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VOLUME 4, ISSUE 2  
 2021 

 

STAKEHOLDER  PERSPECTIVES 

Fiedler G, Schikorra A. A brief introduction to game theory and its potential implications for the economics of orthotics & prosthetics. Canadian Prosthetics & 

Orthotics Journal. 2021; Volume 4, Issue 2, No.18. https://doi.org/10.33137/cpoj.v4i2.36661 

This article has been invited and reviewed by Co-Editor-In-Chief, Dr. Silvia Ursula Raschke. 
English proofread by: Karin Ryan, M.A., B.Sc., P.T. 
Managing Editor: Dr. Hossein Gholizadeh 
 

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1 

Fiedler G, Schikorra A. A brief introduction to game theory and its potential implications for the economics of orthotics & prosthetics. Canadian Prosthetics & 
Orthotics Journal. 2021; Volume 4, Issue 2, No.18. https://doi.org/10.33137/cpoj.v4i2.36661 

 

 

 
STAKEHOLDER  PERSPECTIVES 

 

A BRIEF INTRODUCTION TO GAME THEORY AND ITS POTENTIAL IMPLICATIONS FOR THE 

ECONOMICS OF ORTHOTICS & PROSTHETICS 

Fiedler G.1 *, Schikorra A.2 
 

 

1 University of Pittsburgh, Department of Rehabilitation Science and Technology, Pittsburgh, USA. 
2 University of Pittsburgh, Department of Mathematics, Pittsburgh, USA. 

 

 

 

 

  

 

 

 

 

 

BACKGROUND 

The costs of health care provision in the United States is 

estimated to exceed $4 trillion (T) in the year 2020.1 More 

than half of this amount is expended for hospital care 

($1.3T) and physician and clinical services ($794B). 

Prescription drugs account for $358B, or about 9%. By 

comparison, only $62B, representing about 1.5% of the 

total, go into durable medical equipment of which orthotics 

and prosthetics (O&P) devices are a subsection.1 This 

distribution correlates with the size of the involved industries 

and their respective lobbying budgets. Data from the U.S. 

Bureau of Labor Statistics suggests that more than 750,000 

physicians and more than 320,000 pharmacists were 

employed in 2019, which compares to a total of 10,000 O&P 

jobs nationwide.2 According to the Center for Responsive 

Politics, the pharmaceutical industry spent more than 

$300M on lobbying in 2020, followed by Hospitals/Nursing 

Homes with more than $100M.3 By comparison, the O&P 

Alliance, which is  representing  the  interests  of  the  main  

 

professional O&P organizations, had a lobbying budget of 

$60,000.3 Another measure of the disparity between O&P 

and other health professions is the amount of scientific 

evidence that informs their practice. The comparably small 

size of the O&P field corresponds with a small number of 

researchers working in this field and the associated number 

and quality of scientific publications.4-6 

Overall, of course, this apparent imbalance is in large parts 

reflective of the patient populations tended to by the 

respective specialists. However, on the scale of individual 

patient cases there is, nonetheless, an overlap of 

competencies and a need for the entire health care team to 

collaboratively decide on the best treatment. Additional 

stakeholders include the patient and/or their family, as well 

as third-party payers, such as private and institutional health 

insurers or respective government agencies. If, in the 

example of a progressing orthopedic condition, it is to be 

decided whether conservative treatment or surgical 

intervention is called for, a variety of explicit and implicit 

interests of these stakeholders need to be reconciled. The 

patient is likely to prioritize the subjectively most promising 

and convenient treatment irrespective of the costs, whereas 

the insurer is interested in the most cost-effective treatment, 

which ideally includes a consideration of long-term costs. 

 
OPEN  ACCESS Volume 4, Issue 2, Article No.18. 2021 

 

 

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

 

ABSTRACT 

The economic viability of Orthotics & Prosthetics (O&P) service provision is an important concern 

for policy makers, patients, and practitioners. Against the background of limited funds that can 

be distributed for healthcare expenses overall, it is critical to identify the most cost-effective 

treatment options within and across disciplines, including surgical and pharmacological 

interventions. When those decisions are being negotiated, whether in the context of an individual 

case in the clinic or of general payer policies that allocate spending budgets, the O&P discipline 

is often perceived to be at a disadvantage due to its relatively young age, underdeveloped 

evidence base, and small economic clout as compared to other fields. Such asymmetrical 

negotiations have been the subject of economic theories and mathematical models, such as the 

“Game theory”, work on which has been awarded with several Nobel Prizes and other 

recognitions across the years. In this paper, we are introducing core concepts of this theory and 

discuss how they may be applied in negotiations on treatment approaches and reimbursement 

schedules with the goal to improve outcomes for the O&P profession.  

CITATION 

Fiedler G, Schikorra A. A brief 

introduction to game theory and its 

potential implications for the economics of 

orthotics & prosthetics. Canadian 

Prosthetics & Orthotics Journal. 2021; 

Volume 4, Issue 2, No.18. 

https://doi.org/10.33137/cpoj.v4i2.36661 

KEYWORDS 

Healthcare Economics, Game Theory, 

Rehabilitation, Competitive Bidding 

 

* CORRESPONDING AUTHOR 

Dr. Goeran Fiedler, PhD 
Department of Rehabilitation Science and Technology, University of 
Pittsburgh, Pittsburgh, PA 15206, USA. 

E-mail: gfiedler@pitt.edu 

ORCID number: https://orcid.org/0000-0003-1532-1248  

Special Issue: Health Economics in Prosthetics & Orthotics 

https://doi.org/10.33137/cpoj.v4i2.36661
https://jps.library.utoronto.ca/index.php/cpoj/index
https://doi.org/10.33137/cpoj.v4i2.36661
mailto:gfiedler@pitt.edu
https://orcid.org/0000-0003-1532-1248


 

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Fiedler G, Schikorra A. A brief introduction to game theory and its potential implications for the economics of orthotics & prosthetics. Canadian Prosthetics & 
Orthotics Journal. 2021; Volume 4, Issue 2, No.18. https://doi.org/10.33137/cpoj.v4i2.36661 

ISSN: 2561-987X 
A BRIEF INTRODUCTION TO GAME THEORY IN P&O  

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For the healthcare professionals, the eventual decision will 

have obvious economic implications as well. The surgeon’s 

recommendation, by nature, may be biased toward surgical 

treatment, just as the orthotist’s recommendation may favor 

bracing. A similar dynamic applies when insurance 

coverage and reimbursement schedules are being 

established and/or revised. 

The process of arriving at the decision can by some 

definition be considered a negotiation. With the comparative 

prestige of their academic degree and the amount of citable 

evidence to support their case likely not on the side of the 

O&P practitioners in this scenario, they may be at a 

disadvantage in such a negotiation.  

A different problem is that of competing against another 

provider. There may be various examples of this occurring 

in everyday practice but an instance with especially high 

stakes is the dreaded competitive bidding process that is 

frequently utilized, or at least proposed, by institutional 

payers, including the Centers for Medicare and Medicaid 

Services.7 In some such scenarios, O&P providers may 

have to contend against other bidders from outside the 

actual profession. If those competitors have a different cost 

structure, for instance, by being subject to different 

education and licensing requirements or by having lower 

local costs for labor and parts, the bidding process is 

unlikely to be effective in optimizing the economics of the 

contract at stake. Instead, it may happen that the expert 

O&P provider is priced out and the winning bid does not 

cover the costs of providing quality care, to the detriment of 

the patient, the provider, and ultimately, the insurer as well.  

These scenarios pose the question if there are strategies to 

optimize the outcomes under a given (or assumed) set of 

circumstances. An answer to that question may be offered 

by game theory, chiefly a set of mathematical models to 

describe and predict negotiation dynamics, which has been 

recognized as an important concept in economics.8,9 

The mathematical basis of game theory 

For simplicity we focus here on so-called non-cooperative 

games of, for example, two decision makers (called the 

players). Our game is pretty short and simple: each of the 

players makes a decision and receives a payout (or has to 

pay) according to some rules. 

Take, as an example, two doctors who have to decide which 

treatment to prescribe for a certain type of illness. Let us 

say, Treatment 1 costs $900, and Treatment 2 costs $1,000. 

If both doctors agree that Treatment 2 is better, they will 

likely (in the long run) receive both 50% of the patients to 

treat. If, however, one of the doctors decides to prescribe 

Treatment 1 (even though Treatment 2 might be better), the 

insurance has – all else being equal – an incentive to 

choose the doctor that is cheaper. Knowing this, both 

doctors have an incentive to prescribe Treatment 1 (even 

though it may be not the optimal treatment) for the fear of 

losing all revenue. So, according to this model both doctors 

are coerced to recommend the cheaper treatment-

regardless of the qualitative advantages of Treatment 2 

(Table 1). 

Table 1: Payout structure for each possible combination of 

prescription decisions.  

 

 

In mathematical terms the choice for Treatment 1 is called 

the Nash equilibrium: it is a choice where, for each player, 

the other party cannot improve their outcome by changing 

strategies. The problem that the Nash equilibrium may not 

be the optimal outcome for the participants is called 

prisoners’ dilemma of game theory. And this effect has been 

observed in many real-world situations (e.g., in social 

psychology or drug cartel formation).10,11 

The mathematical models (and summary tables) for this sort 

of real-life situation quickly become much more complex if 

additional parameters are being considered. In the 

simplified example of a “Cardinal game” above, for instance, 

the insurance is making decisions solely by price tag, which 

may not be entirely realistic. If the outcomes are on an 

ordinal scale rather than binary as in this example, or if there 

are additional differences between providers (e.g., 

qualifications, seniority, etc.) that affect the decision 

making, the model needs to be expanded and the additional 

assumptions need to be codified to allow for calculation of 

the Nash equilibrium. 

Implications for negotiations in the O&P realm 

It may not be immediately obvious how the dynamics of a 

“prisoners’ dilemma” could apply to the realm of O&P 

related economics. Indeed, most of the typical scenarios 

with which stakeholders in this field are confronted can be 

explained (and possibly solved) as a simple optimization 

problem. For instance, a negotiation with a payer (health 

insurance) about whether to give a transfemoral prosthesis 

patient a conventional hydraulic knee joint or a 

microprocessor-controlled knee can be reduced to a fairly 

straightforward balancing of costs and benefits. The cost 

differential is well known, and the risks of, say, accidental 

fall(s) that are detrimental to quality of life and follow-on 

health care cost savings12,13 can be reasonably 

approximated using historical data and a probabilistic 

  Doctor 2’s prescription 

  
Treatment 1  

($900) 
Treatment 2 

($1000) 

  
Doctor 
1 gets 

Doctor 
2 gets 

Doctor 
1 gets 

Doctor 
2 gets 

Doctor 1’s 
prescription 

Treatment 
1 

50% of 
900 

50% of 
900 

100% 
of 900 

0% of 
1000 

Treatment 
2 

0% of 
1000 

100% 
of 900 

50% of 
1000 

50% of 
1000 

https://doi.org/10.33137/cpoj.v4i2.36661


 

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Fiedler G, Schikorra A. A brief introduction to game theory and its potential implications for the economics of orthotics & prosthetics. Canadian Prosthetics & 
Orthotics Journal. 2021; Volume 4, Issue 2, No.18. https://doi.org/10.33137/cpoj.v4i2.36661 

ISSN: 2561-987X 
A BRIEF INTRODUCTION TO GAME THEORY IN P&O  

Fiedler & Schikorra, 2021 CPOJ 

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distribution curve. These factors will allow the 

recommendation to utilize either knee type at a specific ratio 

to optimize outcomes for all involved (at least on average).  

A more suitable application may be found in the competitive 

bidding process. An aspect of this process in the O&P field 

is the, theoretically, unlimited number of bidders (i.e., 

players), as well as a large number of contractual terms and 

performance criteria, making it difficult to model as a 

Cardinal game, which has a specific payoff function. 

Instead, a more complex ordinal game theory approach 

may be appropriate. Recent work14 suggests that such a 

model and associated optimization algorithm is applicable 

to general variants of Public-Private Partnerships, claiming 

that, among other things, “(1) it can handle any number of 

private sector players and … performance criteria, (2) it 

determines a single ranking of proposals ..., [and] (3) it can 

be used by the private sector players … to assist with the 

choice of bidding strategies…”.14 Given the inevitable 

differences between the specific scenarios considered in 

this research and the real-world process of entering a bid in, 

say, the CMS Durable Medical Equipment, Prosthetics, 

Orthotics, and Supplies (DMEPOS) Competitive Bidding 

program, more work to validate and refine the model is likely 

required. This work will include a discipline-specific ranking 

of the “strategy profile-induced outcomes”, to include things 

such as long-term health outcomes, processing efficiency, 

and sustainability of the provider pool. Still, it offers an 

interesting approach to maximizing the limited leverage 

wielded by O&P providers in the competitive bidding 

process and to optimize the bid evaluation and contracting 

process by the payer. 

CALL TO ACTION 

The long-term health and sustainability of our industry 

requires a mitigation of the inherent disadvantage that 

small-size businesses, such as typical O&P providers, have 

in competitive bidding and contract negotiations. We believe 

that modern game theory is a tool that can help address this 

issue, and we call on the large professional organizations 

that represent and cater to those businesses (e.g., the 

American Orthotic & Prosthetic Association and the O&P 

Alliance) to explore ways to take advantage of this powerful 

tool. This effort could take the shape of adding game theory 

content to business training offerings, or providing grant 

support for the development of industry-specific game 

theory models. 

ACKNOWLEDGEMENTS 

The authors thank Dave Crish for proofreading the manuscript. 

DECLARATION OF CONFLICTING 

INTERESTS 

The authors declare no conflicts of interest related to this work. 

SOURCES OF SUPPORT 

This work was partially supported by Simons foundation grant no 

579261 and by NSF Career DMS-2044898 

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Fiedler G, Schikorra A. A brief introduction to game theory and its potential implications for the economics of orthotics & prosthetics. Canadian Prosthetics & 
Orthotics Journal. 2021; Volume 4, Issue 2, No.18. https://doi.org/10.33137/cpoj.v4i2.36661 

ISSN: 2561-987X 
A BRIEF INTRODUCTION TO GAME THEORY IN P&O  

Fiedler & Schikorra, 2021 CPOJ 

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14.Ouenniche J, Boukouras A, Rajabi M. An ordinal game theory 

approach to the analysis and selection of partners in public–private 

partnership projects. J Optim Theory Appl. 2016; 169(1):314-43. 

DOI:10.1007/s10957-015-0844-3  

AUTHORS SCIENTIFIC BIOGRAPHY 

Goeran Fiedler is an 

Assistant Professor with the 

Pitt MSPO program. A clinical 

prosthetist/orthotist by 

training, he obtained additional 

graduate degrees in Clinical 

Engineering at the University 

of Applied Sciences Giessen 

(Germany) and in Health 

Sciences at the University of 

Wisconsin-Milwaukee, as well 

as post-doctoral training in 

Prosthetics at the University of 

Washington in Seattle. His research interests include the 

improvement of outcomes in lower limb prosthetics by optimizing 

prescription, fitting, and alignment of devices.  

Armin Schikorra holds 

graduate degrees in 

Mathematics from RWTH 

Aachen and University of 

Freiburg (both in Germany) 

and has completed post-

doctoral training at ETH Zurich, 

University of Basel (both in 

Switzerland) and Max-Planck 

Institute Leipzig (Germany). As 

of 2021, he serves as 

Associate Professor at the 

University of Pittsburgh’s 

Department of Mathematics. His research focuses on Geometric 

Analysis, Harmonic Analysis, and Nonlinear Partial Differential 

Equations. 

 

 

 

https://doi.org/10.33137/cpoj.v4i2.36661

