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VOLUME 4, ISSUE 2  
 2021 

 

STAKEHOLDER  PERSPECTIVES 

Frossard L. Trends and opportunities in health economic evaluations of prosthetic care innovations. Canadian Prosthetics & Orthotics Journal. 2021; Volume 

4, Issue 2, No.9. https://doi.org/10.33137/cpoj.v4i2.36364 

This article has been invited and reviewed by Co-Editor-In-Chief, Dr. Silvia Ursula Raschke. 
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Frossard L. Trends and opportunities in health economic evaluations of prosthetic care innovations. Canadian Prosthetics & Orthotics Journal. 2021; Volume 4, 
Issue 2, No.9. https://doi.org/10.33137/cpoj.v4i2.36364 

 

 

 
STAKEHOLDER  PERSPECTIVES 

 

TRENDS AND OPPORTUNITIES IN HEALTH ECONOMIC EVALUATIONS OF PROSTHETIC CARE 

INNOVATIONS 

Frossard L1-4* 
 

 

1 YourResearchProject Pty Ltd, Brisbane, Australia. 
2 Griffith University, Gold Coast, Australia. 
3 University of the Sunshine Coast, Maroochydore, Australia. 
4 Queensland University of Technology, Brisbane, Australia. 

 

 

 

 

  

 

 

 

 

 

 

 

 

 

 

 

INTRODUCTION 

Alfred Nobel (1833-1896) said the following about 

innovation “If I have a thousand ideas and only one turns 

out to be good, I am satisfied.”  

In healthcare, the difference between a “good” or a not so 

good innovation is made during health technology 

assessment  (HTA)  and/or   health   economic   evaluation  

 

 

 

 

 

 

 

 

(HEE).1 As defined in APPENDIX 1, these evaluations aim 

at understanding what is the value for money of a treatment. 

Simply put, payers want to make sure they get a bang for 

their buck!  

This is tough question because the answer is rarely black 

and white. Nonetheless, addressing any concerns with 

socio-economical value of an intervention is a prerequisite 

to warrant access to market. Great but unaffordable 

treatments have little prospect of being adopted by 

healthcare policymakers.     

The paper deals with issues of health economic 

assessments specific to prosthetic care innovations as 

 
OPEN  ACCESS Volume 4, Issue 2, Article No.9. 2021 

 

 

Journal Homepage: https://jps.library.utoronto.ca/index.php/cpoj/index 

 

ABSTRACT 

Overcoming obstacles to prosthetic fittings requires frequent tryouts of sockets and components. 

Repetitions of interventions are upsetting for users and place substantial economic burden on 

healthcare systems. Encouraging prosthetic care innovations capable of alleviating clinical and 

financial shortcomings of socket-based solutions is essential. Nonetheless, evidence of socio-

economic benefits of an innovation are required to facilitate access to markets. Unfortunately, 

complex decisions must be made when allocating resources toward the most relevant health 

economic evaluation (HEE) at a given stage of development of an innovation. This paper first, aimed 

to show the importance and challenges of HEEs of intervention facilitating prosthetic fittings. Next, 

the main trends in HEEs at various phases of product development and clinical acceptance of 

prosthetic care innovations were outlined. Then, opportunities for a basic framework of a preliminary 

cost-utility analysis (CUA) during the mid-stage of development of prosthetic care innovations were 

highlighted. To do this, fundamental and applied health economic literature and prosthetic-specific 

publications were reviewed to extract and analyse the trends in HEEs of new medical and prosthetic 

technologies, respectively. The findings show there is consensus around the weaknesses of full 

CUAs (e.g., lack of timeliness, resource-intensive) and strengths of preliminary CUAs (e.g., identify 

evidence gaps, educate design of full CUA, fast-track approval). However, several obstacles must 

be overcome before preliminary CUA of prosthetic care innovations will be routinely carried out. 

Disparities of methods and constructs of usual preliminary CUA are barriers that could be alleviated 

by a more standardized framework. The paper concludes by identifying that there are opportunities 

for the development of a basic framework of preliminary CUA of prosthetic care innovations. 

Ultimately, the collaborative design of a framework could simplify selection of the methods, 

standardise outcomes, ease comparisons between innovations and streamline pathways for 

adoption. This might facilitate access to economical solutions that could improve the life of 

individuals suffering from limb loss.    

CITATION 

Frossard L. Trends and opportunities in 

health economic evaluations of 

prosthetic care innovations. Canadian 

Prosthetics & Orthotics Journal. 2021; 

Volume 4, Issue 2, No.9. 

https://doi.org/10.33137/cpoj.v4i2.36364 

KEYWORDS 

Artificial Limbs, Bionic Limbs, Bone-

Anchored Prosthesis, Cost-

Effectiveness, Cost-Utility, Health 

Economic Evaluation, Health 

Technology Assessment, Prosthesis, 

Socket-Suspended Prosthesis 

 

* CORRESPONDING AUTHOR 

Laurent Frossard (PhD), Professor of Bionics 
YourResearchProject Pty Ltd, Brisbane, Australia. 

E-mail: laurentfrossard@outlook.com 

ORCID number: https://orcid.org/0000-0002-0248-9589 

Special Issue: Health Economics in Prosthetics & Orthotics 

https://doi.org/10.33137/cpoj.v4i2.36364
https://jps.library.utoronto.ca/index.php/cpoj/index
https://doi.org/10.33137/cpoj.v4i2.36364
mailto:laurentfrossard@outlook.com
https://orcid.org/0000-0002-0248-9589


 

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ISSN: 2561-987X 
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presented in Figure 1. First, the importance and challenges 

of HEEs of interventions facilitating prosthetic fittings are 

highlighted. Next, the main trends in HEEs of new 

healthcare technologies are outlined with particular 

emphasis on specific HEEs to consider during the course of 

development of innovations. Then, opportunities for a basic 

framework of preliminary assessments during the mid-stage 

of development of prosthetic care innovations are 

suggested. Finally, the paper concludes with some calls to 

action to further develop preliminary assessments.   

IMPORTANCE OF HEALTH TECHNOLOGY 

EVALUATIONS  

This introductory section highlighted (A) the needs for 

solutions facilitating prosthetic fittings and (B) the current 

challenges to produce relevant health economic evaluations 

of prosthetic care innovations.  

Role of prosthetic care 

Because the everyday ability of individuals suffering from 

limb loss to use an artificial limb is critical to their quality of 

life, clinical teams made bespoke recommendations 

intending to maximize comfort, stability and mobility of 

prosthetic fittings.2,3 Ultimately, this process incorporates all 

personalized interventions performed by a prosthetist 

around the choice and alignment of prosthetic components 

as well as the management of prosthetic attachment to the 

residuum including design, manufacture and adjustment of 

socket or osseointegrated implant.4  

 

 

Outcomes of prosthetic fitting depends largely on the 

performance of prosthetic components.5-11 where 

Dillingham et al (2001) noted that  60% of amputees are 

satisfied with prosthetic characteristics such as weight, 

aesthetics and functionality (e.g. servicing, how easy the 

prosthesis is to use) and 57% of the traumatic lower limb 

amputees in the study expressed some dissatisfaction with  

prosthetic comfort.12 Since, studies showed that the use 

and satisfaction of prosthetic lower limb could be 

significantly improved when using advanced components 

such microprocessor-controlled knees compared to a non-

microprocessor-controlled knees.9,13,14  

 

LIST OF ABBREVIATIONS 

CET: Cost-effectiveness threshold 

CHEC: Consensus health economic criteria extended 

checklist 

CHEER: Consolidated health economic evaluation reporting 

standards checklist 

CUA: Cost-utility analysis 

HEE: Health economic evaluation 

HTA: Health technology assessment  

ICER: Incremental cost-effectiveness ratio 

ICUR: Incremental cost-utility ratio 

QALY: Quality-adjusted life-year 

SF36: 36-Item Short Form Survey 

WTP: Willingness-to-pay threshold 

 

Trends 

• Generic pathways to HEE  
• Prosthetic-specific HEE 

IMPORTANCE 

• Needs for prosthetic 
care innovations  

• Challenges to produce 
HEE 

Gaps 
• Knowledge gaps of HEE 
• Role of Pre CUA to 

assess innovation 

Health 
Technology 
Assessment 

Health 

Economy 

Evaluation 

Need for Pre 

CUA 

Basic Pre CUA 
framework  

Figure 1: Overview of importance, trends and gaps of health economy evaluations (HEE) of prosthetic solutions leading to the need for 

basic framework of preliminary (Pre) cost-utility analysis (CUA) for prosthetic care innovations. 

https://doi.org/10.33137/cpoj.v4i2.36364


 

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Satisfactory prosthetic fitting might be compromised 

because of incongruous shapes of residuum (e.g., length, 

bulbous, volume change) and/or skin issues.15-17 Paterno et 

al (2018) and Meulenbelt et al (2009) report that that 63–

82% of lower limb amputees have problems with skin 

lesions.2,18 Turner and McGregor (2020) report that 48.0% 

of amputees and 65.7% of clinicians cited socket fit issues 

as the biggest factor impacting rehabilitation.6 And, sadly, 

Paterno et al (2018) and Meulenbelt et al (2009) found a 25-

57% prosthetic abandonment rate and identified failed 

socket fit as a likely possible cause.2,18 

Demand for prosthetic care innovations 

In many cases, overcoming obstacles to prosthetic fitting 

requires frequent tryouts of components and sockets 

fittings.3 Regular medical attention are, first and foremost, 

upsetting (e.g., pain), disruptive (e.g., sick leave) and costly 

(e.g., out-of-pocket expenses) for users.19 Repetitions of 

interventions also place a substantial economic burden on 

healthcare systems stressed to subsidize treatments 

beyond minimal prosthetic care standards.20-22 For 

example, the fitting of only a single socket per year might be 

approved by some healthcare organizations.22  

Encouraging prosthetic care innovations that alleviate the 

clinical and financial shortcomings of current fitting options 

is essential (APPENDIX 1).2,3,14,23-26 Hence, efforts made 

by a bench of stakeholders (e.g., users, carers, clinicians, 

engineers, researchers, administrators) to develop and 

encourage new prosthetic care interventions to improve 

socket fittings and, eventually, eliminate socket attachments 

altogether (e.g., bone-anchored prostheses).27-34 These 

solution-finders will be called “promoters” of prosthetic care 

innovations throughout this paper and are shown in 

relationship to other concepts presented in this paper as a 

regrouping of individuals suffering from limb loss, providers 

of prosthetic solutions and administrators of healthcare 

organisations (APPENDIX 1) into a single collaborative 

group with common goals.22,35-38 

Ultimately, prosthetic care innovations must be safe and 

efficient in ways that alleviate some adverse events (e.g., 

pain, slippage, pistoning, bell clapping, skin damages, falls), 

maximise functional outcomes (e.g., comfort, stability, 

mobility) and, preferably, enhance quality of life (e.g., 

Quality-Adjusted Life Year, Disability-Adjusted Life 

Year).2,3,14,23-25,29,39,40 Proofs of safety and efficacy of 

innovations are essential but no longer sufficient.11 

Evidence of socio-economic benefits are also 

paramount.4,30,37,38,41-47  

Health economic evaluations of innovations 

Ijzerman and Steuten (2011) identified that in order for 

societal benefits to be maximized three things must occur: 

1) governments need more data on benefits arising when 

public resources are spent, 2) companies need more data 

to effectively manage their product development portfolios 

and 3) research programs at universities may need to be 

actively encouraged in this direction.37 

Policymakers in healthcare organizations around the world 

adopt a reasoning more or less utilitarian when making 

decisions about medical care expenses.37 However, 

healthcare administrators are often obligated to confirm the 

value for money of interventions prior approval (e.g. fee-for-

service, fee-for-value).47-53 For example, an HEE might be 

required to differentiate the four microprocessor-controlled 

knees assessed by Campbell et al (2020) all showing 

relative parity with regards to functional mobility, health 

state satisfaction and quality of life or injurious falls (i.e., C-

Leg, Ottobock, Duderstadt, Germany; Orion, Blatchford 

Group, Hampshire, United Kingdom; Plie, Freedom 

Innovations, Irvine, California, United States; Rheo, Ossur, 

Reykjavik, Iceland).14 Recommendation for one knee or the 

other may be based on costs reduction of prosthetic care 

interventions.  

The burden of HEE of an innovation also falls onto 

developers and manufacturers of technological solutions 

including attachments (e.g., liners, sockets, implants), 

artificial limb components (e.g., elbow, wrist, knee, ankle) 

and protective device (e.g., shock absorbers, failsafe).38 

Steven et al (2019) suggested that solution developers must 

understand the value created by their interventions and act 

quickly on them to  provide some forms of evidence of cost-

effectiveness of their innovations.48 Failing to do so could 

seriously hinder access to market and adoption of their 

innovations. O’Malley (2010) indicated that the most 

common reason for the Australian Medical Services 

Advisory Committee to not recommend funding for new 

technology was not only insufficient clinical evidence but 

also the lack of proven cost-effectiveness presented during 

early stage of the examination process.54 

Making decisions about economic evaluations  

Steven et al (2019) stated that HEE can be approached in 

a number of ways. They identified a range of approaches to 

compare the costs of health care services and possible cost 

savings which observe the consequences of an intervention 

and the effectiveness of that same intervention through a 

lens of outcomes that are valued patients, payers and 

providers, or which align with widely used global utility 

measures.48 They specified that the value of a prosthetic 

care intervention could be assessed using a range of cost-

benefit, cost-consequence, cost-effectiveness and cost-

utility analyses considering valuations of costs (e.g., 

monetary units) and a range of benefits. Ijzerman and 

Steuten (2011) specified that no single method will produce 

the right information for all decision makers. Each method 

has advantages and disadvantages and work for specific 

applications, as opposed to all applications.37 They 

suggested that a toolbox of methods must be used. 

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ISSN: 2561-987X 
HEALTH ECONOMIC EVALUATIONS OF PROSTHETIC CARE INNOVATIONS   

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Unfortunately, the multitude of HEEs often leave promoters 

making challenging decisions around allocation of sufficient 

resources toward the most relevant HEE approach at a 

given point of an innovation development. Facilitating this 

decision-making process would start with an overview of the 

trends and specific ways HEEs can be done at various 

stages of development of an innovation.  

CURRENT TRENDS IN HEALTH 

TECHNOLOGY EVALUATIONS  

This second section (A) reviewed generic pathways to 

assess health economic consequences of a new treatment 

at a given stage of product development and clinical 

acceptance and (B) highlighted selected studies that 

followed these pathways to assess prosthetic care 

interventions.  

Key concepts of health economic evaluations  

As described in APPENDIX 1, HEE include, but not limited 

to, cost-effectiveness analyses (CEA) or cost-utility 

analyses (CUA). These terms are often used 

interchangeably although they are technically looking at 

different types of utilities. CEAs are concerned with a 

particular functional outcome of a treatment (e.g., walking 

speed). CUAs rely on self-reported quality of life status 

measured using standard surveys such as EQ-5D or 36-

Item Short Form Survey (SF36). CUAs comparing usual and 

new treatments involve incremental cost-utility ratio (ICUR) 

based on incremental costs and utilities over time that could 

be compared to cost-effectiveness (CET) or, more often, 

willingness-to-pay (WTP) thresholds.1,48,55 

Patient-centred assessments of global health-related 

quality of life might be influenced by prosthetic care to a 

certain extent. Therefore, these metrics might reflect only 

partially the benefits of a prosthetic intervention. However, 

outcomes of CUA reported in monetary units per quality-

adjusted life-year (QALY) can be easily compared across 

other medical interventions or disease states. CUAs are 

commonly used to facilitate effective communication among 

healthcare professionals.48,56,57 

Health economic evaluations pathways 

Promoters can be informed by an abundance of health 

economic research focusing on a broad range of 

fundamental and applied HEEs issues that could be more 

or less relevant (e.g., difference between pharmaceutical 

and medical technologies).54,58 Some studies provided 

valuable insights into ways outcomes of HEEs can facilitate 

the approval process of an innovation by a particular 

governmental healthcare system (e.g., Australian).53,54,59-61 

Others explained the basic concepts of HEEs to clinicians 

and prosthetic care providers.48,56,57 Several landmark 

studies presented prosthetic-specific HEEs.21,50-52,61-74 

Two studies were of particular interest because they can 

assist promoters to make an educated decision when 

choosing an HEE accordingly to the level of innovation 

development. Ijzerman and Steuten (2011) systematically 

described that early, preliminary and full CUAs can be 

conducted at the early, mid and late stage of clinical 

acceptance of any medical treatment, respectively.37 More 

recently, new insights were provided by Kannenberg and 

Seidinger (2019) who explained how these three types of 

CUAs should also be performed by prosthetic 

manufacturers at early, mid and late phase development of 

a prosthetic product.38 The authors indicated that CUA 

during the product’s life cycle is beneficial in three ways. It 

allows potential cost-effectiveness to be estimated and 

included in  investment decision processes and mitigates 

the risk of investing in technology  unlikely to  be cost-

effective. It helps to prioritize between competing cost-

effective concepts or technologies. It  facilitates the 

identification of parameters having the largest impact on the 

likely cost-effectiveness of the product to be identified in 

order to best manage limited research funds.38 

Figure 2 gives an overview synthesizing both approaches. 

Decision uncertainty and strength of evidence were 

suggested for early, preliminary and full CUAs during early, 

mid and late phase of product development (manufacturer’s 

perspective) and clinical acceptance (healthcare’s 

perspective) of prosthetic care innovations, respectively.  

Next, the general principle, expected capacity to address 

Consolidated Health Economic Evaluation Reporting 

Standards (CHEERS) and Consensus Health Economic 

Criteria (CHEC) extended checklists, typical strengths and 

weaknesses as well as selected examples of prosthetic-

focused CUAs.75-77 is briefly described.  The decision was 

made to  present the CUAs as they historically gained 

recognition starting from full, to preliminary and early CUAs 

rather than following the sequential timeline of their 

implementation. Appraisal of each type of CUAs using the 

CHEERS and CHEC-extended checklists were detailed in 

Supplementary material. 

Full cost-utility analyses   

Traditionally, mainstream HEEs involved comprehensive or 

“full” CUAs essentially produced when innovations are 

gaining clinical acceptance after commercialisation. Full 

CUAs can be conducted from  societal and/or healthcare 

perspectives. These CUAs usually rely on primary costs 

extracted from financial records expressed in monetary 

units as well as utilities measured by quality of life surveys 

expressed in QALY for cohorts of participants over an 

extended period of time (APPENDIX 1).48,50-53,62,78,79 

Costs, utilities and ICURs are projected using Bayesian or 

Markov models based on plausible information extracted 

from primary studies for a series of scenarios over scalable 

time horizons (e.g., Years, decades, 

lifetime).1,37,63,64,70,78,80,81  

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It was postulated that conventional full CUAs should 

address strongly all items of the CHEERS and CHEC-

extended checklists (Table 1,Table 2).  

Modelling CUAs can be comprehensive because of the 

breadth (e.g., scenarios) and depth (e.g., time horizon) of 

their analysis. Furthermore, uncertainty and sensibility of 

outcomes, shown by the size of the errors around the point 

estimates due to data sources (e.g., sample size) and/or to 

the process of evaluation (APPENDIX 1), tend to be well 

worked out and, possibly, relatively low compared to early 

and preliminary CUAs.82 Therefore, full CUA provide strong 

evidence supporting robust recommendations considered 

by decision makers (e.g., approval for funding). 

However, modelling CUAs require substantial resources. 

Building models is labour intensive (e.g., determine 

scenarios, test assumptions). More importantly, 

Kannenberg and Seidinger (2019) noted the necessity of 

requiring the inclusion of outcome parameters, like health-

related quality of life, in these models.38 This means that full 

CUAs produce their best outcomes when sufficient costs 

and utilities are known for large cohorts over an extended 

length of time in a given jurisdiction (e.g., within-trial and 

beyond-trial horizon studies).83 Evidence-based 

Weak 

D
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S
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Low 

High 

Case-series 

Proof of utility 

Clinical trial 

Cohort study 

Randomized 

clinical trial 

Early 

Stage 

Health Technology Assessment 

Mid 

Stage 

Late 

Stage 

Full 

CUA 
Pre 

CUA 

Early 

CUA 

Strong 

Proof of safety 

Proof of efficacy 
Clinical acceptance 

Health Economy Evaluation 

Product development  Clinical acceptance 

Figure 2: Overview of expected grading of decision uncertainty (i.e., high to low) and strength of evidence (i.e., weak to strong) of early, 

preliminary (Pre) and full cost-utility analysis (CUA) conducted during typical health technology assessments at early, mid and late phase 

of product development (manufacturer’s perspective) and clinical acceptance (healthcare’s perspective) of prosthetic care innovations, 

respectively. 

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developments of new interventions takes time, particularly 

when the recommended clinical timelines are followed to 

demonstrate efficiency and safety (e.g., clinical trial 

registration, ethics approval, surgical learning curve, 

observation times, design of rehabilitation program). 

Several years might be needed to gather the costs and 

utilities required to complete primary and modelling CUAs. 

Consequently, mainstream CUAs can hardly inform 

promoters timely. Lack of timeliness is even more 

problematic with new prosthetic care technologies that are 

more susceptible to be superseded after five years.[60] 

Gallego et al (2011) described decisions to approve 

technology by committees and regulatory bodies, such as 

the Australian Medical Services Advisory Committee, 

typically occurs after the technology has evolved or is 

already commonly being used in practice.60 Ijzerman and 

Steuten (2011) also noted the problems with this approach, 

warning that many design decisions (e.g. target population, 

use setting, technology design features such as connectivity 

with data infrastructure, seamless integration with 

complementary technology, etc) are made in the early 

stages of product development and are difficult, expensive 

and/or impossible to change at a later date.37 

Several studies used a full CUA to assess consequences of 

the provision of socket based solution including advanced 

prosthetic components such as microprocessor-controlled 

knees and energy storing and return feet as well as socket-

free solutions including bone-anchored prostheses.21,61,63-

74  

Preliminary cost-utility analyses   

The issue of timeliness of full CUAs could be addressed by 

performing preliminary CUAs of innovations that could take 

place sometimes around the mid-stage of product 

development when clinical usage is still limited to small 

cohorts. Preliminary CUA is an option “in-between” early 

and full CUAs that considered innovations with a broad 

range of development status. Therefore, preliminary CUAs 

can be conducted using a wide spectrum of methods. They 

can involve primary data of actual (e.g., financial records) 

and/or simulated (e.g., purposely created schedules) costs 

expressed in monetary units as well as measured (e.g., 

quality of life surveys) and/or guesstimated (e.g., literature) 

utilities expressed in QALY for cohorts of participants over 

a somewhat lengthy time horizon.48,50-52,62,78,79  

The assumption was made that typical preliminary CUAs 

have a weak and moderate capacity to address 9 (33%) and 

8 (30%) of items in the CHEERS checklist, including 7 

(44%) and 6 (38%) of items in the Methods as well as 2 

(40%) and 2 (40%) of items in the Results sections, 

respectively (Table 1). It was estimated that preliminary 

CUAs should be capable to address 11 (58%) of items in 

the CHEC-extended checklists (Table 2).  

Resources needed to conduct preliminary CUAs could 

varied depending on the sources of data considered. 

Estimating costs from schedules and utilities from literature 

might require less resources than extracting costs from 

financial systems and utilities from a survey for a cohort of 

convenient sample size. Preliminary CUAs can provide 

some indications of probable consequences of innovations. 

Practically, preliminary CUAs can generate primary 

information, in part or in whole, useful for modelling CUAs 

(e.g., costs and utilities estimates, scenario drafting).  

However, preliminary CUAs are usually built around 

substantial assumptions based on best-estimates of costs 

and utilities at the time. Typical preliminary CUAs are 

characterised by narrow perspective, simple scenarios, and 

time horizons tentatively shorter than full CUAs. Further 

limitations are inherent to the mismatch of costs and utilities 

from incongruous jurisdictions, onsets and post-operative 

timelines. For example, actual costs extracted from an 

healthcare financial system over several years might be 

considered against estimated utilities based on studies 

performed in other countries measuring quality of life six 

months after the intervention.50-52 Finally, uncertainty and 

sensibility of preliminary CUAs might be only loosely 

considered and reported. Altogether, the weight of these 

limitations on the strength of evidence is less known 

weakening the recommendations. Unfavourable outcomes 

of preliminary CUAs might, at least, question and, possibly, 

stop further product commercialization and clinical 

considerations. A decision must be made whether 

favourable outcomes are deemed sufficient to pursue and 

eventually, readjust further developments.  

Recent examples of preliminary CUAs of innovations looked 

at the benefits of transfemoral and transtibial bone-

anchored prostheses from government prosthetic care 

perspective.50-53 

Early cost-utility analyses   

Preliminary CUAs can provide timelier assessment than full 

CUAs. Nonetheless, there is a current trend in health 

economic literature arguing that preliminary CUAs are yet to 

provide sufficiently timely assessment of innovations. 

Hence, the promotion of early CUAs, also called “iterative 

economic evaluations” or “very early HTA” by Ijzerman and 

Steuten (2011), which pointed out that attempts have 

already been made, using “horizon scanning systems”, to 

include new, emerging technologies into health policy as it 

is developed. Other authors have referred to this as the use 

of  “early warning systems”.37 Early CUAs tend to be 

constructed like preliminary CUAs but they rely more heavily 

on sparser costs and utilities data as well as sketchier 

assumptions. These analyses tend to be based on best 

guestimates of most likely costs and utilities collected with 

case-series studies and/or extracted from the literature 

often produced outside the relevant jurisdiction.  

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Table 1: Expected capacity (i.e., weak, moderate, strong) of typical early, preliminary (Pre) and full cost-utility analysis (CUA) to address the 

27-item of the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. 

Section and item number Recommendation  

CUA 

Early Pre Full 

Title and abstract 

 Title   1 
Identify the study as an economic evaluation or use more specific terms such as 
“cost-effectiveness analysis”, and describe the interventions compared. 

Strong Strong Strong 

Abstract  2 
Provide a structured summary of objectives, perspective, setting, methods 
(including study design and inputs), results (including base case and uncertainty 
analyses), and conclusions. 

Strong Strong Strong 

Introduction 

Background and 
objectives 

3 
Provide an explicit statement of the broader context for the study. 
Present the study question and its relevance for health policy or practice 
decisions. 

Strong Strong Strong 

Methods 

Target 
population and 
subgroups 

4 
Describe characteristics of the base case population and subgroups analysed, 
including why they were chosen. 

Moderate Moderate Strong 

Setting and 
location 

5 
State relevant aspects of the system(s) in which the decision(s) need(s) to be 
made. 

Moderate Strong Strong 

Study 
perspective 

6 Describe the perspective of the study and relate this to the costs being evaluated. Weak Moderate Strong 

Comparators 7 
Describe the interventions or strategies being compared and state why they were 
chosen. 

Weak Moderate Strong 

Time horizon 8 
State the time horizon(s) over which costs and consequences are being 
evaluated and say why appropriate. 

Moderate Moderate Strong 

Discount rate 9 
Report the choice of discount rate(s) used for costs and outcomes and say why 
appropriate. 

Weak Weak Strong 

Choice of health 
outcomes 

10 
Describe what outcomes were used as the measure(s) of benefit in the evaluation 
and their relevance for the type of analysis performed. 

Weak Weak Strong 

Measurement of 
effectiveness 

11a 
Single study-based estimates: Describe fully the design features of the single 
effectiveness study and why the single study was a sufficient source of clinical 
effectiveness data. 

Weak Weak Strong 

11b 
Synthesis-based estimates: Describe fully the methods used for identification of 
included studies and synthesis of clinical effectiveness data. 

Weak Weak Strong 

Measurement 
and valuation of 
preference 
based outcomes 

12 
If applicable, describe the population and methods used to elicit preferences for 
outcomes. 

Weak Weak Strong 

Estimating 
resources and 
costs 

13a 

Single study-based economic evaluation: Describe approaches used to estimate 
resource use associated with the alternative interventions. Describe primary or 
secondary research methods for valuing each resource item in terms of its unit 
cost. Describe any adjustments made to approximate to opportunity costs. 

Weak Weak Strong 

13b 

Model-based economic evaluation: Describe approaches and data sources used 
to estimate resource use associated with model health states. Describe primary 
or secondary research methods for valuing each resource item in terms of its unit 
cost. Describe any adjustments made to approximate to opportunity costs. 

Weak Weak Strong 

Currency, price 
date, and 
conversion 

14 

Report the dates of the estimated resource quantities and unit costs. Describe 
methods for adjusting estimated unit costs to the year of reported costs if 
necessary. Describe methods for converting costs into a common currency base 

and the exchange rate. 

Strong Strong Strong 

Choice of model 15 
Describe and give reasons for the specific type of decision analytical model used. 
Providing a figure to show model structure is strongly recommended. 

Moderate Strong Strong 

Assumptions 16 
Describe all structural or other assumptions underpinning the decision-analytical 
model. 

Weak Moderate Strong 

Analytical 
methods 

17 

Describe all analytical methods supporting the evaluation. This could include 
methods for dealing with skewed, missing, or censored data; extrapolation 
methods; methods for pooling data; approaches to validate or make adjustments 
(such as half cycle corrections) to a model; and methods for handling population 
heterogeneity and uncertainty. 

Weak  Moderate Strong 

 

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Table 1 (continued).  

Section and item number Recommendation 
CUA 

Early Pre Full 

Results      

Study 
parameters 

18 

Report the values, ranges, references, and, if used, probability distributions for all 
parameters. Report reasons or sources for distributions used to represent 
uncertainty where appropriate. Providing a table to show the input values is 
strongly recommended. 

Weak Moderate Strong 

Incremental 
costs and 
outcomes 

19 
For each intervention, report mean values for the main categories of estimated 
costs and outcomes of interest, as well as mean differences between the 
comparator groups. If applicable, report incremental cost-effectiveness ratios. 

Strong Strong Strong 

Characterising 
uncertainty 

20a 

Single study-based economic evaluation: Describe the effects of sampling 
uncertainty for the estimated incremental cost and incremental effectiveness 
parameters, together with the impact of methodological assumptions (such as 
discount rate, study perspective). 

Weak Moderate Strong 

20b 
Model-based economic evaluation: Describe the effects on the results of 
uncertainty for all input parameters, and uncertainty related to the structure of the 
model and assumptions. 

Weak Weak Strong 

Characterising 
heterogeneity 

21 

If applicable, report differences in costs, outcomes, or cost effectiveness that can 
be explained by variations between subgroups of patients with different baseline 
characteristics or other observed variability in effects that are not reducible by 
more information. 

Weak Weak Strong 

Discussion           

Study findings, 
limitations, 
generalisability, 
and current 
knowledge 

22 
Summarise key study findings and describe how they support the conclusions 
reached. Discuss limitations and the generalisability of the findings and how the 
findings fit with current knowledge. 

Strong Strong Strong 

Other 

Source of 
funding 

23 
Describe how the study was funded and the role of the funder in the identification, 
design, conduct, and reporting of the analysis. Describe other non-monetary 
sources of support. 

Strong Strong Strong 

Conflicts of 
interest 

24 

Describe any potential for conflict of interest of study contributors in accordance 
with journal policy. In the absence of a journal policy, we recommend authors 
comply with International Committee of Medical Journal Editors 
recommendations. 

Strong  Strong Strong 

 
Table 2: Expected capacity (i.e., yes, no) of typical early preliminary (Pre) and full cost-utility analysis (CUA) to address the 19-item Consensus 

Health Economic Criteria (CHEC) extended checklist. 

Item Questions 
CUA 

Early Pre Full 

1 Is the study population clearly described? Yes Yes Yes 

2 Are competing alternatives clearly described? Yes Yes Yes 

3 Is a well-defined research question posed in answerable form? Yes Yes Yes 

4 Is the economic study design appropriate to the stated objective? Yes Yes Yes 

5 Is the chosen time horizon appropriate in order to include relevant costs and consequences? No No Yes 

6 Is the actual perspective chosen appropriate? Yes Yes Yes 

7 Are all important and relevant costs for each alternative identified? No No Yes 

8 Are all costs measured appropriately in physical units? Yes Yes Yes 

9 Are costs valued appropriately? No No Yes 

10 Are all important and relevant outcomes for each alternative identified? No No Yes 

11 Are all outcomes measured appropriately? No No Yes 

12 Are outcomes valued appropriately? No No Yes 

13 Is an incremental analysis of costs and outcomes of alternatives performed? No Yes Yes 

14 Are all future costs and outcomes discounted appropriately? No No Yes 

15 Are all important variables, whose values are uncertain, appropriately subjected to sensitivity analysis? No No Yes 

16 Do the conclusions follow from the data reported? Yes Yes Yes 

17 Does the study discuss the generalizability of the results to other settings and patient/client groups? Yes Yes Yes 

18 Does the article indicate that there is no potential conflict of interest of study researcher(s) and funder(s)? Yes Yes Yes 

19 Are ethical and distributional issues discussed appropriately? Yes Yes Yes 

 

 

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It was assumed that usual early CUAs have a weak capacity 

to address 15 (56%) of items in the CHEERS checklist 

including 11 (69%) of items in the Methods as well as 4 

(80%) of items in the Results sections (Table 1). Preliminary 

CUAs might be incapable to address up to 9 (47%) of items 

in the CHEC-extended checklists (Table 2).  

Early CUAs are affordable and timely. They could help to 

reduce or validate assumptions subsequently used in 

preliminary or modelling CUAs. Perhaps, the most valuable 

return on investment of early CUAs is to provide insight into 

the viability of the product and worthiness of the clinical 

introduction on an innovation, as described by Kannenberg 

and Seidinger (2019).38  

As expected, outcomes of early CUAs are likely to have high 

uncertainty and sensibility leading to low level of evidence 

and only tentative recommendations. Early evidence of 

potential CUA might fast-track on-going innovation 

development. Limited prospects of CUA might raise 

questions about further allocation of resources to a product 

that has, ultimately, minimal chance to meet payer’s 

expectations.  

GAPS IN EARLIER HEALTH ECONOMIC 

EVALUATIONS  

This last section (A) presented the current consensus and 

knowledge gaps around earlier HEEs and (B) highlighted 

opportunities for developments of a basic framework of 

preliminary CUA. 

Benefits of earlier health economic evaluations 

There is consensus around the weaknesses of full CUAs 

(e.g., lack of timeliness, resource-intensive) and strengths 

of early and preliminary CUAs, summarised in Table 3. 

Earlier CUAs have the potential to assist promoters to: 

• Identify evidence gaps and headroom for improvements 

that generate insights into potential capacity of an 

innovation to alleviate the financial burden of prosthetic 

fittings.37,50-52 

• Educate the design of primary and modelling studies 

including the planning (e.g., calculate statistical power, 

determine of sample size, obtain ethics approval), 

collection (e.g., mine data from financial records, design 

    Table 3: Typical strengths and weaknesses of the early, preliminary, and full cost-utility analyses (CUA) of prosthetic care innovations.   

                   Strengths               Weaknesses 

Full CUA  

• Address strongly all 27 CHEERS items 

• Capable to address all 19 CHEC items  

• Comprehensive list of scenarios 

• Scalable time horizon  

• Strong understanding of uncertainty 

• Strong understanding of sensibility 

• High level of evidence 

• Strong recommendations 

• Need of primary costs and utilities data  

• Require substantial resources  

• Lack of timeliness 
 

Preliminary CUA 

• Address strongly 37% of CHEER items  

• Capable to address 58% of CHEC items 

• Timeliness of information 

• Identify evidence gaps 

• Provide headroom for improvement 

• Capable to generate primary data 

• Educate design of full CUAs 

• Fast-track approval  

• Address weakly 33% of CHEER items  

• Uncapable to address 42% of CHEC items  

• Variability of resources required 

• Build around substantial assumptions 

• Rely on best-known evidence 

• Consider narrow perspective 

• Consider plausible scenarios,  

• Consider mid-term time horizon 

• Mismatch costs and utilities data 

• Limited understanding of uncertainty 

• Limited understanding of sensitivity 

• Moderate level of evidence 

• Moderate strength of recommendations 

Early CUA 

• Address strongly 30% of CHEER items  

• Capable to address 53% of CHEC items 

• Require little resources  

• Timeliness of information 

• Early insights into product viability 

• Early insights into clinical worthiness  

• Identify evidence gaps  

• Provide headroom for improvement 

• Educate design of preliminary CUAs 

• Facilitate fast-track approval 

• Address weakly 56% of CHEER items  

• Uncapable to address 47% of CHEC items  

• Build around substantial assumptions 

• Rely on best-known evidence 

• Consider narrow perspective 

• Consider hypothetical scenarios,  

• Consider short-term time horizon 

• Rely of expected costs and utilities data 

• Low understanding of uncertainty 

• Low understanding of sensitivity 

• Low level of evidence 

• Low strength of recommendations 

 

 

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databases) and analysing (e.g., build model, draft 

scenarios, choose assumptions).47  

• Fast-track approval from governing bodies like 

Australian Medical Services Advisory Committee. 

Gallego et al (2011) said that earlier CUAs can help to 

prioritize in which order new technologies are evaluated 

and allows for the fast-tracking of technologies which 

either have a least potential for harm or which have a 

great potential to benefit patients.54,60 

Obstacles to earlier health economic evaluations 

Ijzerman and Steuten (2011) pointed out that the emerging 

field of HTA research will likely gain prominence as it will 

help navigate the increasingly complex trade-offs that must 

be considered when making investments in medical product 

development and ensuring access to those products.37 

However, earlier CUAs are far from being widely considered 

when developing new prosthetic solutions. Several 

obstacles must be overcome before earlier and, more 

particularly, preliminary CUAs of prosthetic care innovations 

would be routinely carried out by promoters. 

One critical obstacle is the abundance of methods. Ijzerman 

and Steuten (2011) listed ten quantitative methods that 

could be used in earlier HTA (e.g., payback from research 

analysis, strategic business cases, health impact 

assessment, multi-criteria decision methods, choice-based 

preference methods, real options analysis, early health 

economic modelling, horizon scanning systems, clinical trial 

simulation, value-of-information analysis).37 

Another obstacle is the multiple pathways for HEE relying 

on the same level of clinical evidence of utilities (Figure 2). 

Logically, early and full CUAs are indicated at early stage 

and after clinical acceptance, respectively. Initial clinical 

evidence provided by proof of utility and case-series could 

be used to perform an early and preliminary CUAs. Stronger 

evidence gathered during cohort study and clinical trial 

might be deemed sufficient to conduct a preliminary or full 

CUAs.  

Disparities of methods and constructs of earlier CUAs (e.g., 

perspective, time horizon, discount, uncertainty, sensibility) 

have ripple effects limiting implementation of earlier CUAs. 

Cross-comparing outcomes of earlier CUAs between 

innovations might be challenging to interpret. 

Generalization of outcomes across healthcare 

organisations might be limited. Earlier CUAs might show a 

broad level of quality when appraised with standard 

CHEERS and CHEC-extended checklists, primarily 

designed for full CUAs (Table 1, Table 2). Altogether, 

disparity of outcomes also makes earlier CUAs scoring 

modestly in these checklists less likely to be published. The 

result of this is a sparsity of publications in prosthetic-

focused scientific journals, let alone heath economics 

journals, the latter of which are inclined to consider that 

socio-economic research in prosthetics is for a niche 

audience. Literature review and meta-analyses of health 

economic evaluations failing to stratify publications 

accordingly to the three types of CUAs might appraise 

unfavourably the contribution of earlier CUAs.84,85 

Therefore, this review might skew the perception on the 

overall quality of health economic evaluations of prosthetic 

care. Earlier CUAs might score less not because they are 

poorly done but because they are dealing with more 

unreliable datasets.  

Opportunities for basic framework of preliminary CUA  

On a one side, every innovation is different. Each healthcare 

organisation has particular expectations. Promoters might 

choose a specific pathway for a given CUA depending on 

their confidence to make valid assumptions. Therefore, a 

preliminary CUA of an innovation could be unique. 

One the other side, provision of prosthetic care follows a 

rather standardized process. Reimbursement are often 

made for categories of components (e.g., microprocessor-

controlled knees.14 Prosthetists performed series of well-

identified specific tasks related to prosthetic fitting (e.g., 

fitting of socket, choice of components, alignment of 

prosthesis), assessment of outcomes (e.g., comfort, 

stability, mobility) and reporting to payers (e.g., 

reimbursement claims).47 Indeed, each of these tasks is 

sufficiently codified to be individually supported by 

healthcare organisations (e.g., L-Codes). This means that 

most preliminary CUAs relying on estimated rather than 

primary costs could apply a template of schedule of 

allowable expenses. This typical matrix can present costs at 

the intersections of list of tasks in rows and timeline of 

interventions in columns (APPENDIX 1). Ideally, disruptive 

and economical innovations changing best prosthetic care 

practice should affect a schedule by reducing the price tag 

and/or the frequency of one or more tasks. 

Furthermore, standard assessments are commonly used to 

quantify outcomes of prosthetic fittings using self-reported 

satisfaction (e.g., Orthotics and Prosthetics User's Survey, 

Quebec User Evaluation of Satisfaction with Assistive 

Technology, socket prosthetic comfort score), physical 

tasks (e.g., Berg Balance Scale, timed get-up and go, 

walking speed, 2-minute walk, 6-minute walk, functional 

ambulation profile, amputee mobility predictor with 

prosthesis) as well as specific (e.g., Questionnaire for 

Persons with a Transfemoral Amputation) and generic (e.g., 

EQ-5D, SF36) health-related quality of life with an 

innovation.12,13,29,86  

Altogether, organisation of the delivery and assessment of 

prosthetic care might be sufficiently transferable across 

innovations to consider a more uniform approach to 

preliminary CUAs.50-52 This creates opportunities to explore 

the development of a basic framework including set 

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constructs (e.g., perspective, time horizon, discount) and 

practical recommendations (e.g., funding cycles) specific to 

preliminary CUAs of the prosthetic care innovations 

(APPENDIX 1). This new approach to a preliminary CUA 

has the potential to simplify the selection of methods, 

standardise outcomes, ease comparisons between 

innovations and streamline pathways for adoption while 

facilitating the production of a body of literature on prosthetic 

health economics.    

CONCLUSION  

This work showed that promoters must make complex 

decisions when attempting to establish the socio-economic 

values of prosthetic care innovations. It is commonly 

acknowledged that a unique type of CUA could not be 

applied at every stage of development of an innovation. 

Preliminary CUAs of innovations at the mid-stage of 

development is particularly valuable but challenging. 

Boundaries delineating preliminary CUAs from early and full 

CUA might be blurry pushing promoters to consider a wide 

range of methods.  

The outcomes suggest that there are opportunities for 

collective design of a basic framework of a preliminary CUA 

of prosthetic care innovations. However, reaching 

consensus around a framework can be challenging 

because there is no formal forum capable to organise 

discussions outside of usual scientific peer-review 

channels. There is a need for an ad-hoc reference group 

involving promoters and heath economists specialized in 

prosthetics and medical aids. Ideally, this working group 

should be hosted by international (e.g., World Health 

Organisation Standards for Prosthetics and Orthotics 

Service Provision, International Society for Prosthetics and 

Orthotics) or national (e.g., American Orthotic and 

Prosthetic Association, Center for Orthotic and Prosthetic 

Learning and Outcomes/Evidence-Based Practice) 

governing bodies. Its missions could be to develop 

guidelines and, possibly, standards of HEEs of prosthetic 

care interventions including preliminary CUAs frameworks 

(e.g., set constructs, practical recommendations).  

Ultimately, a wide adoption of a this collegial preliminary 

CUA framework will, hopefully, contribute to promote the 

routinely used preliminary CUA. It is anticipated that this 

framework should facilitate access to economical prosthetic 

care solutions improving the life of individuals suffering from 

limb loss worldwide.  

CALL TO ACTION 

• Gather an ad-hoc reference group capable of (A) 

monitoring the current trends in HEEs of new healthcare 

technologies, (B) develop guidelines and, possibly, 

standards of HEEs of prosthetic care interventions, (C) 

promote the adoption of these guideline (e.g., 

publications of position papers, presentations at 

conferences). 

• This working group could facilitate discussions between 

promoters of prosthetic care innovations around the use 

and validation of preliminary CUAs frameworks.  

• Practically, these discussions should focus on the 

development of basic framework of a preliminary CUAs, 

more particularly set constructs and practical 

recommendations.  

ACKNOWLEDGEMENTS 

The author wishes to express his gratitude to Debra Berg and 

Gregory Merlo for their support. 

DECLARATION OF CONFLICTING 

INTERESTS 

The author is in the view that these competing interests do not 

conflict with the content of this manuscript. Laurent Frossard, 

Director and Chief Scientist Officer of YourResearchProject Pty Ltd, 

has worked as consultant for several organisations on non-related 

educational programs and projects of research focusing on 

recording loading data, developing of database to record clinical 

outcomes as well as drafting grants and manuscripts for Cognitive 

Institute, Exercise & Sports Science Australia, Griffith University, 

iPug Pty Ltd, Middlesex University, New Zealand Artificial Limb 

Service, Osseointegration Group of Australia Pty Ltd, OSSUR, 

Poly-Orthodox International, Queensland Artificial Limb Service, 

Queensland University of Technology, Return to Work-South 

Australia, South Australia Health, Tequir S.L, University of the New 

South Whales, University of the Sunshine Coast. 

SOURCES OF SUPPORT 

This study was funded by YourResearchProject Pty Ltd. 

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preliminary study. J Prosthet Orthot. 2011; 23(1): 2-11. DOI: 

10.1097/JPO.0b013e318207914c 

 

AUTHOR SCIENTIFIC BIOGRAPHY 

Dr Laurent Frossard is a bionic 

limbs scientist who is passionate 

about developing ground-

breaking prosthetic solutions to 

improve the lives of individuals 

suffering from limb loss. He is 

internationally recognized as a 

researcher and an independent 

expert for his unique expertise in 

bionic limbs. He approaches 

bionic solutions from a holistic 

perspective, by integrating the 

prosthetic biomechanics, clinical 

benefits, service delivery, and health economics. Dr Frossard has 

over 25 years of experience, both in academia and in private 

industries in Australia, Canada, and Europe. He has collaborated 

with over 100 organizations worldwide. He is currently a Professor 

of bionics at the Griffith University, the Director and Chief Scientist 

Officer at YourResearchProject Pty Ltd, and Adjunct Professor at 

the Queensland University of Technology and the University of 

Sunshine Coast in Australia.   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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APPENDIX 1: Definition of key terms 

Basic framework of preliminary cost-
utility analysis 

Generic canvas of preliminary cost-utility analysis including set constructs specific to prosthetic care 
innovations 

Cost-effectiveness analysis 
Form of economic analysis that compares the relative costs expressed in monetary value and particular 
functional outcome of a treatment (e.g., walking speed) 

Cost-utility analysis 
Form of economic analysis that compares the relative costs expressed in monetary value and health effects of 
various interventions converted into utilities expressed quality-adjusted life-year 

Health economic evaluation 
Comparative assessment of costs and outcomes of alternative health care technologies or health strategies 
providing incremental cost-outcome ratio, the relation of the estimated additional costs and the estimated 
additional outcome saved or lost by using an alternative health care technology 

Health technology assessment 
Systematic evaluation of the properties and effects of a health technology, addressing the direct and intended 
effects of this technology, as well as its indirect and unintended consequences, and aimed mainly at informing 
decision making regarding health technologies 

Modelling cost-utility analysis 
Form of analysis projecting of cost-utility based on decision-analytic models involving Bayesian or Markov 
models generally using plausible information extracted from primary studies 

Primary cost-utility analysis 
Form of analysis relying on actual costs extracted from financial records expressed in monetary units or actual 
utilities measured by quality of life surveys converted into quality-adjusted life-year 

Promoters of prosthetic care 
interventions 

Groups developing and encouraging prosthetic care interventions including individuals suffering from limb loss 
(users’ perspectives), providers of prosthetic solutions (manufacturers’ perspective), rehabilitation and 
prosthetic specialists (clinicians’ perspective) and administrators of healthcare organisations (taxpayers 
perspective) 

Prosthetic care innovation 
New intervention susceptible to alleviate clinical shortcomings and financial burden of current prosthetic fitting 
options 

Schedule of allowable expenses 
Matrix of costs (monetary units of talk) at the intersection of rows corresponding to lists of tasks (type of 
expenses) and columns corresponding to onsets of tasks (time of expenses) 

Uncertainty and sensibility of health 
economic evaluations 

The size of the errors around the estimates of costs and utilities due to data sources (e.g., sample size) and/or 
to the process of evaluation (Markov modelling),    

 

 

 

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