$156 (2050)

IMF USA

$75 Pre-2017 (revoked): $14 - $72 (2020) $30 - $110 (2050) From 2017: $1 - $6 (2020) $2 - $11 (2050)

th

%ile C$75 – C$320 (2050)

Cost-benefit analysis for Regulatory Impact Analysis Statements Economic analysis for project appraisal; compulsory for some projects, “invited” for others Proposed optimal global carbon tax Monetizing the value of changes in GHG emissions resulting from regulations

World Bank (2017) IMF (2019) Jacobs (2018)

as possible through the cost, rather than the outcome, side of the equation (Mishan, 1988). The work cited above shows that quantification and attribution of GHG emissions to services and interventions is entirely possible. In the case of GHG emissions in particular (but also, to a reasonable extent, air pollution), estimates of the social cost of carbon are available that could make their incorporation as a cost in health economic evaluation entirely practical via shadow pricing. It is true that in some countries (most notably the USA) the social cost of carbon has become a deeply loaded political issue. Yet in several others, there is very clear public guidance on what SCC should be used in project appraisal. Given that most of the health care funders currently using economic evaluation and HTA outside the US are public entities, it might even be reasonable to ask the question as to why they are not already following their own national guidance in this area. Where such guidance exists, a strong case can surely be made that it should be adopted straight away.

had advised on previous official values for the SCC, and revoking the previous SCC guidance, reverting to values from 2003 Bush-era regulations (POTUS, 2017). Table 3 therefore shows both the now-revoked SCC estimates and the lower values that replaced them in 2017. While significantly less extensive than the social cost of carbon literature, much work has been undertaken on placing a monetary value on the externalised costs of air pollution in particular, with Bai et al. (2018) providing a useful review. A 2007 US study not only showed large economic costs from air pollution, but also that these costs were overwhelmingly driven by damage to human health (Muller and Mendelsohn, 2007). Meanwhile, a few studies examine the estimation of shadow prices to account for the environmental benefits of removing selected pharmaceuticals from waste water treatment plants (MolinosSenante et al., 2013; Bellver-Domingo et al., 2017). While not examining a pharmaceutical, another study investigated approaches to estimating the health costs of triclosan, an antibacterial agent that started life as a health care product, with endocrine-disrupting properties (Prichystalova et al., 2017). There is a long way to go before “off the shelf” estimates of the costs of pharmaceutical pollution will be available.

8. Incorporating GHG costs in economic evaluation – Some illustrative estimates At the time of writing, only one health economic evaluation could be identified which had not only estimated the carbon footprint of the interventions under scrutiny, but also incorporated them as a cost within the analysis. This study was by de Preux and Rizmie (2018), and sought explicitly to test the inclusion of the costs of GHG emissions within a cost-effectiveness analysis of different modes of haemodialysis delivery in the UK National Health Service. Using a social cost of carbon of GBP52 per tonne, their estimates suggested that the inclusion of carbon costs added between 0.7% and 1.3% to total financial costs, depending on the carbon intensity of the treatment mode in question. de Preux and Rizmie (2018) show clearly that internalisation of costs of carbon within the economic evaluation of healthcare is feasible, but provide only one data point. This section therefore undertakes a secondary analysis of a number of other studies which provide estimates of the carbon footprint of different health services or interventions, to generate secondary estimates of the likely costs of carbon therein. The primary aim of this exercise is to assess the likely order of magnitude of carbon costs in economic evaluation if they are to be included in economic evaluation, and not to pretend to deliver definitive estimates for any of the services under consideration. Esmaeili (2016) and Alshqaqeeq et al. (2020) undertook a systematic review of the literature to identify studies of healthcare services which had included estimates of the relevant carbon footprint. His search strategy was updated to identify any more recent studies. These studies were primarily of carbon footprints, and did not include cost estimates. Where feasible, relevant Australian unit cost data (IHPA, 2019; PBS, 2019; MBS, 2019) have been used to provide a baseline financial cost. Three scenarios for a social cost of carbon have then been applied (see Tables 3 and 4 for details): a low scenario based on the mid-range of current UK guidance for 2020; a mid-range scenario based on the IMF’s proposed carbon tax; and a high estimate based on the upper Canadian guidance for 2050. This selection is simply to provide a

7. Should environmental impacts be treated as costs or outcomes in economic evaluation? In considering the possible inclusion of environmental impacts in HTA, Marsh et al. (2016b) consider a number of possibilities: including health gains from improved environmental outcomes into estimates of HRQoL; considering health care decision makers willingness to pay for environmental gains; use of cost benefit analysis; or inclusion of environmental factors in Multi Criteria Decision Analysis (MCDA). Given the preceding discussion of health care’s environmental impacts, some discussion of their points is warranted. As they note, incorporating health impacts into HRQoL measures confines the evaluation of environmental impacts purely to health. Yet GHG emissions from health care have all the wider social and ecosystem impacts of climate change as any other sector’s emissions, while plastics and pharmaceutical pollution may have much more significant impacts on ecosystems than directly on human health. While internally consistent with the world view of extra-welfarism, constraining consideration of environmental impacts to health effects alone seems somewhat to miss the point of bothering with any level of environmental impact assessment; while mechanisms for assigning back the externalised health effects of any given treatment (which by definition fall on people other than the patients concerned) to adjust the HRQoL scores of the patients concerned may require some very convoluted logic. However, use of MCDA techniques would be wholly reasonable, although it necessarily is complex and may not fully allow for the internalisation of negative externalities. Ultimately, there is a need to confront a more fundamental issue. In standard economic theory, in environmental economics and in ecological economics, the negative externalities of environmental harms are costs, and economic evaluation should seek to re-internalise them as far 6

7

NHCDC NHCDC NHCDC NHCDC 0.7% 0.5% 2.1% 1.2% 0.2% 0.2% 0.7% 0.4% 0.1% 0.0% 0.2% 0.1% 19.01 30.47 39.28 4.75 6.60 10.58 13.64 1.65 1.52 2.43 3.13 0.38 2859.55 5725.86 1885.21 384.07 88 141 181.8 22 McGain et al., 2018 Power et al., 2012 Morris et al., 2013 Connor et al., 2010

4235 8480 2792 568.81

0.0% 0.9% 1.4% 0.0% 0.3% 0.5% 0.0% 0.1% 0.1%

High Medium Low High

0.02 1.45 4.28 0.01 0.50 1.49 0.00 0.12 0.34 75.15 168.80 308.71 111.30 250 457.20 0.11 6.7 19.8 Martin et al., 2018 Martin et al., 2018 Martin et al., 2018

Diagnostic Imaging: Abdominal Ultrasound Abdominal CT Scan Abdominal MRI Scan Hospital care: ICU for septic shock (bed day) Laparascopic Cholecystectomy Cataract surgery Haemodialysis

Table 6 Carbon footprint unit cost scenarios for selected services.

Cost (AUS$)

Cost (US$)

broad range for the SCC values to be used. All costs are then converted to US$ using the exchange rates in Table 5 (Treasury, 2019). The results of this analysis are presented in Tables 6 to 8 below. Table 6 provides estimates of the additional and proportionate cost of carbon for a number of health services – diagnostic imaging, ICU care, laparascopic and cataract surgery, and haemodialysis. Table 7 presents the additional and proportionate costs of carbon for different types of inhalers, some of which use propellants which are themselves very potent greenhouse gases. Table 8 completes the analysis of Marsh et al. (2016a) by attaching costs to their estimates of carbon footprint in diabetic therapy. Significant caveats must be acknowledged regarding the approach used in Tables 6 to 8, most crucially that the approaches to life cycle analysis used in the original studies may or may not be comparable, and that unit costs from one country have been applied to services and CO2e estimates from another. Clearly, greenhouse gas emissions are only one dimension of the full environmental impacts and costs of health care service provision. Nevertheless, this approach allows a first approximation of the potential costs of carbon across a range of health care service items, and of the impact of differing levels of social costs of carbon. For most of the services considered, the estimates presented above indicate that – even under a scenario of relatively high social costs of carbon – the inclusion of carbon footprint increases total costs by percentages in only the low single digit range; this appears consistent with the analysis of de Preux and Rizmie (2018). It is unlikely that additional costs of this scale would, in and of themselves, lead to decisive changes in incremental cost-effectiveness ratios. Yet, as the example of the different inhaler propellant types illustrates, this cannot be assumed in all cases. Under medium and even low social costs of carbon, the inclusion of carbon footprint was sufficient to make a highly material difference to the unit costs of HFA227 and HFA134 inhalers. Most of the estimates in Table 6 represent unit costs of services which might be included in an economic evaluation, but which would probably not themselves be the subject of an economic evaluation; they might therefore reasonably be thought of as providing some information about the “background” carbon cost of key hospital services. While the inhalers represent a special case (due to the very high CO2e intensity of their propellants), they suggest that detailed investigation of the carbon footprint of the central intervention under evaluation (especially for drugs or devices within HTA) will be important. Indeed, over time it may be possible to develop reasonably robust estimates of carbon footprint and cost for most key healthcare inputs, which can then routinely be injected into cost models; whereas new products will clearly need to be accompanied by bespoke estimates of their carbon footprint. This is consistent with the general evidence that the pharmaceutical manufacturing process is a key source of health care carbon emissions. As noted earlier, HTA is not the only application for economic evaluation in healthcare. Carbon

Medium

1.481 1.325 0.812

Reference

Australian $ Canadian $ GB Pound

Low

US$1=

Kg CO2e per case

Table 5 Exchange rates used (Treasury, 2019).

Service

$17.24 $75.00 $216.07

Notes

GBP14 US$75 C$320

Cost of Carbon as % of Financial Cost

Low Medium High

Cost of Carbon, US$ per item (by SCC Scenario)

US$ per tonne CO2e

Data

Domestic Currency per tonne CO2e

Description

Social Cost of Carbon Scenario (see Table 3 for sources)

MBS Item 55036 MBS Item 56401 MBS Item 63482

Table 4 Scenarios for Social Cost of Carbon.

A14A H08B C16Z L61Z

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Notes

PBS Item 10024N PBS Item 8288F PBS Item 11273H

High

57.9% 84.7% 0.8%

Medium

20.1% 29.4% 0.3%

Low

4.6% 6.8% 0.1%

Incremental QALYs Incremental costs (GBP) Incremental costs (USD) Incremental carbon kg CO2e Cost of Carbon Scenario USD Incremental cost of carbon Incremental cost per QALY - no CO2e Incremental cost per QALY incl. CO2e Percentage impact of including CO2e

0.36 2668 3285.71 1057 Low 18.22 7411.11 7429.34 0.2%

Medium 79.28 7411.11 7490.39 1.1%

High 228.39 7411.11 7639.50 3.1%

footprint and costs might be expected to have a relatively larger and more material impact on economic evaluations of infrastructure and construction projects, and of service models with differing transport requirements.

18.07 11.37 0.23 46.25 19.87 44.79

31.23 13.42 30.24

1.44 0.91 0.02

6.27 3.95 0.08

If economic evaluations move to incorporate environmental externalities as costs (hence increasing total assessed costs), what implications might this have for funding policies? This will depend most crucially on whether their incorporation takes the form of shadow pricing only, or of a real tax; and on the clarity of objectives and purpose for their inclusion. The case of an effective carbon tax (or a tax on another environmental externality) is relatively straightforward. Such a tax will incur real financial costs on producers along the supply chain, who will reflect these additional costs in their prices. The purpose of such a policy is to reduce use of environmentally damaging products or services, and to encourage producers and consumers to switch to less damaging processes and products respectively. While the implementation of such a tax might be phased in over time to avoid sudden shocks, or subsidies offered to patient groups who might be impacted by a rapid implementation (e.g. low income groups), the whole purpose of such a tax is to change relative incentives, and hence change actual choices and behaviours. Incorporating environmental costs via shadow pricing, however, does not necessarily require additional cash to change hands. Shadow pricing changes the relative prices of alternative options within an economic evaluation. Depending on the magnitude of this change, an environmentally damaging but financially cheaper option (A) might become more expensive (after incorporation of shadow prices) than an environmentally-friendly yet more expensive option (B). As a result, option A might be removed from a funding or benefits schedule, or option B procured in preference to option A. The producers of option A will also be incentivised to reduce its environmental costs, to make it more competitive. But there is no necessary reason for actual funding / reimbursement levels to change to compensate any actors – the shadow prices serve simply to allow a more fully-informed decision to be taken by the relevant “decision maker” who is using the economic evaluation. At first sight, the estimates provided in Section 8 above suggest that major changes in relative superiority might only occur in a minority of cases. However, producer interests might be expected to work hard to lobby for “compensation” for lost future profits; a clear focus on the overall policy goal of reducing environmental damage would be required to avoid rent-seekers from undermining such action (Hensher et al., 2019). Marsh et al. (2016b) allude to the possibility of adjusting cost-effectiveness thresholds, in effect to pay more to incentivise less environmentally damaging interventions. This might be likened to a health sector version of the Australian Government’s Direct Action Plan (Australian Government, 2017), which provides funding to incentivise emissions reductions economy-wide, and might therefore represent a valid option for climate policy in health care, pending persuasion of the health care funders concerned. However, were other policy approaches

0.697 0.263 0.009 HFA227 (Symbicort Rapihaler 50/3) HFA134a CFC-free (Asmol Salbutamol) Dry Powder Inhaler (DuoResp Spiromax)

120 200 120

High Medium Low Unit Cost (AUS$) Doses per unit Kg CO2e per dose Inhaler propellant type:

Table 7 Carbon footprint costs of common inhalers (Jeswani and Azapagic, 2019).

Table 8 Incremental cost-effectiveness of oral antidiabetic medication and basal insulin therapy (Marsh et al., 2016a).

9. Implications for health care funding policies

Unit Cost (US$)

Cost of Carbon, US$ per unit (by SCC Scenario)

Cost of Carbon as % of Financial Cost

M. Hensher

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externalities (especially in relation to future carbon and resource prices) also provides a strong pragmatic argument in favour. It has also argued that the most effective approach to doing so – both theoretically and practically – will be via the use of shadow prices on the cost side of the cost-consequences equation. It has presented some initial attempts to estimate the impact of such shadow prices, and indicated that this approach is feasible. Throughout, it has been made clear that we must not lose sight of the fact that economic evaluation in health care concerns much more than the heavily formalised framework of HTA; incorporating environmental impacts will be equally, if not more important in all the other contexts and levels of the health care system to which economic evaluation can contribute. None of which is to say that the incorporation of environmental impacts into the economic evaluation of health care will be easy. Proportionality of effort will be critical, suggesting that a stepped framework for approaching environmental effects in economic evaluation might be helpful. This might build out sequentially from the initial starting point of simply identifying potential environmental impacts as part of the impact inventory in the societal reference case (Sanders et al., 2016). The next step would be to undertake an environmental impact assessment (EIA), which provides some development and estimation of the magnitude of these impacts and their associated risks (Elliott, 2014) without yet attempting to value them or convert them into units for use in the economic evaluation. The EIA would focus heavily on materiality – illuminating which, if any, impacts are likely to be material and under what circumstances, allowing a decision on which factors then might need to be taken forward to the final phase of detailed estimation and valuation for inclusion in the overall economic evaluation. Readers who have been involved with larger project appraisals beyond the realm of HTA (perhaps for major capital investment projects or strategic health programs, for example) will undoubtedly find this generic approach familiar. The estimates of social costs of carbon within economic evaluations provided in Tables 6 to 8 indicate that early attention to materiality is likely to be important – environmental externalities and costs will be much more relevant to some health care interventions than to others, and analytical effort should be prioritised accordingly. Fig. 1 represents this process for ensuring proportionality of effort graphically: The following areas are particularly highlighted as potentially high value targets in moving forward a pragmatic approach to better including environmental impacts in the economic evaluation of health care. Studies aimed at feeding the development of national-level toolkits or data resources which make accessible simple, generic estimates for key pollutants (especially but not only GHGs), with standard methods for attributing them to different service types (e.g. GP visits, outpatient attendances, hospital bed days, intensive care days, operating theatre minutes / hours, dialysis sessions etc) will be an essential practical tool. Development of common standards for life cycle analysis in health care settings might assist this effort considerably. More broadly, a focused measurement program is badly needed to develop pollution / carbon footprint estimates for a number of representative low income, lower-middle income and middle income country health systems – current evidence is overwhelming biased towards high-income health systems. Not only will this provide important evidence to allow analysis of the current environmental impacts of health care in lower income settings, but it will provide important information on the extent to which environmental impacts might be expected to grow as progress is made towards universal health coverage. Such a program should include not only input-output analysis of aggregate system-level emissions, but also to incorporate life cycle analysis approaches to provide more granular information to support micro-level costing. Just as important as improved footprint estimates, though, will be emerging evaluations of interventions designed to decrease health care emissions (e.g. Alshqaqeeq et al., 2020). While more basic research is required on pharmaceutical pollution of ecosystems, it is probably not yet a high priority for work on

to GHG reduction to be adopted further upstream from health (for example, more challenging carbon taxes), it would be hard to make a general case that cost-effectiveness thresholds should be raised simply to reflect carbon pricing – instead, we might expect cost-effectiveness thresholds to remain unchanged, precisely to sharpen incentives on manufacturers and providers to move production and care models to become less GHG-intensive. Given suspicions that QALY thresholds may already be too generous (Claxton et al., 2015), arguments for “special treatment” for green processes seem harder to make when concerted progress is needed at least cost. 10. Overuse, environmental harms and economic evaluation in health care It is also important to consider briefly the problems of overuse, overdiagnosis and overtreatment. Evidence has steadily been growing of the prevalence and scale of overuse in health care – the phenomenon whereby patients receive care that yields them little or no benefit, yet exposes them to the risks of intervention (Brownlee et al., 2017; Lyu et al., 2017). It is clear that, in addition to risking harm to patients, overuse also represents waste of resources, and also represents environmental harms that are being incurred for no benefit to patients – but it is also the case that economic evaluation in health care appears to have struggled with identifying or dealing effectively with this phenomenon (Hensher et al., 2017). One particular driver of overdiagnosis and overtreatment is the tendency towards “indication creep”, where interventions are prescribed to more and more patients with ever less severe indications, often seeing what were initially therapeutic interventions eventually become used to “prevent” illness in asymptomatic patients (Welch et al., 2011; Djulbegovic and Paul, 2011). From an environmental perspective, indication creep and prevention creep may pose particular risks – the scale of the increase in treatment seen might be very large (for example, in the case of statins or anti-hypertensives); this will not only have the potential to increase GHG emissions, but may greatly increase pharmaceutical pollution by particular compounds. HTA understandably has great difficulty dealing with such risks of expansion prospectively, because – at the time an HTA is undertaken – the interventions involved are new and probably earmarked for use in more limited indications than might be the case some years after adoption. However, better attention to the scale and risks of indication creep in economic evaluation through modelling could yield benefits both health and environmental outcomes and decision-making. 11. Conclusion - Moving forwards The very earliest economists, such as the French physiocrats, and subsequently Adam Smith and Thomas Malthus, advocated an economic naturalism which was deeply concerned with the interrelationship between the economy and its environmental constraints (Jonsson, 2010) – a concern which increasingly fell away during the nineteenth century as concepts of market exchange and the “marginal revolution” came to dominate economics (Schabas, 2005). The founder of the physiocratic school, François Quesnay, was a surgeon (Schabas, 2005). There might therefore be a pleasing historical symmetry in health systems and health professionals re-embracing an ecological perspective on the economics of health care. This paper has presented a range of evidence on the nature and scale of environmental harms accruing from health care systems. Using perspectives from environmental, ecological and health economics it has considered the arguments in favour of incorporating the environmental impacts of health care into health economic evaluation. In particular, it has argued that the fundamental argument for internalising the costs of negative externalities provides a powerful case in favour of doing so, and that this plausibly overrides counter-arguments from the extra-welfarist perspective. The precautionary need for health systems to “price in” the risk of future policy action on these 9

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Fig. 1. A proportionate process for assessing material environmental impacts.

incorporation into economic evaluation – with the exception of antimicrobial resistance. A concerted program of research on better incorporating all aspects of AMR into the economic evaluation of health care is an urgent priority (essentially on how AMR will impact on other health interventions, rather than purely on the economic evaluation of antibiotic or antimicrobial agents themselves); environmental pollution and AMR is very much an important element of such a program. Finally, better approaches to handling overuse will be an important adjunct to considering the environmental and the economic costs of health care; developing a stronger understanding of the risks of overuse inherent in emerging areas such as genomics and precision medicine might provide significant insights on new frontiers for potential harms to both human and environmental health.

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