###### Abstract

The unsustainable take-make-dispose linear economy prevalent in healthcare
contributes 4.4% to global Greenhouse Gas emissions. A popular but not yet
widely-embraced solution is to remanufacture common single-use medical devices
like electrophysiology catheters, significantly extending their lifetimes by
enabling a circular life cycle. To support the adoption of catheter
remanufacturing, we propose a comprehensive emission framework and carry out a
holistic evaluation of virgin manufactured and remanufactured carbon emissions
with Life Cycle Analysis (LCA). We followed ISO modelling standards and NHS
reporting guidelines to ensure industry relevance. We conclude that
remanufacturing may lead to a reduction of up to 60% per turn ($-$1.92 kg
CO2eq, burden-free) and 57% per life ($-$1.87 kg CO2eq, burdened). Our
extensive sensitivity analysis and industry-informed buy-back scheme
simulation revealed long-term emission reductions of up to 48% per
remanufactured catheter life ($-$1.73 kg CO2eq). Our comprehensive results
encourage the adoption of electrophysiology catheter remanufacturing, and
highlight the importance of estimating long-term emissions in addition to
traditional emission metrics.

###### keywords:

medical remanufacturing; single-use devices; life cycle analysis; greenhouse
gas emissions; carbon footprint

1 1 0 Academic Editor: Anna Trubetskaya https://doi.org/ Assessing Long-Term
Medical Remanufacturing Emissions with Life Cycle Analysis Assessing Long-Term
Medical Remanufacturing Emissions with Life Cycle Analysis Julia A. Meister ,
Jack Sharp, Yan Wang * and Khuong An Nguyen Julia A. Meister, Jack Sharp, Yan
Wang and Khuong An Nguyen Meister, J.A.; Sharp, J.; Wang, Y.; Nguyen, K.A.
Correspondence<EMAIL_ADDRESS>
##  1 Introduction

Global healthcare services contribute an enormous 4.4% to the world’s
Greenhouse Gas emissions, enough to place it fifth in the country carbon
footprint ranking just after China, USA, India, and Russia Karliner et al.
(2019). A large portion of these emissions comes from waste processes. For
example, 590,000 tonnes of healthcare waste are produced annually in England
alone, creating significant environmental impacts and a financial cost of over
£700 m Zils et al. (2022). In 2020, the NHS became the world’s first health
system committed to a legally binding net zero emissions target UK Public
General Acts (2022), recognising and solidifying the importance of reducing
carbon emissions in healthcare.

The NHS Net Zero plan and similar global initiatives acknowledge that the
current take-make-dispose linear economy marked with single-use devices (SUDs)
is a significant contributor to climate impact England and Improvement (2020).
Fortunately, there are promising opportunities for improvement. A circular
economy approach to retain value through reuse, remanufacturing, and recycling
reduces premature device disposal and may lead to large emission and financial
savings Van Boerdonk et al. (2021); Cole et al. (2018); Guzzo et al. (2020).
However, remanufacturing comes with considerable challenges, as regulations
understandably require that SUD medical devices are ‘reset’ before clearance
for reuse (i.e., returned to a state substantially equivalent to a new device)
MHRA (2016, 2021).

Because of the stringent healthcare requirements, the medical remanufacturing
process requires a series of resource-heavy steps (e.g., cleaning,
sterilisation, testing) Schulte et al. (2021). Therefore, careful
consideration of the environmental impacts is required to ensure that it would
indeed reduce emissions compared to producing a new device. To support
decisions regarding linear versus circular procurement strategies, Life Cycle
Analysis (LCA) is often employed to systematically assess the environmental
impacts Liu et al. (2022). To ensure reliable results, comprehensive industry
standards have been developed in recent years (e.g., ISO standards iso (2006)
and NHS reporting guidelines Penny et al. (2012); Standard (2013)).

For remanufacturing to become a widely accepted practice, a collaboration
between industry, legislation, and healthcare institutions is necessary.
Previous studies have shown that successful remanufacturing is driven by
engagement and support from all participating actors, who are largely
motivated by triple bottom line benefits: profit, people, and planet Vadoudi
et al. (2022); Jensen et al. (2019). With that in mind, in this article, we
focus on evaluating the long-term emission savings of remanufactured
electrophysiology catheters. They are a promising candidate for
remanufacturing on a large scale because they have the potential for
significant financial savings (up to £1.7 m annually in the UK Leung et al.
(2019)), physician motivation is high (62% in 42 EU-based healthcare centres
Boussuge-Roze et al. (2022)), and remanufacturing is promising (40% of
ablation procedure emissions come from catheters Ditac et al. (2022)).

In this article, we explore three research questions related to a circular
remanufacturing approach for electrophysiology catheters:

  1. (i)

Can we validate the EP catheter remanufacturing results achieved by the
Fraunhofer case study Schulte et al. (2021)? (Section 4.1)

  2. (ii)

To what extent do key life cycle parameters affect the overall emission
results? (Section 4.2)

  3. (iii)

How can we incorporate a realistic, industry-informed circular use of
catheters to evaluate long-term emission savings? (Section 4.3)

### Contribution

The novelty of our work is the comprehensive and contextualised analysis of
Life Cycle Analysis (LCA) emissions of medical single-use electrophysiology
catheters, including the proposal of a long-term emission metric. Following on
from the research questions laid out above, we identify three main objectives
that this article addresses:

  1. (i)

_To validate a previous case study on the environmental emissions of
electrophysiology catheter remanufacturing_ Schulte et al. (2021) by the
prestigious Fraunhofer Institute.
We have developed a sophisticated, industry-informed Life Cycle Analysis model
with the open source openLCA software Ciroth et al. (2019) for both virgin
manufactured and remanufactured catheters (Section 3).

  2. (ii)

_To perform a sensitivity analysis of key life cycle parameters, showcasing
the magnitude of impact that model uncertainty may have on the total emission
results_.
After carrying out a holistic evaluation of virgin and remanufactured catheter
emissions, we analysed the impact of three key circular economy life
parameters: the remanufacturing location, the catheter rejection rate, and the
number of remanufacturing turns (Section 4).

  3. (iii)

_To propose a novel framework to assess the realistic, long-term emissions of
adopting a circular economy approach with remanufactured medical devices._
Our proposed framework models an industry-informed buy-back scheme to evaluate
long-term remanufacturing emissions (Section 4.3). We interpret the results in
a healthcare context, taking industry stances and existing literature into
account (Sections 5 and 6).

##  2 Methodology

As discussed in detail in Section 1, the purpose of this study is to develop a
novel emission framework to assess the realistic, long-term emissions of a
circular medical device economy. To evaluate our approach, we test the
proposed framework on a use case of remanufactured single-use
electrophysiology catheters and compare our results against a state-of-the-art
emissions analysis in the literature. To estimate the emissions of a single
medical device, we use Life Cycle Analysis (LCA) modelling, a systematic tool
to analyse a product’s environmental impacts over its entire life cycle
Kløverpris (2018). This makes our framework device-agnostic, and the
comprehensive analysis of single-use catheter remanufacturing may be extended
to other medical devices in the future. A flowchart of our methodology is
presented in Figure 1.

Figure 1: _Methodology flowchart._ Our proposed framework extends existing
industry standards to ensure that it may be seamlessly adopted by industry
practitioners. Therefore, ISO regulations 14040 iso (2006) and NHS emission
reporting standards Penny et al. (2012); Standard (2013) have significantly
influenced our methodology, LCA models, and result reports.

To ensure that our comprehensive emission analysis framework maintains a high
standard and may be seamlessly adopted by the industry for climate impact
analysis, we incorporate widely-accepted industry guidelines. The most
impactful LCA standards are ISO 14040 iso (2006) and NHS regulations Penny et
al. (2012); Standard (2013). More details are given in Sections 2.1.

The following sections discuss the methodology of data collection, LCA
modelling, and emission metrics in more detail.

###  2.1 Life Cycle Analysis Methodology

In this article, we carry out a comparative analysis of a virgin manufactured
and a remanufactured electrophysiology catheter’s climate impact. We use Life
Cycle Analysis (LCA) modelling to assess a single product’s emissions over the
course of its life. LCA systematically quantifies the climate impact of each
material and waste input and output. Subsequently, the LCA results are used as
the input to our proposed emission framework, which contextualises the
emission savings by calculating the realistic, long-term climate impacts of a
circular catheter economy. In this section, we present a robust methodology
for a comparative LCA. All models and impact calculations were carried out in
_openLCA_ version 1.10.3, an open-source LCA software Ciroth et al. (2019).

Our LCA modelling approach was heavily influenced by industry regulations. In
particular, we incorporated ISO 14040 iso (2006) guidelines. Additionally, NHS
England has published numerous sophisticated LCA reporting and modelling
standards Penny et al. (2012); Standard (2013) which were taken into account.
These standards are highly significant because they encode the unified
principles of a thorough LCA impact analysis, define relevant terms, and
describe best practices. The benefit of incorporating these guidelines is that
they are defined on an international and national level, respectively, and
therefore ensure that the LCA modelling is of high quality and comparable
between studies.

ISO prescribes four essential and interconnected steps for LCAs (also
visualised in Figure 1): Goal and Scope definition (Section 2), Inventory
analysis (Section 3), Impact assessment (Section 4), and Results
interpretation (Sections 4 and 5). In contrast, the NHS guidelines are
particularly relevant for the emission analysis of medical devices. They give
detailed rubrics for the quantitative life cycle materials that should be
included in the LCA (see Table 1), and the qualitative assessment of LCA data
quality (see Section 2.3).

Following the guidelines discussed above, we take the _cradle-to-grave_
modelling approach to measure the impact of a catheter over its entire life
Botejara-Antúnez et al. (2022). For a virgin, newly manufactured catheter,
this means from the production of the raw resources (cradle) to incineration
after one use (grave). For a remanufactured catheter, we measure emissions
from the pickup of a used catheter, e.g., at a hospital, to when it has been
reused after a successful remanufacturing cycle (grave). The _system boundary_
describes which attributable and non-attributable processes are included in
the emission calculations. We follow the quantitative material input
guidelines for medical devices as described in the NHS GHG accounting guidance
Penny et al. (2012). The list of included and excluded material flows is given
in Table 1. Details of the individual life stages and material inputs are
described in Section 3.

Table 1: _Quantitative rubric of the relevant material inputs and outputs for medical device LCA models. Taken from the NHS guideline for accounting and reporting medical device life cycles Standard (2013)_. Included Processes | Excluded Processes
---|---
Attributable Processes |  Non-Attributable Processes |  Attributable & Non-Attrib.
Production, processing and transport of raw materials. |  Production and distribution of energy/water/chemicals for sterilisation of reusable devices. |  Transport of staff involved in delivery, maintenance, refurbishment and repair.
Manufacture, sterilisation, packing, storage and distribution of the device. |  Production and distribution of consumables required for the operation of a medical device. |  Transport of patients to receive treatment.
Production and distribution of energy, water and materials consumed by the medical device during operation. |  Sterilisation and cleaning chemicals. |  General hospital/clinic/home infrastructure to support use of the medical device.
Production of spare parts/materials, and energy required for refurbishment and repair of devices. |  Refrigerant leakage associated with product manufacturing. |  Software to run medical devices.
Waste management activities at end-of-life, including transportation. |  |  Ancillary products and equipment, e.g., protective clothing.

For a meaningful comparison between one virgin and one remanufactured
catheter’s life, we choose the _cut-off system model_. Consequently, emissions
from waste treatment after the first life are attributed to the producer
Baustert et al. (2022). In other words, the used virgin catheters are burden-
free for the remanufacturing process.

Finally, we forgo _normalisation_ and _weighting_ for the final LCA emission
calculations. These techniques may be used to aggregate impact effects and
evaluate the results relative to reference information Sánchez-Barroso et al.
(2021), while there are benefits to such techniques, they are marked as
optional in LCA ISO guidance Borglin et al. (2021) due to widespread criticism
of their usefulness. We skip these steps to avoid inadvertently introducing
bias through the choice of reference information and to maintain
interpretability Pizzol et al. (2017).

###  2.2 System and Unit-Level Assumptions

The more detailed, expansive, and specific the underlying process data is, the
more accurate and realistic a Life Cycle Analysis (LCA) model will be
Salemdeeb et al. (2021). However, in the interest of time and cost-
effectiveness, most LCA regulations acknowledge a necessary balance between
model exactness and simplicity iso (2006, 2006); Penny et al. (2012); Standard
(2013), while defining universally effective simplification methods is still
an open problem, Gradin and Björklund (2021) suggests that meaningful LCA
analysis should include a detailed description of any assumptions built into
the model. To increase the interpretability of our results, the following list
summarises the system-level assumptions we made.

  1. (i)

Catheter producers and remanufacturers follow a Just-in-Time (JIT) inventory
management system. Therefore, catheters do not need to be stored, and there
are no emissions tied to the running and maintenance of a warehouse.

  2. (ii)

Since OEMs produce many virgin device models, we assume that our generalised
virgin device is representative of them. This position is supported by our
industry collaborators.

  3. (iii)

We assume that the modelled virgin single-use device is eligible for
remanufacturing.

  4. (iv)

We assume that all catheter production steps (e.g., production, assembly,
packaging) are performed in the same manufacturing facility and, therefore,
transportation of individual components is not required. Equivalently, all
remanufacturing steps (e.g., disassembly, cleaning, sterilisation) are
performed in the same remanufacturing facility.

  5. (v)

Due to concern over the potential contamination of used medical equipment, we
assume that virgin and remanufactured end-of-life devices are disposed of by
incineration (e.g., rather than recycled).

  6. (vi)

We assume that used catheters arriving at a remanufacturing facility are fully
functional and do not require replacement components.

  7. (vii)

We assume that chips embedded in catheters are not locked by the OEM after
first use and therefore do not need to be unlocked during remanufacturing.

We also make the following unit-level assumptions. Concrete details are given
in the description of relevant life cycle stages in Section 3 for both virgin
and remanufactured single-use devices.

  1. (i)

In cases where proprietary component plastics are not available in the
Ecoinvent dataset, we assume that replacing these with plastics that have
similar production characteristics (most importantly, melting point) will have
a similar overall climate impact.

  2. (ii)

We assume that some life cycle processes are carried out manually, and
therefore do not include material inputs or outputs for those stages.

  3. (iii)

We assume that the virgin and remanufactured catheters’ packaging and use
stages are the same.

  4. (iv)

We assume that ready-to-use catheters (virgin and remanufactured) are packaged
manually.

  5. (v)

We assume that ready-to-use catheters do not require regular maintenance
because they are single-use devices.

  6. (vi)

We assume that the average use duration of a catheter in surgery is 1 h,
supported by primary data from AMDR.

  7. (vii)

We assume that the waste-disposal facility is in the vicinity of the user, and
therefore exclude transportation to the incineration site.

Our system and unit-level assumptions may lead to slightly conservative
emissions. We take this into account with a sensitivity analysis in Section
4.2 and an in-depth discussion of our results in Section 5.

###  2.3 Data Sources and Quality Assessment

Life Cycle Analysis (LCA) models are made up of foreground and background
data. Foreground data is specific to the product system that is modelled,
while background data gives the context of the wider economic and
technological systems Steubing and de Koning (2021). To achieve a realistic
representation of the product systems, we collected primary data where
possible and filled in gaps from secondary sources. The following data sources
were consulted:

  1. (i)

_Primary foreground sources._ NHS England and USA-based medical device
remanufacturers AMDR and Innovative Health provided primary process activity
data from 2021.
This data focused on life cycle statistics influenced by actors across the
single-use catheter’s value chain. In particular, parameters such as the
remanufacturing collection, rejection, and success rates. Additionally, our
collaborators validated the secondary material and process data for the
catheter components and life cycle processes.

  2. (ii)

_Secondary foreground sources._ A 2021 case study Schulte et al. (2021) on the
life cycle impacts of electrophysiology catheter remanufacturing conducted by
the prestigious Fraunhofer Institute for Environmental, Safety and Energy
Technology was the source of secondary process activity.
The study provides a detailed bill of materials of the single-use catheter,
provided by the Germany-based medical remanufacturer Vanguard AG. Some
simplifications were made, including neglecting a filler of polyurethane in
the catheter curvature and loop because details about the concentration (and
therefore mass) were unknown. However, the authors suggest that this did not
significantly influence the total emissions, as the curvature and loop
represent only 0.7% of the catheter’s total weight. Similarly, when
proprietary component materials were not available in the background dataset,
the study replaced them with possible preliminary products (e.g., for the
catheter shaft). The article reports that the recorded remanufacturing
processes are in full compliance with the specifications of the original
product and with the EU Medical Device Directive 93/42/EEC.

  3. (iii)

_Background data sources_. The established industry-standard Ecoinvent v3.8
dataset Wernet et al. (2016) provided background data and emission factors for
the product processes.
Data points were collected between 2006 and 2011. Ecoinvent process details
are given for each material flow data point when discussing the virgin and
remanufactured catheter Life Cycle Inventory (LCI) in Section 3.

Since the quality of a Life Cycle Impact Assessment (LCIA) is directly
correlated with the quality of the product system’s underlying data Edelen and
Ingwersen (2018), we report the data quality for each input and output flow in
Section 3. Following the NHS guideline for life cycle reporting Penny et al.
(2012) we used an adjusted qualitative data quality appraisal technique (Table
2).

Furthermore, data precision is key in LCIAs, as impacts may be highly
sensitive to even minor changes in a range of factors Schulte et al. (2021).
Where details about process region, production details, and producers were
reported, they were included in the models. Where specific information was
missing or inconclusive, we used relevant alternatives to improve data quality
following best practices. Details are provided as part of the LCI in Section 3
for all affected material flows and life cycle stages. Improvement methods
included:

  1. (i)

When data ranges were given, we calculated average values.

  2. (ii)

When material producer information was not given, we selected producers from
regions with similar production conditions.

  3. (iii)

Proprietary plastics that were not represented in the Ecoinvent Wernet et al.
(2016) dataset were replaced with alternatives. When selecting the best
alternative, the focus was on matching characteristics relevant to plastic
production, as plastic processing has the highest environmental impacts
throughout a plastic’s life Mannheim (2021).

Table 2: _Qualitative data quality appraisal rubric._ Adjusted from the NHS guideline for accounting and reporting medical device life cycles Standard (2013). Score |  Technology | Age | Geography |  Completeness |  Reliability |  _Note_
---|---|---|---|---|---|---
Very good |  Consistent generation. | <3 years | Same area. |  All relevant sites. |  Verified data based on measurements. |  _Primary data from AMDR, Innovative Health, and NHS England._
Good |  Similar generation. | 3–6 years | Similar area. |  More than 50% of sites for an adequate time. |  Non-verified data based on measurements. |  _Data taken directly from the Fraunhofer case study._
Fair |  Different generation. | 6–10 years | Different areas. |  Less than 50% of sites for an adequate time. |  Non-verified data partly based on assumptions or a qualified estimate. |  _Data adapted from the Fraunhofer case study (e.g., due to data availability)._
Poor |  Unknown generation. | >10 years | Unknown area. |  Less than 50% of sites for a shorter time. |  Non-qualified estimate. |  _Not applicable._

###  2.4 Sensitivity Analysis Methods

As discussed in Section 2, Life Cycle Analysis (LCA) results may be sensitive
to even minor changes in the input data. Consequently, sensitivity analysis is
a valuable tool to assess uncertainty in the environmental impact results
McAlister et al. (2021). In collaboration with NHS England and industry
remanufacturers AMDR and Innovative Health, three high-impact remanufacturing
parameters were identified for analysis:

  1. (i)

The _remanufacturing location_ $L$ dictates the transportation mode and route
of the used and remanufactured catheters between the user and remanufacturing
facilities (studied $L\in\\{$DE, UK, USA$\\}$).

  2. (ii)

The _rejection rate_ $R$ describes the percentage of used catheters discarded
during remanufacturing due to their sub-par quality (studied $0\%\leq R\leq
70\%$).

  3. (iii)

The _number of turns_ $N$ identifies the number of times a catheter may be
used overall. For example, a catheter with $N=3$ turns is used once as a
virgin catheter and twice as a remanufactured catheter before reaching the end
of its life (studied $1\leq N\leq 5$).

To assess the importance of the above life cycle parameters, we carried out a
comprehensive _univariate sensitivity analysis_ in Sections 4.2.1–4.2.3,
varying one of the three parameters at a time. After analysing the individual
magnitude of LCA result changes, we evaluated the combined effect of the
parameter changes in three representative remanufacturing scenarios. The
_multivariate sensitivity analysis_ results are presented in Section 4.2.4.

  1. (i)

_Good scenario_ : Ideal scenario ($L=$UK, $R=0$%, $N=5$).

  2. (ii)

_Average scenario_ : Approximately current ($L=$DE, $R=15$%, $N=4$).

  3. (iii)

_Bad scenario_ : Approximately following Schulte et al. (2021) ($L=$USA,
$R=50$%, $N=3$).

###  2.5 Emission Metrics

We chose _climate impact_ as the primary indicator of a catheter’s effects on
the environment. Furthermore, known as Greenhouse Gas (GHG) emissions or
carbon footprint, climate impact is central to many widely-circulated
technical reports and regulations (e.g., the legally binding NHS net zero
commitment England and Improvement (2020), EU Commissions Climate Target Plan
EU Commission (2020), and the UN’s Paris Agreement Agreement (2015), to name a
few). Consequently, the term is familiar to a global audience across the
public, industry, and political spectrum.

To quantify a catheter’s climate impact, we followed the Environmental
Footprint (EF) 3.0 methodology, a European Commission initiative to
standardise the calculation of emissions during a product’s life cycle EU
Commission (2013). The unit is kg CO2eq (spoken “carbon dioxide equivalent”),
which allows different GHGs to be reported as one value by multiplying their
weight with their Global Warming Potential (GWP) Brander and Davis (2012). For
this article, the functional unit of analysis is defined as the production and
potential disposal of one catheter (virgin or remanufactured) after its use in
a 1-hour procedure.

An inherent challenge with circular life cycles such as catheter
remanufacturing is how to attribute the total emissions across individual
turns. To address this, we follow the NHS GHG reporting guidelines Penny et
al. (2012); Standard (2013) on how to calculate per life and per turn
emissions. We report the following values in Section 4:

  1. (i)

Burden-free per turn emissions $E^{f}_{v}$ for virgin manufactured and
$E^{f}_{r}$ for remanufactured catheters;

  2. (ii)

Burdened per turn catheter emissions $E^{b}_{perTurn}$;

  3. (iii)

Furthermore, burdened per life catheter emissions $E^{b}_{perLife}$.

Equations (1) and (2) define the total emissions of one virgin catheter
$E^{f}_{v}$ and one remanufactured catheter $E^{f}_{r}$ as the sum of all
input emissions $e_{i}$ and output emissions $e_{o}$. The superscript $f$
indicates that the emission results are _burden-free_ ; No previous lives are
accounted for. For example, the remanufactured catheter’s emissions
$E^{f}_{r}$ do not include emissions from its first virgin life.

$\displaystyle E^{f}_{v}$ $\displaystyle=\sum e_{i}+\sum e_{o}$ (1)
$\displaystyle E^{f}_{r}$ $\displaystyle=\sum e_{i}+\sum e_{o}$ (2)

In contrast, results marked with the superscript $b$ include the emissions
from previous lives, i.e., the emissions are _burdened_. These values are
dependent on the _number of turns_ $N$, which describes the total number of
uses before a catheter reaches the end of its life and is discarded. For
example, a catheter with $N=3$ turns is used exactly three times: once as a
virgin catheter and twice as a remanufactured catheter. The formula for a
catheter’s emissions across its whole life $E^{b}_{perLife}$ is given in
Equation (3).

$\displaystyle E^{b}_{perLife}=E^{f}_{v}+(N-1)\cdot E^{f}_{r}$ (3)

For an equivalent turn comparison between a virgin catheter’s emissions
$E^{f}_{v}$ and a burdened remanufactured catheter’s emissions, we may
calculate the relative per turn emissions $E^{b}_{perTurn}$ with Equation (4).

$\displaystyle E^{b}_{perTurn}=\frac{1}{N}E^{b}_{perLife}$ (4)

###  2.6 Proposed Long-Term Emission Metrics

Industrial medical device remanufacturing is often carried out as a third-
party service, and a common approach is to treat it as a buy-back scheme.
Evaluating the long-term emissions, therefore, requires estimating the
necessary number of units (i.e., catheter uses) required for a period of time,
and purchasing an initial injection of virgin devices to be remanufactured
until either the quality fails, or the maximum number of turns is reached.

To simulate the emission savings of a long-term buy-back scheme compared to
purchasing only new virgin catheters, we must first calculate the necessary
number of new catheters to prime the system. Given details of the
remanufacturing process, we can solve for the initial number of virgin
catheters $C$ needed to achieve $U$ total catheter uses in a buy-back scheme:

$\displaystyle U=\sum^{N}_{n=1}C\cdot(1-R)^{n-1}$ (5)

$C$ is dependent on the cleared number of turns $N$ (where $n=1$ is a
catheter’s first virgin life) and the catheter rejection rate $R$. Assuming
that all used catheters are successfully collected and returned to the
remanufacturer, we may calculate the initial injection of new devices.
Similarly to $E^{b}_{perLife}$ and $E^{b}_{perTurn}$ in Equations (3) and (4),
we may define the long-term total $E^{l}_{perScheme}$ and per turn
$E^{l}_{perTurn}$ emissions of the buy-back scheme.

$\displaystyle E^{l}_{perScheme}=C\cdot E_{v}^{f}+(U-C)\cdot E_{r}^{f}$ (6)
$\displaystyle E^{l}_{perTurn}=\frac{1}{U}\cdot E^{l}_{perLife}$ (7)

##  3 Single-Use Catheter Life Cycles and Material Flows

Before analysing the environmental impacts, we provide a detailed Life Cycle
Inventory (LCI). This illustrates the virgin manufactured and remanufactured
catheter life cycle stages with a comprehensive description of material inputs
and outputs. The start and end life cycle stages (i.e., cradle and grave) are
dictated by the _functional unit_. A functional unit is key in LCAs, as it
defines one unit of the product or service being evaluated DeMarco and Fortier
(2021). In this paper, we determine it as the production, use (1-h long
procedure), and disposal of one catheter. By choosing equivalent functional
units for both the virgin and remanufactured scenarios, we may confidently and
intuitively compare their emission results (even though catheter ‘production’
includes different processes) Furberg et al. (2022).

To decide which inputs and outputs are contained in the system boundary, we
use the quantitative rubric published by NHS guidelines (see Section 2.3).
Additionally, we outline the quantity, source, and data quality of each data
point in this section, following the NHS guidance for life cycle reporting
Standard (2013).

Since component materials and processes may vary significantly based on the
catheter model, Original Equipment Manufacturer (OEM), and remanufacturer, we
selected representative product systems for the virgin and remanufactured life
cycles. The inputs and outputs were largely informed by a 2021 EP catheter
case study Schulte et al. (2021) which was supplemented and updated with our
primary data from NHS England and USA-based medical device remanufacturers
AMDR and Innovative Health (see Section 2). The primary data additionally
influenced our catheter use and remanufacturing locations, which were set in
the UK and the USA, respectively. To account for the possible bias introduced
to our emission values by the chosen representation, we include a sensitivity
analysis of key process parameters in our results analysis (Section 4).

###  3.1 Virgin Manufactured Catheter

A catheter’s linear life cycle was tracked from the production from raw
materials in the USA (cradle) to its waste disposal after use in the UK
(grave), as shown in Figure 2. Because we selected the cut-off model (see
Section 2.1), any energy recovered after incineration was not credited to the
catheter’s life cycle. Table 3 presents an overview of the process steps, and
subsequent material flows per life stage.

Figure 2: _Virgin catheter product system._ The life stages are arranged in a
linear life cycle from cradle-to-grave, which here is defined as production to
incineration. We follow the cut-off system that is marked by the square system
boundary. Table 3: _Virgin life stages and materials_. The materials are based
on Schulte et al. (2021) and supplemented with primary data from our
collaborators, medical device remanufacturers AMDR and Innovative Health. The
data quality was assessed with the rubric in Table 2, and the region marks the
Ecoinvent production geography.

Stage/Material | Quantity | Source | Quality | Time Range | Region |  Description
---|---|---|---|---|---|---
Production |  |  |  |  |  |  Component production from raw resources and assembly.
polyamide |  $3.20\times 10^{3}$ kg | Adjusted Schulte et al. (2021) | Fair | 2011–2021 | GLO |  Pre-product for the shaft.
ethylene glycol |  $1.25\times 10^{3}$ kg | Adjusted Schulte et al. (2021) | Fair | 2011–2021 | RER |  Pre-product for the shaft.
polyethylene LD |  $3.00\times 10^{4}$ kg | Schulte et al. (2021) | Good | 2011–2021 | GLO |  Shaft stiffener.
polysulfone | 0.10810 kg | Adjusted Schulte et al. (2021) | Fair | 2012–2021 | GLO |  Plug and handle.
polyurethane |  $0.80\times 10^{3}$ kg | Schulte et al. (2021) | Good | 2018–2021 | RER |  Curvature and loop.
electricity | 0.026 kWh | Adjusted Table 4 | Fair | 2014-2021 | US-WECC |  Component assembly.
Sterilisation |  |  |  |  |  |  Gas sterilisation.
carbon dioxide |  $2.82\times 10^{3}$ kg | Schulte et al. (2021) | Good | 2011–2021 | RER |  Sterilisation gas ingredient.
ethylene oxide |  $1.80\times 10^{4}$ kg | Schulte et al. (2021) | Good | 2018–2021 | GLO |  Sterilisation gas ingredient.
electricity | 0.360 kWh | Schulte et al. (2021) | Good | 2014–2021 | US-WECC |  Process electricity.
Packaging |  |  |  |  |  |  Manual packaging.
polyethylene HD |  $2.00\times 10^{2}$ kg | Schulte et al. (2021) | Good | 2011–2021 | GLO |  Primary (sterile) packaging.
carton box |  $1.40\times 10^{1}$ kg | Adjusted Schulte et al. (2021) | Fair | 2011–2021 | GLO |  Secondary packaging.
Transport |  |  |  |  |  |  Transport from manufacturer to user.
container ship | 0.11890 kg | Ports.com1 | Fair | 2007–2021 | GLO |  USA-UK sea route.
$\times$ 18,760 km
lorry | 0.11890 kg | Google maps1 | Fair | 2011–2021 | RER |  UK final distribution.
$\times$ 250 km
Use |  |  |  |  |  |  Materials consumed by device.
electricity | 0.050 kWh | AMDR, IH, Food and Drug Administration (2007) (FDA) | Very Good | 2014–2021 | GB |  1 h of use, 50 watts.
Incineration |  |  |  |  |  |  End-of-life waste disposal.
plastic incineration | 0.11890 kg | Schulte et al. (2021) | Good | 2006–2021 | CH |  Municipal (100%).

1 Accessed on 25 November 2022.

####  3.1.1 Production Stage

The catheter production stage consisted of the raw resource extraction,
component production, and device assembly steps. We assume that all components
were produced in the same facility, which is also where the catheter was
assembled.

A catheter was made up of a plug, handle, curvature, loop, and shaft, and
weighed a total of 118.9 g. Plastic components were modelled following the
case study Schulte et al. (2021), which used a bill of materials provided by
their collaborating remanufacturer, Vanguard AG. We assume that other
materials were excluded because they do not significantly contribute to the
catheter emissions, e.g., by the material cut-off rule presented in Penny et
al. (2012). Several proprietary plastics were not available in the Ecoinvent
v3.8 dataset Wernet et al. (2016) (PEI granulate and PA6). In these cases, we
selected replacement materials that closely matched the manufacturing
properties of the original plastics (polysulfone and polyamide, respectively).
Most importantly, by ensuring a similar melting point, we expect to achieve
high similarity in the overall plastic life cycle impacts on the modelled
catheter. This is because the production process, undertaken at high
temperatures, is one of the most energy and environmental impact-intensive
stages of the material’s life (e.g., melting the plastic, pre-heating moulds
and dies) Mannheim (2021), while our replacements may influence other impact
categories, they will create similar results for GHG emissions, our chosen
climate impact (see Section 2.5).

Once the components were manufactured (electricity and other input emissions
are included in the material flows), electricity was required to assemble them
into a completed catheter. Because this step was excluded in the original
study, we calculated the assembly electricity as half of the electricity used
to assemble and disassemble a used catheter during remanufacturing (see
Section 3.2).

####  3.1.2 Sterilisation and Packaging Stages

Before transportation to the user, all virgin manufactured catheters were
sterilised with ethylene oxide gas. According to Schulte et al. (2021), the
material inputs given in Table 3 were the main identifiable components from a
safety sheet provided to the authors by Vanguard AG, a medical remanufacturer
based in Germany. The data was also supported by AMDR’s primary data. Apart
from the gas materials, electricity was also needed to complete the procedure
(e.g., gas introduction and evacuation from the sterilisation chamber).

We assume that the packaging stage is carried out manually. Therefore, only
the packaging materials are required as input to the model.

####  3.1.3 Transportation Stage

After production, sterilisation, and packaging, the catheters were transported
from the remanufacturer in the USA to an NHS end user in the UK. There were
two transportation stages: A representative 18760km container ship route
between the USA and UK, and a 250km lorry transport for the final distribution
within the UK. The locations were updated from the case study, which used
locations specific to their collaborators (USA and Germany, respectively).

####  3.1.4 Use Stage

A major update in our approach compared to Schulte et al. (2021) is the
inclusion of emissions generated during the use stage. As shown in Table 1,
NHS GHG modelling standards Penny et al. (2012) dictate that materials
consumed by a medical device during the use stage should be included in the
life cycle assessment. Electrophysiology catheters require only electricity to
be operational. Therefore, we included a catheter’s average energy use. The
total amount was calculated from the average length of an electrophysiology
procedure (1-hour length, primary data from AMDR) and the average watts a
catheter draws Food and Drug Administration (2007) (FDA). Because
electrophysiology catheters are single-use devices, they do not need regular
maintenance before being used.

####  3.1.5 Incineration Stage

Medical devices are most commonly incinerated after disposal to reduce
contamination risk. For the end-of-life incineration after one use, we assume
that the waste management facility was in the vicinity of the user, and
therefore exclude transportation to the incineration site.

###  3.2 Remanufactured Catheter

Compared to the virgin catheter, a remanufactured catheter has a circular life
cycle as shown in Figure 3. That starting life stage (cradle) is when a used
catheter is transported from the previous user to the remanufacturer. The life
cycle ends (grave) after a successfully remanufactured catheter is used by a
healthcare provider.

The total weight of a remanufactured catheter is 118.9 g, the same as a virgin
catheter. Table 4 presents an overview of the material flows per life stage.

Figure 3: _Remanufactured catheter product system._ The life stages are
arranged in a circular life cycle from cradle-to-grave, which here is defined
as from the transportation of a used catheter to its re-use after successful
remanufacturing. We follow the cut-off system that is marked by the square
system boundary. Table 4: _Remanufacturing life stages and materials_. The
materials are based on Schulte et al. (2021) and supplemented with primary
data from our collaborators, medical device remanufacturers AMDR and
Innovative Health. The data quality was assessed with the rubric in Table 2
and region marks the Ecoinvent production geography.

Stage/Material | Quantity | Source | Quality | Time Range | Region |  Description
---|---|---|---|---|---|---
Transport $\times 2$ |  |  |  |  |  |  Transport from remanufacturer to user and back.
container ship | 0.11890 kg | Ports.com1 | Fair | 2007–2021 | GLO |  USA-UK sea route.
$\times$ 18,760 km
lorry | 0.11890 kg | Google maps1 | Fair | 2011–2021 | RER |  UK final distribution.
$\times$ 250 km
Reman. |  |  |  |  |  |  Dissassembly, reman., reassembly, and testing.
hydrogen peroxide | 0.03020 kg | Schulte et al. (2021) | Good | 2018–2021 | RER |  Detergent ingredient.
sodium bicarbonate |  $1.46\times 10^{2}$ kg | Schulte et al. (2021) | Good | 2011–2021 | GLO |  Detergent ingredient.
sodium cumensulph. |  $3.50\times 10^{4}$ kg | Schulte et al. (2021) | Good | 2015–2021 | GLO |  Detergent ingredient.
tap water | 7.00000 kg | Schulte et al. (2021) | Good | 2012–2021 | Europe |  Process water.
water, ultrapure | 5.00000 kg | Adjusted Schulte et al. (2021) | Fair | 2009–2021 | CA-QC |  Process water.
electricity | 0.207 kWh | Schulte et al. (2021) | Good | 2014–2021 | US-WECC |  Process electricity.
Incineration |  |  |  |  |  |  End-of-life waste disposal.
plastic incineration | 0.01784 kg | AMDR, IH | Good | 2006–2021 | RoW |  Municipal (15% rejection rate).
Sterilisation |  |  |  |  |  |  Gas sterilisation.
carbon dioxide |  $2.82\times 10^{3}$ kg | Schulte et al. (2021) | Good | 2011–2021 | RER |  Sterilisation gas ingredient.
ethylene oxide |  $1.80\times 10^{4}$ kg | Schulte et al. (2021) | Good | 2018–2021 | RER |  Sterilisation gas ingredient.
electricity | 0.360 kWh | Adjusted Schulte et al. (2021) | Good | 2014–2021 | US-WECC |  Process electricity.
Packaging |  |  |  |  |  |  Manual packaging.
polyethylene HD |  $2.00\times 10^{2}$ kg | Schulte et al. (2021) | Good | 2011–2021 | GLO |  Primary (sterile) packaging.
carton box |  $1.40\times 10^{1}$ kg | Adjusted Schulte et al. (2021) | Fair | 2011–2021 | GLO |  Secondary packaging.
Use |  |  |  |  |  |  Materials consumed by device.
electricity | 0.050 kWh | AMDR, Food and Drug Administration (2007) (FDA) | Very Good | 2014–2021 | GB |  1 h of use, 50 watts.

1 Accessed on 25 November 2022.

####  3.2.1 Transportation Stage

In a significant change from Schulte et al. (2021), we have doubled the
transportation route between the USA and the UK. The case study assumes that
the used catheters and remanufactured catheters are transported in a single
round trip. However, discussions with medical device remanufacturers AMDR and
Innovative Health revealed that this does not reflect current industry
practice. Each transport route has two stages: A representative 18,760 km
container ship route between the USA and UK, and a 250 km lorry transport for
the final distribution within the UK.

####  3.2.2 Remanufacturing Stage

The catheter remanufacturing stage consists of the disassembly, cleaning,
reassembly, and testing steps. We assume that all processes take place in the
same remanufacturing facility, and therefore do not include further
transportation. Additionally, we assume that the electrophysiology catheter’s
software does not have to be maintained. Used catheters that failed quality
control at any point of the process or passed their cleared number of maximum
turns reached their end of life. For simplicity, the modelled remanufacturing
process does not include replacing faulty components.

A significant difference of our model to Schulte et al. (2021) is the
rejection rate. The case study assumes an almost 50% rejection rate. In other
words, only one catheter is successfully reprocessed for every two used
catheters that arrive at the remanufacturing facility. In comparison, medical
device remanufacturers AMDR and Innovative Health confirmed that a 15%
rejection rate more accurately reflects the current state of EP catheter
remanufacturing in 2021.

####  3.2.3 Incineration Stage

As with the virgin catheter, we assume that incineration occurs near the
healthcare provider and therefore exclude transportation to the waste
management facility (see Section 3.1).

####  3.2.4 Sterilisation and Packaging Stages

The gas sterilisation and packaging processes are assumed to be exactly the
same as for a virgin single-use catheter (see Section 3.1.2).

####  3.2.5 Use Stage

According to NHS regulations Standard (2013), medical device remanufacturing
must return a used catheter to its original state to classify it as a
remanufactured single-use device. Consequently, we may assume that the use
stage of a fully remanufactured catheter is the same as that of a virgin
manufactured catheter (see Section 3.1.4).

##  4 Greenhouse Gas Emission Results

This section contains our comparative analysis of virgin manufactured and
remanufactured catheter emissions. All results were generated following the
comprehensive methodology illustrated in Section 2. Wider-context insights and
implications initiated by the results are discussed in Section 5.

The functional unit of analysis is defined as the production and potential
disposal of one catheter after its use in a 1-h procedure. We report the
following values:

  1. (i)

Burden-free per turn emissions $E^{f}_{v}$ for virgin manufactured and
$E^{f}_{r}$ for remanufactured catheters;

  2. (ii)

Burdened per turn catheter emissions $E^{b}_{perTurn}$;

  3. (iii)

Furthermore, burdened per life catheter emissions $E^{b}_{perLife}$.

Readers are referred to Section 2.5 for a more detailed treatment of the
metrics with definitions, equations, and intuitions.

###  4.1 Burden-Free Catheter Emissions

The total climate emissions generated during the production, use, and disposal
of one _virgin catheter_ is $\bm{E^{f}_{v}=1.53}$kg CO2eq (based on the
material inputs shown in Table 3). Figure 4a shows how the total value is
broken down into material categories. For a different perspective, interested
readers are referred to Table 5a for the emissions per life stage and
individual material. As expected, the procurement and manufacturing of plastic
catheter components were responsible for the majority of virgin catheter
emissions, coming in at 58%. Disposing of the waste plastic was also a
significant contributor, covering 18%. In total, around three-quarters of
virgin catheter emissions came from the production and disposal of plastic
components, which implies that remanufacturing may make a consequential dent
in life cycle emissions. The two lowest contributors were gas sterilisation
(0.2%) and, surprisingly, transportation of catheters between the USA-based
manufacturer and the UK-based user (2.4%). We will explore this figure in more
detail as part of the sensitivity analysis in Section 4.2.1.

a

b

Figure 4: _Burden-free catheter results per turn._ Virgin emissions are primarily caused by plastic processing and incineration. In contrast, remanufactured emissions are more evenly distribution across categories. (a) Virgin catheter emissions $E^{f}_{v}$. (b) Remanufactured catheter emissions $E^{f}_{r}$. Table 5: _Greenhouse gas emissions by life stage and material._ Around three-quarters of virgin catheter emissions came form the production and disposal of plastic components. In comparison, remanufacturing emissions were more evenly divided across life stages. (a) Virgin manufactured catheter |  (b) Remanufactured catheter
---|---
Stage/Material | Kg CO2eq | Proportion |  Stage/Material | Kg CO2eq | Proportion
Production |  0.90018 |  58.65% |  Transport $\times$2 |  0.07223 |  11.80%
polyamide | 0.02934 | 1.91% |  container ship | 0.04203 | 6.87%
ethylene glycol | 0.00261 | 0.17% |  lorry | 0.03020 | 4.93%
polyethylene LD | 0.00077 | 0.05% |  Remanufacturing |  0.14603 | 23.85%
polysulfone | 0.85250 | 55.55% |  hydrogen peroxide | 0.03497 | 5.71%
polyurethane | 0.00419 | 0.27% |  sodium bicarbonate | 0.01861 | 3.04%
electricity | 0.01077 | 0.70% |  sodium cumensulph. | 0.00084 | 0.14%
Sterilisation |  0.15171 | 9.89% |  tap water | 0.00232 | 0.38%
carbon dioxide | 0.00229 | 0.15% |  water, ultrapure | 0.00368 | 0.60%
ethylene oxide | 0.00034 | 0.02% |  electricity | 0.08561 | 13.98%
electricity | 0.14908 | 9.72% |  Incineration |  0.09426 | 15.40%
Packaging |  0.15188 |  9.90% |  plastic incineration | 0.09426 | 15.40%
polyethylene HD | 0.04798 | 3.13% |  Sterilisation |  0.15182 |  24.80%
carton box | 0.10390 | 6.77% |  carbon dioxide | 0.00229 | 0.37%
Transport |  0.03612 |  2.35% |  ethylene oxide | 0.00034 | 0.06%
container ship | 0.02102 | 1.37% |  electricity | 0.14919 | 25.24%
lorry | 0.01510 | 0.98% |  Packaging |  0.13201 | 21.57%
USE |  0.01586 |  1.04% |  polyethylene HD | 0.04798 | 7.84%
electricity | 0.01586 | 1.04% |  carton box | 0.08403 | 13.73%
Incineration |  0.27902 | 18.18% |  Use |  0.01586 | 2.59%
plastic incineration | 0.27902 | 18.18% |  electricity | 0.01586 | 2.59%
$\bm{E_{v}^{f}}$ | 1.53477 | 100.00% |  $\bm{E_{r}^{f}}$ | 0.61221 | 100.00%

Turning to a _remanufactured catheter_ , climate emissions totalled
$\bm{E^{f}_{r}=0.61}$kg CO2eq (Note that the used catheter at the start of the
remanufacturing process had no emissions tied to it, as dictated by the cut-
off model we used (see Section 2)). (based on the material inputs shown in
Table 4). Figure 4b illustrates the emission breakdown into categories. For
more detail on the life stage and material emissions, see Table 5b. Compared
to the virgin catheter, emissions were more evenly divided across categories.
Electricity was the highest single contributor (41%), which suggests that the
composition of energy production may be a significant factor when optimising
the remanufacturing process. The lowest climate impact categories were water
(1%) and sterilisation gas (0.4%).

_Comparing a virgin catheter to a remanufactured catheter_ , we found that
remanufacturing reduced climate emissions by 60% per burden-free catheter
($-$1.92 kg CO2eq, Table 6). As expected, the single largest emission saving
came from the omission of plastic processing and component manufacture
($-$1.89 kg CO2eq) with reduced waste processing in second place ($-$1.19 kg
CO2eq). In contrast, the inclusion of cleaning inputs for remanufacturing
(detergent, water, electricity) only marginally increased the emissions by
+0.14 kg CO2eq. A final noteworthy change is that the transportation emissions
were doubled for the remanufactured catheter, since the used catheters had to
be transported to the remanufacturing facility and back to the user. However,
total transportation emissions were still nominal (0.07 kg CO2eq).

Table 6: _Burden-free catheter remanufacturing emission savings._ Our analysis shows that catheter remanufacturing reduces climate emissions by 60%. The results are given in kg CO2eq. Category |  Virgin |  Reman. |  $\Delta$
---|---|---|---
Plastic |  0.889 |  0 |  $-$1.889
Waste |  0.279 |  0.094 |  $-$1.185
Elec. |  0.176 |  0.251 |  +0.075
Packag. |  0.152 |  0.132 |  $-$1.020
Transp. |  0.036 |  0.072 |  +0.036
Deterg. |  0 |  0.054 |  +0.054
Water |  0 |  0.006 |  +0.006
Ster. |  0.003 |  0.003 |  0
$\sum$ |  1.535 |  0.612 |  $-$1.923

###  4.2 Sensitivity Analysis and Burdened Catheter Emissions

In this section, we carry out a comprehensive sensitivity analysis of three
high-impact remanufacturing life cycle parameters:

  1. (i)

The _remanufacturing location_ $L$.

  2. (ii)

The _rejection rate_ $R$.

  3. (iii)

Furthermore, the _number of turns_ $N$.

After examining the magnitude of each key parameter’s individual effect on
emissions (Sections 4.2.1–4.2.3), we contextualise the results by analysing
three representative scenarios (Section 4.2.4). Readers are referred to
Section 2.4 for a detailed description of the methodology and parameters.

####  4.2.1 Remanufacturing Location

Remanufacturing is commonly offered as a third-party service Opresnik and
Taisch (2015). When comparing catheter life cycle emissions, we must consider
both the absolute and relative location of the remanufacturing facility to the
user because both may have wide-ranging effects: from the transport mode and
distance to the origin and composition of the remanufacturing materials and
processes (e.g., electricity generation, water processing, waste treatment).

Figure 5 shows the burden-free emission results $E^{f}_{r}$ for one catheter
remanufactured in three different locations: Germany (0.77 kg CO2eq), USA
(0.61 kg CO2eq), and UK (0.53 kg CO2eq). In each scenario, the remanufactured
catheter was used in the UK. _Electricity_ showed a noticeable emissions
increase when remanufacturing took place in Germany (+0.06 kg CO2eq),
potentially because energy generation is more reliant on coal combustion than
other countries Bruninx et al. (2013). Conversely, UK remanufacturing reduced
electricity emissions by $-$1.6 kg CO2eq. Since electricity was the highest
emission category, the composition of energy production technologies should be
taken into consideration to optimise the remanufacturing process.

Figure 5: _Sensitivity analysis of the remanufacturing location $L$._ Burden-
free emission results $E^{f}_{r}$ show that the location may influence non-
transport categories because the regionality of their material inputs has
changed.

Surprisingly, the _transportation_ of used and remanufactured catheters
between Germany and the UK had the highest climate impact as well (0.16 kg
CO2eq), over USA-UK transportation (0.07 kg CO2eq). This may be partially due
to the different transport modes. Our results suggest that in terms of their
climate impact, long-distance routes using primarily container ship
transportation (USA-UK, 19,000 km) may be more efficient than shorter-distance
routes using primarily road transportation (DE-UK, 1400 km). Interestingly,
the total transport distance may not necessarily indicate the emission
efficiency of a remanufacturing location.

Given its significance to the majority of remanufacturing materials and
processes, it is unexpected to see multiple categories with only minor changes
between the burden-free emissions at three different locations. We hypothesise
that this is most likely due to two reasons:

  1. (i)

The materials (e.g., for cleaning and sterilisation) were in small quantities,
and therefore the absolute regional differences were minimal,

  2. (ii)

And/or Ecoinvent v3.8 Wernet et al. (2016) had only broad regional categories
that included multiple remanufacturing locations such as the ‘global’ region
for waste treatment, packaging, and water.

For those categories, more detailed and regionally distinguished data flows
could be used in future for more precise emission calculations.

Even with the stated regionality limitations, our results highlight the
environmental impact a catheter user may exert through the careful selection
of a remanufacturer based on their facility’s location. Our results suggest
that the location of remanufacturing may not just have a significant effect on
the emissions caused by the transportation, but also on the climate impact of
the remanufacturing process itself.

####  4.2.2 Rejection Rate

The rejection rate describes the proportion of used catheters that are
discarded due to sub-par quality for every successfully remanufactured
catheter. Many factors, including the catheter model and collection processes,
may influence the quality rejection rate. For simplicity, we assume that low-
quality catheters are rejected on arrival at the remanufacturing facility
(e.g., because of missing identification or damage during collection).

To illustrate the significant influence of the rejection rate on
remanufacturing emissions, we evaluated a range from 0% (optimal) to 70% in
Figure 6. The virgin catheter emissions are given for reference
($E^{f}_{r}=1.53$kg CO2eq). As the rejection rate increases, the burden-free
remanufactured catheter emissions $E^{f}_{r}$ increased exponentially from
0.52 to 1.18 kg CO2eq. To put that in context relative to a virgin catheter, a
0% rejection rate represents a 66% emission reduction through remanufacturing,
35% represents 56% reduction, and 70% means only a 23% reduction,
respectively.

Figure 6: _Sensitivity analysis of the rejection rate $R$._ Burden-free
remanufacturing emissions $E^{f}_{r}$ increase exponentially as the rejection
rate grows. Since 100% of virgin catheters are discarded after use, their
emissions $E^{f}_{v}$ are not affected.

The increased emission savings were directly caused by a lower quality
rejection rate, which implies that more of the used catheters arriving at the
remanufacturing facility could be successfully reprocessed. In turn, this led
to less used catheters reaching their end of life due to a low quality. The
climate impact reduction primarily stemmed from the reduced waste incineration
per reprocessed catheter.

####  4.2.3 Number of Turns

To ensure that the functionality of remanufactured catheters is substantially
equivalent to a virgin catheter, each catheter model must be cleared for a
certain number of turns by regulators before they may be remanufactured.
According to medical device remanufacturer Innovative Health, EP catheters are
relatively fragile compared to other remanufactured devices and typically
cannot withstand more than 1–5 turns. Consequently, we evaluated the burdened
emissions $E^{b}_{perLife}$ of remanufactured catheters for that range and
contrasted the results against the total emissions of using a new virgin
catheter for each turn in Figure 7.

Both scenarios started at $E^{f}_{v}=1.53$kg CO2eq since a remanufactured
catheter’s first life is as a virgin catheter. As the number of turns
increased, so did the improved savings of remanufactured over virgin
catheters. In the virgin scenario, each ‘turn’ required the production, use,
and disposal of a brand-new catheter, which meant a linear growth of +1.53 kg
CO2eq. In contrast, remanufacturing the same catheter repeatedly had a
significantly shallower growth of +0.61 kg CO2eq per turn. This represents a
60% reduction per turn since a remanufactured catheter only emits 40% of
emissions compared to a virgin catheter.

Our results highlight that remanufacturing emission savings increase
significantly with the number of viable turns. After two turns,
$E^{b}_{perLife}$ is decreased by 30% compared to two virgin catheters ($-$0.9
kg CO2eq), 40% after three turns ($-$1.8 kg CO2eq), and 48% after five turns
($-$3.7 kg CO2eq). To put it in a different perspective, a remanufactured
catheter used five times has lower climate emissions than three virgin
catheters (4 kg CO2eq vs. 4.6 kg CO2eq).

Figure 7: _Sensitivity analysis of the number of turns $N$._ Each
remanufactured catheter has its first life as a virgin catheter with emission
$E^{f}_{v}$. After that, remanufactured burdened per-life emissions
$E^{b}_{perLife}$ increase by $E^{f}_{r}$ per turn.

####  4.2.4 Multivariate Scenarios

Finally, we combine the individually explored parameters into three
representative multivariate scenarios, as shown in Table 7. By analysing these
scenarios in parallel, we may contextualise the univariate sensitivity
analysis results (Sections 4.2.1–4.2.3) and evaluate the possible overall
gains that may be achieved with an improved remanufacturing process.

Table 7: _Multivariate sensitivity analysis scenarios._ High-impact remanufacturing parameters were combined into three scenarios to contextualise emission results: remanufacturing location $L$, used catheter rejection rate $R$, and number of turns $N$. Scenario |  $L$ |  $R$ |  $N$ |  Comments
---|---|---|---|---
Good |  UK |  0% |  5 |  Ideal scenario.
Average |  DE |  15% |  4 |  Approximately current.
Bad |  USA |  50% |  3 |  Approximately following Schulte et al. (2021).

A high-level comparison in Figure 8a revealed that the burden-free climate
emissions of a remanufactured catheter $E^{f}_{r}$ followed the expected
ranking (0.81, 0.73, 0.44 kg CO2eq). The Average scenario improved on the Bad
remanufacturing scenario by 10% compared to the 46% improvement by the good
scenario. The largest variations in results were observed in the waste
treatment (0–0.3 kg CO2eq) and transport (0.04–0.16 kg CO2eq) categories,
which were the most directly affected by the quality rejection rate and
remanufacturing location parameters. We also observed a variation in the
electricity category, influenced by the remanufacturing location.

a

b

Figure 8: _Multivariate sensitivity results of remanufactured catheters._ As
the efficiency of the remanufacturing process improves (see Table 7), the
emission savings of remanufactured catheters improves compared to an
equivalent number of virgin catheters ($E^{f}_{v}\cdot N$). Remanufacturing
reduces emissions by up to 57%. (a) Burden-free per turn emissions
$E^{f}_{r}$. (b) Burdened per life emissions $E^{b}_{perLife}$.

To incorporate the number of turns, we calculated the burdened per life
emissions $E^{b}_{perLife}$ for remanufactured catheters and compared them to
an equal number of virgin catheters ($E^{f}_{v}\cdot N$) in Figure 8b. As the
remanufacturing process became more efficient overall (Bad to Average to Good
scenarios), the per life emission reductions increased significantly from 19%
to 57% ($-$0.9 to $-$4.3 kg CO2eq). Our results showcase that even sub-optimal
remanufacturing processes with relatively small per-turn emission reductions
(e.g., the Bad scenario) may significantly reduce the emissions across a
remanufactured catheter’s entire life cycle.

###  4.3 Long-Term Emissions Use Case: A Realistic Buy-Back Scheme

Finally, we simulate an industry buy-back scheme where medical remanufacturing
is provided by a third-party service. Given the number of turns $N$ and the
remanufacturing rejection rate $R$, we may calculate the necessary initial
injection of virgin catheters $C$. Results for catheter uses $U=1000$ are
shown in Table 8 for the Bad, Average, and Good scenarios, calculated with
Equation (5) (defined in Section 2.6).

Table 8: _The initial injection $C$ of virgin catheters needed to prime a buy-back scheme system_. Results are calculated with Equation (5) for the three scenarios described in Table 7. Scenario |  Bad |  Average |  Good
---|---|---|---
Nr. of turns $\bm{N}$ |  3 |  4 |  5
Rejection rate $\bm{R}$ |  0.5 |  0.15 |  0.0
Initial injection $\bm{C}$ |  572 |  314 |  200
Total uses $\bm{U}$ |  1000 |  1000 |  1000

Figure 9a visualises the total emissions for 1000 catheter uses across
scenarios. It immediately stands out that all remanufacturing burdened-
emissions $E^{b}_{perLife}$ were significantly lower than the emissions of
1000 virgin catheters ($E^{f}_{v}\cdot 1000$ = 1535 kg CO2eq). As the
proportion of uses covered by remanufactured catheters grew, the total
emissions reduced from 1140 kg (Bad) to 902 kg (Average) to 797 kg CO2eq
(Good).

Relative to one remanufactured catheter (Figure 9b), the burdened per turn
emissions $E^{b}_{perTurn}$ were reduced to 0.8–1.14 kg CO2eq, compared to a
1.53 kg CO2eq virgin catheter. Overall, our results show that remanufacturing
may reduce long-term, cumulative emissions by a significant 25–48%, depending
on the process efficiency and the used catheter quality.

a

b

Figure 9: _Emission results of a realistic buyback scheme._ A total of 1000
catheter uses $U$ were considered. The proportion of virgin and remanufactured
catheter uses are given in Table 8. The results show that remanufacturing may
reduce long-term emissions by up to 48%. (a) Burdened long-term emissions
$E^{l}_{perScheme}$. (b) Burdened long-term emissions $E^{l}_{perTurn}$.

##  5 Discussion

Our extensive emission result analysis found that remanufacturing catheters
reduces burden-free climate emissions by 60%. Figure 10a compares our burden-
free results $E_{v}^{f}=1.53$ and $E_{r}^{f}=0.61$kg CO2eq (Section 4.1)
against the _Fraunhofer case study_ Schulte et al. (2021). The case study
reports $E^{f}_{v}=1.75$ and $E^{f}_{r}=0.87$kg CO2eq, representing a 50%
emission reduction through remanufacturing. Even though the total emissions
were slightly higher than what our models produced, we consider the results
validated as the total and most category emissions follow the same trends.
Furthermore, the discrepancies can be explained with the primary data updates
we made, such as the lower-impact virgin plastic processing (replacement
materials), lower remanufacturing waste emissions (reduced rejection rate) and
the increased remanufacturing transport emissions (doubled transport rather
than one round trip). Readers are referred to Section 3 for details and
justifications.

a

b

Figure 10: _A summary of our results._ (a) compares our virgin vs.
remanufactured catheter emission results against the case study Schulte et al.
(2021). (b) illustrates how much the total remanufacturing emissions may vary
depending on the selected emission metric. For a fair comparison, all
remanufactured emissions are calculated for the same scenario ($N=3$, $R=50\%$
and $l=USA$, as defined in Section 4.2.4).

_Emission metrics_. However, burden-free results do not necessarily accurately
reflect the realistic emissions. Figure 10b visualises how the total emissions
may change depending on the selected metric. For a fair comparison, all
remanufactured emissions are calculated for the same scenario ($N=3$, $R=50\%$
and $l=$USA). Our proposed metric $E_{perTurn}^{l}$ comes the closest to
accurately reflecting the real-world emissions, as it takes the _previous
lives_ (burdened) and _long-term use_ of catheters into account. For the
chosen Bad scenario, remanufacturing reduces climate emissions by 47% burden-
free, 19% burdened, and 26% long-term, respectively.

_Sensitivity analysis._ Of course, these results may improve dramatically when
the remanufacturing process is optimised. One of the main insights of our
extensive sensitivity analysis (Section 4.2) is the significant impact even
relatively minor changes may have on the absolute and cumulative
remanufacturing emissions. Higher remanufacturing efficiency (e.g., quality
rejection rate, number of turns, location) may significantly reduce climate
impact. In our best-case scenario, remanufacturing reduced climate emissions
by 71% burden-free, 57% burdened, and 52% long-term, respectively.

_Result uncertainty._ Because Life Cycle Analysis (LCA) results are calculated
from a model of the real-world product, LCA climate emissions should be
considered as estimates. The uncertainty of the results may be categorised
into three groups: _model_ , _scenario_ , and _parameter uncertainty_ Bamber
et al. (2020). Throughout our study, we have attempted to address these
concerns and improve the reliability of our results. Model uncertainty comes
from the structure of the emission-calculating models themselves. We have
addressed this by choosing highly-regarded software and background datasets
openLCA and Ecoinvent v3.0. On the other hand, scenario uncertainty describes
uncertainty introduced through LCA methodological choices such as the
functional unit and system boundary. To minimise the introduced uncertainty,
we have followed industry standards (e.g., ISO iso (2006) and NHS guidelines
Penny et al. (2012); Standard (2013)). Finally, to address parameter
uncertainty (i.e., data uncertainty), we have conducted a qualitative analysis
of the data quality and included a comprehensive sensitivity analysis of high-
impact life cycle parameters.

_Versatility._ Note that the systematic evaluation of virgin and
remanufactured electrophysiology catheter emissions and the proposed long-term
emission metric are versatile and not limited to electrophysiology catheters.
In future, a similar approach could be taken to evaluate the life cycle
emissions of other high-waste medical devices, as well as for circular economy
approaches other than remanufacturing (e.g., recycling).

##  6 Related Work

As substantial individual contributors to environmental impacts, healthcare
organisations and regulatory bodies worldwide have been investing in circular
economy solutions England and Improvement (2020); Agreement (2015); EU
Commission (2020). Compared to the current reliance on a linear, take-make-
dispose model, a circular economy is defined by its principles to redesign,
reduce, recover, recycle, and reuse (5R’s) resources to significantly extend
their life before disposal Chen et al. (2020). Remanufacturing is a promising
technique which resets a used device to a “substantially equivalent” state as
when it was first manufactured MHRA (2016, 2021). This approach is
particularly impactful for single-use medical devices, which contribute
significantly to the 590,000 tonnes of healthcare waste produced annually in
England alone Zils et al. (2022) and have similar statistics globally.
Regulated remanufacturing processes allow the devices to be legally reused,
reducing both the consumption of rare raw resources and minimising the need
for emission-heavy waste disposal treatments (e.g., incineration) Unger and
Landis (2016).

Apart from the environmental and financial benefits of a more circular single-
use device economy, remanufacturing also has the potential to make expensive,
multi-use medical devices more available to developing countries Eze et al.
(2019). By prolonging their life, devices discarded due to the fast-paced,
technology-driven turnover in high-income countries may be repurposed.
Multiple studies have argued that the required initial investment to ramp up
remanufacturing capabilities would be offset quickly as the devices are safely
reused Oturu et al. (2022); Eze et al. (2020).

To make the required sustainable procurement decisions throughout a product
value chain, decision makers need access to realistic, quantified climate
impacts Dong et al. (2018). Life Cycle Analysis (LCA) has been widely
recognised as an effective tool to support sustainable decision-making by
systematically evaluating a product system’s potential impacts over its entire
life Liu et al. (2022). Climate impact (also GHG emissions or carbon
footprint) measured in kg CO2eq tends to be the most popular emission metric
Smol et al. (2017); Ditac et al. (2022), presumably due to its widespread use
across public, industry, and legislative communication around climate change.
However, LCAs may be used to give a broad overview of multiple environmental
factors instead, which may avoid over-optimising a particular indicator
Bojarski et al. (2009). The LCA modelling may have different purposes within
the scope of sustainability: (i) To compare the impact efficiency of
healthcare practices (e.g., healthcare waste management approaches Soares et
al. (2013)), (ii) to inform product design (e.g., comparing single-use medical
devices containing biopolymers vs. plastic equivalents Unger et al. (2017),
and (iii) to inform procurement decisions (e.g., single-use vs. reusable
bronchoscopes Sørensen and Grüttner (2018)). Furthermore, called a Comparative
LCA, such analysis may provide a robust and transparent comparison of two or
more products Martin et al. (2022).

However, a significant limitation of LCAs is that they rely on a core,
approximated model of a real-world product system Larsson Ivanov et al.
(2019). Therefore, the quality of the environmental impact measurements is
subject to the quality of the representative model, which describes all
material inputs and outputs that contribute to or stem from the product or
service Wu (2019). This inherent challenge to the modelling process means that
LCA models are very time-consuming and expensive to construct, often requiring
long periods of extensive data collection throughout a product’s life cycle.
The consequence is that few studies have been carried out on complex product
systems. Popular healthcare candidates tend to be simple with relatively few
components, for example, face masks van Straten et al. (2021), surgical
scissors Rizan et al. (2022), and staplers Freund et al. (2022), to name a
few. In contrast, electrical medical devices are rarely featured (e.g.,
bronchoscopes Sørensen and Grüttner (2018)). Especially in the healthcare
domain, proprietary design and materials in key components may make the data
collection and LCA modelling process more complicated than usual.

In cases where product life cycle data is unavailable, assumptions and
simplifications have to be made. Because LCAs may be highly sensitive to such
choices as well as other modelling decisions (e.g., system boundary, reference
unit, allocation strategy) Djati et al. (2018); Liu et al. (2019); Bishop et
al. (2021), recent years have seen an attempt to standardise LCA analysis
through modelling standards (e.g., ISO regulations iso (2006, 2006)) and
reporting guidelines (e.g., NHS GHG accounting Penny et al. (2012); Standard
(2013)). Consequently, current studies tend to include a report of the
assumptions made Anshassi and Townsend (2021); Anshassi et al. (2021);
Kløverpris (2018) and a sensitivity analysis of key life cycle parameters
Shimako et al. (2018); Pannier et al. (2018); Patouillard et al. (2019). The
aim is to give the results and their interpretation a clear context and
provide a measure of the uncertainty.

Given the uncertainty of LCA estimations and their importance in supporting
significant shifts in sustainable medical device procurement, it is not
unreasonable to expect studies to be frequently validated to ensure that the
results are accurate. However, LCA result validation is rare because comparing
absolute environmental impact results across studies is difficult even when
common guidelines are followed Spreafico (2022). This is because the mentioned
industry standards propose best practices in broad strokes but leave many
details to the study designers, which may drastically influence the results.
For example, there is currently no one-size-fits-all solution for
incorporating circular life cycles in LCA models, nor a hard-and-fast rule for
which life cycle parameters to consider when calculating long vs. short-term
emissions. When validation is attempted, it often results in major impact
discrepancies (e.g., $-$270–570% variation in a validation of 13 plastic
recycling studies Creadore and Castaldi (2022)).

The challenges with LCA emission modelling illustrated above also apply to
electrophysiology catheters, the medical device examined in this article. As a
traditionally single-use medical device with significant rare-resource
material components, they are a promising candidate for remanufacturing. To
the best of our knowledge, only a handful of studies have assessed their
environmental impacts, which we discuss in the following.

In a recent study, Leung et al. found that circular mapping catheters could be
remanufactured to their original functionality and efficiently reused in
healthcare centres without complications Leung et al. (2019). According to
their calculations, over £30,000 were saved across only 100 procedures. They
estimate that up to £1.7 m may be saved annually in the UK if half of all
circular mapping catheter procedures (5000–10,000) were carried out with
remanufactured catheters instead. The paper concludes that catheter
remanufacturing is a highly cost-efficient process that may be implemented
without compromising patient safety. Additionally, Ditac et al. modelled the
carbon footprint of atrial fibrillation catheter ablation procedures from
catheter production to surgery, covering all processes carried out in the
operating room Ditac et al. (2022). The authors found that catheters
contributed almost 40% of total Greenhouse Gas (GHG) emissions during the
procedure, 26% of emissions came from the anaesthesia and other pharmaceutical
drugs, and the remaining 34% were emitted by other disposable materials during
surgery. Since more than a third of ablation GHG emissions are released during
material mining and catheter production, the results suggest that catheter
remanufacturing could potentially significantly reduce their environmental
impact.

A survey of 278 physicians from 42 European healthcare centres revealed a high
motivation to reduce the environmental impact of EP procedures (62% of
responses) Boussuge-Roze et al. (2022). However, Boussuge-Roze et al. report
that only 15% of catheters are remanufactured and identify multiple barriers
that must be addressed before the process can become more widespread. These
are mainly at an institutional, processing, and regulatory level and highlight
the need for a collaborative approach between healthcare, industry, and
legislation. Schulte et al. provide an incentive for catheter remanufacturing
by quantifying the emission reductions with a comparative LCA analysis of
virgin manufactured and remanufactured single-use electrophysiology catheters
Schulte et al. (2021). They find that remanufacturing reduces GHG emissions by
51% per turn when classifying the used catheter at the start of the
remanufacturing process as burden-free (i.e., not considering previous lives).
They also include a circularity metric to take multiple remanufactured
catheter lives into account, which can be critical to interpret LCA results
accurately Andrae (2022).

Even with widely-accepted standards for LCA analysis in place, LCA methodology
for healthcare faces open questions. Significant challenges include (i) how to
address data unavailability (e.g., due to proprietary materials and
processes), (ii) how to address the consequent uncertainty, and (iii) how to
translate the absolute LCA emission results into actionable insights for
industry and healthcare practitioners. To address these points in our
comprehensive study of electrophysiology catheters, we validate a case study
from the literature, conduct an extensive results analysis including a
sensitivity analysis of key parameters, and propose a novel metric that
calculates realistic emissions by taking long-term use statistics of the
device into account.

##  7 Conclusions

In this article, we carried out a comprehensive analysis of the climate impact
and carbon emissions of virgin manufactured and remanufactured
electrophysiology catheters, validating and expanding on a previous case study
by the prestigious Fraunhofer Institute with a holistic sensitivity analysis
and long-term emission analysis. Our emission framework is based on Life Cycle
Analysis (LCA) models.

According to our models, remanufacturing catheters achieved 60% burden-free
per turn emission reductions (1.53 to 0.61 kg CO2eq). However, our results
have shown that burden-free results do not necessarily reflect real-world
emissions. Therefore, we have included a range of emission metrics, including
a novel long-term emission metric. When taking a remanufactured catheter’s
previous lives into account, the emission reduction drops slightly to 57%
burdened per life reductions ($-$0.87 kg CO2eq). Including long-term
remanufacturing use statistics changes the results to up to 48% cumulative
reductions ($-$0.73 kg CO2eq).

Our comprehensive results analysis concluded in three primary insights:

  1. (i)

Remanufacturing is a promising circular economy approach to reduce the climate
impact of single-use electrophysiology catheters.

  2. (ii)

Sensitivity analysis has shown that parameters across the product chain may
have major impacts on environmental emissions (e.g., up to 66% reduction with
an improved remanufacturing rejection rate). Therefore, our study encourages a
collaborative approach to remanufacturing by all actors throughout the value
chain.

  3. (iii)

Furthermore, finally, the distinction between burden-free (no previous lives)
and burdened emissions (taking previous lives into account) is necessary to
fully understand how emissions may be attributed to catheter turns over its
entire life. Additionally, long-term use statistics should be incorporated
into the emission metrics for more accurate results.

In future, we would like to expand our LCA models by removing the need for
simplified assumptions that we had to make due to data availability.
Additionally, since our proposed emissions framework is device-agnostic, it
would be beneficial to analyse the emissions of other high-waste medical
devices to inform the developing circular economy and net zero goal in
healthcare.

Conceptualization, Y.W. and K.A.N.; methodology, J.A.M., J.S., Y.W. and
K.A.N.; software, J.A.M. and J.S.; validation, J.A.M., J.S., Y.W. and K.A.N.;
formal analysis, J.A.M. and J.S.; investigation, J.A.M. and J.S.; resources,
J.A.M., J.S., Y.W. and K.A.N.; data curation, J.A.M., J.S., Y.W. and K.A.N.;
writing—original draft preparation, J.A.M. and J.S.; writing—review and
editing, J.A.M., J.S., Y.W. and K.A.N.; visualization, J.A.M. and J.S.;
supervision, Y.W. and K.A.N.; project administration, Y.W. and K.A.N.; funding
acquisition, Y.W. and K.A.N. All authors have read and agreed to the published
version of the manuscript.

This research was funded by University of Brighton’s 2021 Quality Research
grant.

Not applicable.

Not applicable.

The data presented in this study are available in this article and in the
licensed Ecoinvent 3.8 dataset at https://ecoinvent.org/, accessed on 11 July
2022.

###### Acknowledgements.

We gratefully thank Dan Vukelich and David Sheon from the Association of
Medical Device Reprocessing (AMDR); Lars Thording from Innovative Health; and
Agnes Henson, Nicole Fletcher and Rebecca Griffiths from NHS England for their
insight and contribution. This research was funded by University of Brighton’s
2021 Quality Research grant. The authors declare no conflict of interest. The
funders had no role in the design of the study; in the collection, analyses,
or interpretation of data; in the writing of the manuscript; or in the
decision to publish the results. Abbreviations The following abbreviations are
used in this manuscript:
AMDR | Association of Medical Device Reprocessors (USA).
---|---
CO2 | Carbon Dioxide.
DE | Germany.
EF | Environmental Footprint.
EP | Electrophyisiology.
EU | European Union.
FDA | Food and Drug Administration (USA).
GHG | Greenhouse Gases.
GWP | Global Warming Potential.
IH | Innovative Health (USA).
ISO | International Organization for Standardization.
JIT | Just In Time.
LCA | Life Cycle Analysis.
LCI | Life Cycle Inventory.
LCIA | Life Cycle Impact Analysis.
NHS | National Health Service (UK).
OEM | Original Equipment Manufacturer.
SUD | Single-Use Device.
UK | United Kingdom.
UN | United Nations.
USA | United States of America.
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