Taxonomy of medical devices in the logic of health technology assessment [original]

International Journal of Technology Assessment in Health Care, 31:5 (2015), 324–330.

Cambridge University Press 2015

doi:10.1017/S0266462315000562

Taxonomy of Medical Devices in the

Logic of Health Technology

Assessment

Cornelia Henschke

Department of Health Care Management, Technische Universit¨

at Berlin

[email protected]

Dimitra Panteli

Department of Health Care Management, Technische Universit¨

at Berlin

Matthias Perleth

Medical Consultancy Department, Federal Joint Committee

Reinhard Busse

Department of Health Care Management, Technische Universit¨

at Berlin

Objectives: The suitability of general HTA methodology for medical devices is gaining interest as a topic of scientific discourse. Given the broad range of medical devices, there might

be differences between groups of devices that impact both the necessity and the methods of their assessment. Our aim is to develop a taxonomy that provides researchers and policy

makers with an orientation tool on how to approach the assessment of different types of medical devices.

Methods: Several classifications for medical devices based on varying rationales for different regulatory and reporting purposes were analyzed in detail to develop a comprehensive

taxonomic model.

Results: The taxonomy is based on relevant aspects of existing classification schemes incorporating elements of risk and functionality. Its 9 ×6 matrix distinguishes between the

diagnostic or therapeutic nature of devices and considers whether the medical device is directly used by patients, constitutes part of a specific procedure, or can be used for a variety

of procedures. We considered the relevance of different device categories in regard to HTA to be considerably variable, ranging from high to low.

Conclusions: Existing medical device classifications cannot be used for HTA as they are based on different underlying logics. The developed taxonomy combines different device

classification schemes used for different purposes. It aims at providing decision makers with a tool enabling them to consider device characteristics in detail across more than one

dimension. The placement of device groups in the matrix can provide decision support on the necessity of conducting a full HTA.

Keywords: Health technology assessment, Medical devices, Classification

Health technologies such as medical devices are an essential

part of health care. The European Union defines a medical de-

vice as “[ . . . ] any instrument, apparatus, appliance, software,

material or other article, whether used alone or in combina-

tion, together with any accessories [ ...]”(1), which includes

a broad range of different products for purposes such as pre-

vention, diagnosis, monitoring, treatment, alleviation of dis-

ease, or compensation for an injury or handicap (1). Many

of these devices have led to important improvements in di-

agnosis and treatment of diseases such as better health out-

comes in terms of higher life expectancy and/or better quality

of life (2–4). However, their rapid pace of innovation might

also be associated with risks (5) and cause harm to patients.

Recent examples arising from the use of medical devices in-

clude recalls of specific types of breast implants (6), artifi-

cial hips (7), and implantable cardioverter-defibrillators (8).

Furthermore, fast-paced innovation is accompanied by rising

health expenditures (9;10). The combined imperatives of pa-

tient benefit and safety as well as cost containment have led

many countries to introduce regulatory instruments to identify

technologies that minimize risk and ensure value and value for

money.

There are two approaches to regulate medical technologies

depending on the point in time when regulation applies relative

to market authorization. The first approach concerns premar-

ket evaluations, which cover safety and performance aspects.

An additional demonstration of efficacy can be required de-

pending on the authorization system and the risk of the device

(e.g., high risk devices in the United States that are regulated

by the Food and Drug Administration [FDA]) (11;12). The sec-

ond approach encompasses postmarket evaluation systems that

additionally aim to consider effectiveness in the usage context,

cost-effectiveness and other domains potentially relevant for

coverage decision making, such as legal, ethical, socio-cultural,

and organizational consequences (13). Health technology as-

sessment (HTA) falls under this second approach and aims at

informing regulatory decision makers once marketing autho-

rization has been granted. It is applied to a broad range of

technologies, including pharmaceuticals, medical devices, and

public health interventions. The final intention of HTA is to pro-

vide the evidence base for decision makers, primarily at health

system level, on the consequences of adopting a given tech-

nology across the aforementioned domains (14;15). However,

most formal decision structures incorporating evidence-based

324

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Medical device taxonomy

approaches were established for pharmaceuticals (16), which

also have been the main focus of guidelines for economic eval-

uation (17). The relevance of general methodology for medical

devices, both in HTA as a whole and for economic evaluation

in particular, has been gaining interest as a topic of scientific

discourse, especially in light of new regulatory provisions for

their market authorization (18).

There are particularities characterizing medical devices,

which merit differentiated assessment practices ranging from

trial design to statistical methods to be used for the analysis of

clinical and economic data (19–21). Assessors of medical de-

vices, especially if they are provided as part of invasive and high-

risk diagnostic and therapeutic procedures frequently face the

problem of a lack of randomized controlled trials (RCTs), which

partly derives from lower evidence hurdles in market autho-

rization processes compared with pharmaceuticals (17;22;23).

McCulloch et al. (21) describe particularities and difficulties

of evaluations in the field of surgical innovations, and propose

possible solutions for the assessment of effectiveness against

current standards. They give options for alternative study de-

signs, such as parallel group nonrandomized studies or con-

trolled interrupted-time series studies, to be used when ran-

domized trials are not feasible for ethical or pragmatic reasons

(21;24).

Furthermore, given the large, heterogeneous spectrum of

devices used for diagnostic and/or therapeutic purposes, it is

safe to assume that there might be device-specific characteris-

tics that should be accounted for in HTA practice. For exam-

ple, the evaluation of diagnostic devices might be complicated

by difficulties in separating the value of the diagnosis itself

from the value of improved outcomes due to subsequent treat-

ment (17;25). Furthermore, many medical devices are subject to

device-operator interaction, which makes the efficacy of the de-

vice contingent on the learning curve of the operator (17;22;24).

Finally, the implementation of a new device might be associ-

ated with wider organizational and economic implications for

providers, such as the need for professional trainings or new

infrastructures and associated investments (17). These partic-

ularities complicate the debate about what the related health

benefits are, where and to whom these accrue and how rational

decisions regarding coverage in relation to effectiveness and

cost can be made.

Medical devices have been classified in different ways.

While classifications facilitating market authorization aim at

categorizing medical devices according to the degree of risk

assigned to them, procurement classifications adopt a perspec-

tive relevant to pricing and reimbursement decisions. To our

knowledge, as of yet there is no detailed classification that

looks at medical devices from the viewpoint of HTA. There-

fore, the aim of this study is (i) to clarify, describe and dis-

tinguish different categories of medical devices in the context

of HTA for decision making on value and coverage and (ii) to

develop a taxonomic model that incorporates elements of exist-

ing classification schemes. With the ultimate goal of providing

researchers and policy makers with an orientation guide on how

to approach the assessment of medical devices, the taxonomy

aims at (i) highlighting the extent to which HTA is necessary

for different device categories and (ii) indicating if and how

assessment tools should be tailored to include device-specific

elements and achieve best results depending on different cat-

egories of medical devices. As a first step, the model focuses

on Europe and does not account for differences in pre- and

postmarket approval processes of medical devices beyond the

European Union (EU) context.

METHODS

The research centered on different classification schemes for

medical devices. To identify several classifications and nomen-

clatures for medical devices based on varying rationales for

different regulatory and reporting purposes, selected to account

for different characteristics of medical devices, we carried out

a search of literature. We first carried out a PubMed search

to identify relevant published literature and only considered

studies with a focus on classification and nomenclatures of

medical devices. We also reviewed legislative and policy docu-

ments in the European context discussed in the included studies.

These included the current European Union regulatory frame-

work for medical devices consisting of three directives used for

the licensing process, the international classification for medi-

cal devices used by the Global Medical Device Nomenclature

(GMDN), and the OECD Classification of Health Care Func-

tions, which considers, inter alia, reimbursement aspects. These

frameworks were analyzed in detail to inform the development

of a comprehensive taxonomic model.

RESULTS

Background on Existing Classifications of Medical Devices

Classification of Medical Devices According to EU Directives.

The current Euro-

pean Union regulatory framework for medical devices con-

sists of three directives: Council Directive 93/42/EEC on med-

ical devices (MDD), Council Directive 90/385/EEC on active

implantable medical devices (AIMDD) and Council Directive

98/79/EC on in vitro diagnostic medical devices (IVDD) (26–

28). Medical device manufacturers are allowed to market their

products across all EU member states after receiving a Confor-

mit´

e Europ´

eenne (CE) mark, which demonstrates that the safety

criteria, quality in terms of reliability, and performance are ful-

filled (11;29). However, these regulations do not require manu-

facturers to demonstrate the effectiveness or cost-effectiveness

of their products to obtain marketing authorization (30).

MDD is applicable to all medical devices that are neither

an active implantable medical device nor an in vitro diagnostic

medical device. During conformity assessment, medical de-

vices are categorized in one of four classes (I, IIa, IIb, or

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Henschke et al.

III) according to the potential risk associated with their use.

This Directive contains eighteen rules that guide categorization

based on device characteristics such as nonactive versus active

devices, noninvasive versus invasive devices and short-term use

versus long-term use of invasive devices. Different conformity

assessment procedures have to be implemented depending on

device class (26).

AIMDD is valid for active implantable medical devices,

whichrelyonsourcessuchaselectricalenergyandare“[...]

intended to be totally or partially introduced, surgically or med-

ically, into the human body or by medical intervention into a

natural orifice, and which is intended to remain after the proce-

dure[...]”.IncontrasttoMDD,AIMDDcontainsnodifferen-

tiation according to identified risks associated with the device.

However, it does distinguish between custom-made products

developed specifically for an individual patient, and products

intended for clinical investigations, which include active im-

plantable medical devices used only by specialist doctors when

conducting investigations in a clinical environment. Conformity

assessment procedures are assigned according to this current

differentiation (27).

Finally, IVDD regulates the market authorization of medi-

cal devices intended for in vitro usage, such as reagents, reagent

products, calibrators, control materials, kits, instruments, ap-

paratuses, equipment, or systems, which are used alone or in

combination. Different conformity assessment procedures are

applied to groups of devices based on lists, which are annexed

to the directive. Devices are assigned to List A or List B or are

subject to specific regulations (e.g., for performance evaluation

or self-testing devices) (28).

In response to several scandals in the field of medical de-

vices in the recent past (e.g., prefilled silicone breast implants

manufactured by Poly Implants Prosth`

ese [PIP] (6) and hip

implants manufactured by DePuy) (7), the European Commis-

sion issued two proposals on medical device regulation on 26

September 2012 and recommendations on the audits and as-

sessments performed by notified bodies in the field of medical

devices on 24 September 2013. The first proposal modifies both

the MDD and the AIMDD to directly categorize active im-

plantable devices into class III, where they would fall under de

facto due to their risk potential (31). The second proposal calls

for in vitro diagnostic devices to be classified into four classes

according to their risk level, which necessitates different con-

formity assessment procedures (32).

Classification of Medical Devices According to Financial Aspects.

The OECD pro-

vides within its framework “System of Health Accounts” a

systematic description of financial flows concerning the con-

sumption of healthcare goods and services. The aim of the

international classification for health accounts (ICHA) is to de-

scribe healthcare systems from an expenditure perspective. One

essential dimension in this classification is that of healthcare

functions (ICHA-HC), which groups healthcare goods and ser-

vices based on their purpose. Medical devices are assigned to

different healthcare functions, for example therapeutic appli-

ances and other medical goods (HC.5.2), which include devices

such as glasses (HC.5.2.1), hearing aids (HC.5.2.2), as well

as orthotic devices and other orthopedic appliances (HC.5.2.3)

(33).

Sorenson and Kanavos (34) also developed a categoriza-

tion of medical devices according to financial aspects, taking

into account procurement policies across a sample of five Euro-

pean countries (England, France, Germany, Italy, Spain). They

explored how such practices interact with coverage and reim-

bursement approaches. They used Busse’s (35) three categories

of devices—medical aids, implantable artificial body parts, and

medical devices for the assistance of medical professionals—

to explain the relationships between actors of procurement and

purchasing interactions.

Global Medical Device Nomenclature (GMDN).

The GMDN was developed as

an international coding system for medical devices based on dif-

ferent existing nomenclatures. These included the Classification

Names for Medical Devices (CNMD) used in the United States,

the European Diagnostic Manufacturers Association (EDMA)

in vitro product classification, ISO 9999 Technical Aids for Dis-

abled Persons Classification (international use), the Japanese

Medical Device Nomenclature (JFMDA), the Norsk Klassi-

fisering Koding and Nomenklatur (NKKN), and the Universal

Medical Device Nomenclature System (UMDNS) (36). The aim

was to provide a common method for unambiguously describing

and identifying medical devices, to be used by relevant regula-

tory authorities, healthcare providers, manufacturers, suppliers,

and assessment bodies (37). Its structure is based on three levels:

device category, generic device group, and device type (37).

Developing a Taxonomic Model

Relevant elements from the identified classification schemes

were combined to form a wider taxonomic model that fol-

lows the logic of HTA for decision making on value and

coverage (Figure 1). While the GMDN seems best suited for

product identification in the context of market approval, vig-

ilance reporting and recall systems, it might be inappropri-

ate for the development of a device-taxonomy following the

logic of HTA. Thus, to systematically develop the aforemen-

tioned taxonomy, characteristics of the EU Directives and the

OECD Classification of Health Care Functions were primarily

used. Results in the form of a 9 ×6 matrix are presented in

Figure 1.

The nine rows show the categories included in the three

Directives on medical devices, which are used to determine au-

thorization processes, incorporating elements of risk and func-

tionality of device types. According to the Directive 93/42/EEC,

technologies that are neither an active implantable medical de-

vice (IV) nor an in vitro diagnostic medical device (V-VIII)

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Medical device taxonomy

Figure 1. Taxonomic model to classify medical devices according to their HTA relevance.

are integrated in one of four classes. While medical devices

in class I are associated with low potential risk, medium risk

is attributed to classes IIa (nonactive) and IIb (active). Class

III devices are considered high-risk while the risk associated

with active implantable devices (IV) falling under Directive

90/385/EEC is deemed particularly high. Cells numbered from

V to VIII include products classified according to the criteria

of Directive 98/79/EC on in vitro diagnostic medical devices.

Risk, if relevant to patient safety, is a dimension for HTA to be

balanced with the patient-relevant benefit. As HTA for medical

devices with high-risk potential is more important due to risks

for patients and user arising from their use, a high-risk potential

thus can also guide the selection process of devices that should

be evaluated.

The six columns of the matrix consider whether the medi-

cal device (i) is directly used by patients (A1/ A2), (ii) consti-

tutes part of a specific procedure (for which a device is deci-

sive) (B1/ B2), or (iii) can be used for a variety of procedures

(C1/ C2). This differentiation is based on procurement/ reim-

bursement activities used in the OECD Classification of Health

Care Functions (ICHA-HC) and in previous work by Busse (35)

and Perleth et al. (38). Assistive technology devices (A1/ A2)

are products dispensed to and used by patients to compensate,

maintain, or improve their functional capabilities. These include

class HC.5.2 (therapeutic appliances and medical goods) from

the OECD ICHA-HC. For HTA purposes, these technologies

are the ones closest to pharmaceuticals, at least those with a

therapeutic objective. Artificial body parts (B1/ B2) are im-

planted by medical procedures and are largely related to class

HC.1 (Curative care) in the OECD ICHA-HC. More precisely,

these technologies encompass “medical procedures” in which

the device is an important component. Medical devices for the

assistance of medical professionals (C1/ C2) include classes

HC.4.1 (Laboratory services) and HC.4.2 (Imaging services) of

the OECD ICHA-HC. A relevant issue for HTA is that these

technologies can be used in a variety of ways (by indication, by

body part, etc.). Furthermore, the columns allow for a separa-

tion of the aforementioned functions based on the diagnostic or

therapeutic use of devices.

We considered the relevance of different device categories

in regard to HTA to be considerably variable, ranging from high

to low. For taxonomic positions with low relevance, the neces-

sity of conducting an HTA in the first place should be discussed

under consideration of efficient resource use. We propose an ini-

tial, theoretical color-coding in the matrix (its plausibility will

be tested in a subsequent step, see discussion below). High HTA-

relevance of different device categories is highlighted green, low

relevance red. Cells marked yellow include groups where rele-

vance is context-sensitive. Grey fields denote cells for which no

medical devices were identified (29 of the 54 cells). The color

coding of the taxonomy could be used to inform decision mak-

ers when an HTA should be undertaken. The extent to which

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Henschke et al.

assessment tools should be tailored to achieve best results de-

pending on different categories of medical devices is discussed

below.

DISCUSSION

The developed taxonomy combines different device classifica-

tion schemes that have been used for different purposes. Its aim

is to provide decision makers (and at a later stage, assessors)

with a tool enabling them to consider device risk in more de-

tail across more than one dimension. The placement of device

groups in the model cells provides decision support on the ne-

cessity of conducting a full HTA in the first place. It additionally

illustrates that choosing to assess a given device may be inef-

ficient in some cases (e.g., cell A1/ I) or particularly complex

in others (e.g., cell B1/ IV especially in combination with cell

B2/ IV). Furthermore, that different taxonomic positions may

merit separate additional considerations both at the conceptual

stage of assessment as well as in the methodological approach

adopted. The model can thus provide helpful insight during

the operationalization of the research question along the lines

of the PICO model and the development of the HTA protocol

(e.g., on relative taxonomic position of comparators, spectrum

of relevant outcomes, study design etc.).

The three EU Directives on medical devices used in the

licensing process focus on elements of risk and functionality.

Device risk is highly important for patient safety and is therefore

one of the required domains both in pre- and postmarket eval-

uation processes. From the HTA-perspective, it can also guide

topic prioritization processes, as policy makers should pay par-

ticular attention to high-risk devices (39) (e.g., implantable or

surgically invasive devices). Furthermore, risk classification in

the MDD also depends on the duration of patient-device con-

tact (transient: <60 min, short term: continuous use 60 min –

30 days, long term: continuous use >30 days). This might be

a significant detail to consider during assessment, as duration

of contact can play an important role in data collection (e.g.,

dental implants) and thus required duration of studies consid-

ered acceptable as evidence. Generally, longer contact duration

is associated with a higher risk for patients and, therefore, a

higher need for HTA.

The separation of assistive technology devices, artificial

body parts and devices for the assistance of medical profes-

sionals is an essential part of the matrix from an HTA view-

point. While assistive technology devices are products directly

used by patients and can in most cases be assessed “alone”,

artificial body parts and medical devices for the assistance

of medical professionals are both used within procedures and

are subject to device-operator interaction. Thus, effectiveness

outcomes are also dependent on the process or its operator.

In addition, they often need to be compared with the cur-

rent standard procedures. Therefore, assessment tools need to

be able to account for those dimensions. Furthermore, how

certain procedures are to be assessed may depend on whether

they are a part of a wider treatment plan under a physician’s

care (40).

The taxonomic model further separates diagnostic from

therapeutic devices, thus recognizing that different methodolog-

ical approaches need to be adopted depending on the nature of

the device. This is in agreement with international reference

models, such as the HTA Core ModelTM developed by EU-

netHTA. The Model’s second version was published in late 2013

and comes in different iterations for diagnostic and therapeutic

technologies, the former explicitly addressing issues of clinical

utility and clinical validity of diagnostic tests (41). Furthermore,

NICE in England has a separate program for diagnostic tech-

nologies, incorporating appropriate methods (42). As a rule, it

is important to recognize that for some devices, it is challenging

to separate the value of the diagnostic test per se from the value

of improved outcomes as a result of subsequent treatment. We

argue that a potential approach for devices with both diagnostic

and therapeutic functions (cell combination B1/ IV and B2/ IV)

would be for the two components to be considered separately.

In its presented form, the matrix model is not without lim-

itations. The color-coded relevance of HTA for each device

category currently relies on several assumptions. Thus, to test

the model’s plausibility, a subsequent step in our work entails

filtering available HTA reports of European institutions and as-

signing taxonomic positions to devices assessed. Furthermore,

the approach toward risk used in the EU regulation and trans-

ferred to the technology is product-specific, thus ignoring the

contribution of patient characteristics (such as severity of con-

dition) toward the overall risk of the intervention. Finally, as

the current taxonomy is focused on the European context, it

is possible to strengthen the model by including classification

criteria from other contexts, such as those of the FDA.

Issues that pertain to individual device groups, such as bat-

tery life for active implantable devices or learning curves where

device-operator interaction applies, may pose additional chal-

lenges that need to be recognized and be accounted for to pro-

duce robust and representative assessments. Therein lies one of

the intentions of the presented model, namely to fuel the debate

on when and to what extent a differentiated approach is appro-

priate and necessary. Thus, the taxonomy does not elaborate on

individual elements at this stage but rather draws attention to

the categorical position of each device and its core properties to

point in the direction of what device-specific elements may be.

The next step in our work will include the establishment of ba-

sic methodologies per taxonomic position to explicitly consider

particularities of different categories of medical devices.

CONCLUSIONS

Existing medical device classifications are not sufficient for the

purposes of HTA evaluation as they are based on different under-

lying logics. Furthermore, general HTA methodology, while it

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Medical device taxonomy

may incorporate important considerations such as the therapeu-

tic versus diagnostic nature of devices, does not consistently

account for device-specific elements such as device-operator

interaction, duration of patient-device contact, level of device

activity, or combined diagnostic/therapeutic functionality. The

new developed taxonomy combines the two worlds and add fur-

ther considerations to provide a tool enabling decision makers

to consider device risk in more detail across more than one

dimension; it can thus provide decision support on the neces-

sity of conducting a full HTA in the first place. The taxonomy

thus may be considered an important step toward advancing the

debate on HTA/economic evaluation by grouping medical de-

vices according to their relevance for HTA activities. Ongoing

steps include testing taxonomy’s plausibility by filtering avail-

able HTA reports produced by European institutions to assign

medical devices a taxonomic position, and establishing basic

methodologies (e.g., study design requirements) in HTA, which

explicitly consider peculiarities of different categories of med-

ical devices.

ACKNOWLEDGEMENTS

We are grateful to Sabine Fuchs, Britta Olberg and Susanne

Felgner for their constructive comments.

CONFLICTS OF INTEREST

This paper is the result of research that was funded through the

European Commission’s FP7 Cooperation Work Programme:

Health (Grant Agreement Number 305983; acronym AD-

VANCE HTA). The European Commission is not responsible

for the content of the paper. The authors declare no further

conflict of interest in conjunction with this work.

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