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Sharing Risk between Payer and Provider by Leasing HealthTechnologies: An Affordable and Effective ReimbursementStrategy for Innovative Technologies?Richard Edlin, PhD1, Peter Hall, PhD2, Klemens Wallner, BA3, Christopher McCabe, PhD3,*1Health Systems, School of Population Health, University of Auckland, Auckland, New Zealand; 2Academic Unit of Health Economics,LIHS, University of Leeds, Leeds, UK; 3Department of Emergency Medicine, School of Community Medicine, University of Alberta,Edmonton, AB, Canada

A B S T R A C T

The challenge of implementing high-cost innovative technologies inhealth care systems operating under significant budgetary pressurehas led to a radical shift in the health technology reimbursementlandscape. New reimbursement strategies attempt to reduce the riskof making the wrong decision, that is, paying for a technology thatis not good value for the health care system, while promoting theadoption of innovative technologies into clinical practice. The remain-ing risk, however, is not shared between the manufacturer andthe health care payer at the individual purchase level; it continuesto be passed from the manufacturer to the payer at the time ofpurchase. In this article, we propose a health technology paymentstrategy—technology leasing reimbursement scheme—that allows thesharing of risk between the manufacturer and the payer: the replacingof up-front payments with a stream of payments spread over the

ee front matter Copyright & 2014, International S

r Inc.

1016/j.jval.2014.01.010

@ualberta.ca.

ndence to: Christopher McCabe, PhD, Departmenreet, Edmonton, AB, Canada T6G 2T4.

expected duration of benefit from the technology, subject to thetechnology delivering the claimed health benefit. Using trastu-zumab (Herceptin) in early breast cancer as an exemplar technology,we show how a technology leasing reimbursement scheme not onlyreduces the total budgetary impact of the innovative technology butalso truly shares risk between the manufacturer and the health caresystem, while reducing the value of further research and thuspromoting the rapid adoption of innovative technologies into clinicalpractice.Keywords: cost effectiveness, decision uncertainty, risk, value-basedpricing.

Copyright & 2014, International Society for Pharmacoeconomics andOutcomes Research (ISPOR). Published by Elsevier Inc.

Introduction

The challenge of implementing high-cost innovative technolo-gies in health care systems operating under significant budgetarypressure has led to a radical shift in the health technologyreimbursement landscape. Where 10 years ago, the majority ofreimbursement decisions were either yes or no, with the occa-sional special scheme for politically high-profile technologies,now decision makers are increasingly choosing from a menu ofreimbursement strategies, as illustrated in Figure 1 [1]. Theprocedural justice considerations and efficient operation ofhealth care systems mitigate against one-off reimbursementschemes. A characteristic of all these reimbursement schemesis that the risk associated with the uncertainty about the truevalue of the technology is transferred from the manufacturer tothe health care payer at the time of purchase. Thus, the newreimbursement strategies attempt to reduce the scale of the riskof making the wrong decision, that is, paying for a technologythat is not good value for the health care system, primarily byreducing the total budget impact or by creating an opportunity forthe development of additional information to inform future

reviews of the funding decision. A positive reimbursementdecision, however, still entails significant risk and that risk isnot shared between the manufacturer and the health care payerat the individual purchase level; it continues to be passed fromthe manufacturer to the payer at the time of purchase.

In this article, we propose a health technology paymentstrategy that allows the sharing of risk between the manufacturerand the payer: the replacing of up-front payments with a streamof payments spread over the expected duration of benefit fromthe technology, subject to the technology delivering the claimedhealth benefit. The article is structured as follows: The secondsection briefly reviews the history of innovative reimbursementschemes—the so-called access with evidence development (AED)and the move toward value-based pricing (VBP)—and discussesthe extent to which these address the problem of asymmetricallocation of risk between the health care payer and the manu-facturer. The third section describes the technology leasingreimbursement strategy (TLRS) and the method used for calcu-lating the lease payment. The fourth section applies the TLRS toan exemplar cancer treatment, showing how the risk borne bythe payer is significantly reduced and how this can facilitate

ociety for Pharmacoeconomics and Outcomes Research (ISPOR).

t of Emergency Medicine, 736 University Terrace, University of

Fig. 1 – Selected reimbursement strategies ordered accordingto restrictiveness.

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more rapid and broader patient access to new technologies bychanging the expected net present value of further research. Thefifth section discusses the potential value of the TLRS in thecontext of VBP [2].

AED, VBP, and Uncertainty in the Evidence Base

Stafinski et al. [3] recently reviewed AED schemes. They observedthat although the problem that AEDs attempt to address has beenaround for a long time, and that most developed health caresystems have been involved in at least one such scheme, there isvery little evidence to suggest that they are successful from thehealth care payer perspective. As well as being of limited valuefrom the payer perspective [3,4], patient advocates and manu-facturers complain that AEDs restrict access to effective therapiesand reduce the return on investment in developing new tech-nologies, thus threatening future research and development.

VBP has been proposed as an alternative mechanism forpromoting the uptake of new technologies [5] that avoids thedelays associated with AED schemes. VBP, however, works byidentifying the price at which a technology is expected to be cost-effective and although upward and downward price adjustmentsbased on observed effectiveness allow some longer term miti-gation of the costs of uncertainty, the risk of nonreturn oninvestment in the technology is transferred in its entirety to thehealth care payer at the time of payment. Hence, VBP is at best aweak policy instrument for addressing the uncertainty in theevidence base for interventions requiring up-front investment.

Because the high levels of uncertainty in the evidence forcost-effectiveness are typical for innovative technologies, a policyresponse is required. “Only in Research” and “Only withResearch” AED schemes are the primary choices currently avail-able to decision makers concerned about uncertainty. Hall et al.[6] have shown that Only with Research schemes are extremelyinefficient mechanisms for addressing uncertainty in the evi-dence base because the value of the information produced willtypically be much less than the cost of the scheme unless thedegree of decision uncertainty or the budget impact of thetechnology is small. Only in Research schemes in contrast aremore efficient but are politically less acceptable because of theireffect on patient access to the technology. The current portfolioof policy options for allowing access to potentially valuable buthighly uncertain technologies is likely to be either highly ineffi-cient or highly unpopular. An alternative strategy that shared therisk that is inherent in funding such technologies while allowingprompt patient access would be useful.

Technology Leasing Reimbursement Strategy

Industries in which reliability of delivery is highly important,such as civil aviation, have developed payment mechanisms inwhich the suppliers receive payment only for delivered outputsrather than delivered technology [7]. For example, airlines buyflying time from aero engine manufacturers rather than enginesper se [8]. When engines need maintenance or repair, a replace-ment engine is provided to maximize the time that the airline isin the air and minimize the risk that the airline fails to deliverscheduled flights. By leasing a working engine rather than merelypaying for an engine, the airline pays only for what it receives.Just as importantly, the manufacturer has a strong incentive toprovide surety of service because it is this service that is paid forrather than the technology itself. Although airlines enjoy otherbenefits from leasing engines, the ability to link payment todelivered benefits commends the consideration of leasing as apayment strategy for health care.

Although leasing is not unknown in health care, its use islimited to the provision of technologies with very high up-frontcosts that are used in the treatment of a large numbers ofpatients, such as Di Vinci surgical robots and magnetic resonanceimaging scanners. The standard model in health care sees payerspurchasing health care rather than health. Although treatmentsare not engines—we cannot return or reclaim a treatment alreadyprovided—it is feasible for payers to reimburse manufacturers fordelivered healthy time rather than for the delivered technology.To a degree this happens with chronic therapies such as statinsand beta blockers, where failure of the treatment (death) resultsin stoppage of the payment stream. For many expensive tech-nologies such as surgical implants and cancer drug treatments,however, the link between health delivered and payment doesnot exist at the individual patient level.

In the context of a value-based reimbursement decision usinga cost-effectiveness rubric, the question of cost-effectivenesswould be established in the same manner as now. Here, costsand benefits over time are assessed, and a judgment made.Having established the price at which the technology is expectedto be cost-effective, the “lease” payment due for each period ofhealth delivered could be established by calculating a stream ofpayments over the expected lifetime of the technology that hasthe same expected net present value as the agreed price. Manysuch streams are possible, and there are many dimensions inwhich they might differ. These include whether the streamsallow the price paid to increase for inflation or not; whether theylimit payment to a fixed period after the delivery; and, of course,which measure of effectiveness is used to judge whether atechnology has delivered the promised effectiveness. This articledoes not make specific recommendations about which types ofstream are relevant, but chooses a case in which the price paidincreases in line with discounting; that is, we assume that theprice paid is adjusted for inflation and the net present value ofeach payment is equal. No time limit is set on the length ofthe lease.

The TLRS would work by paying the company for each periodof health delivered at the individual patient level. If the observedmean effectiveness was equal to the expected effectiveness, thenthe manufacturer would receive the full value of the technology.When an individual’s health experience from the technology wasless than predicted, the payment would stop and thus the healthcare system would be to some degree protected from the risk ofpaying for a technology that was not in fact good value for it.Equally, if the observed effectiveness exceeded that expected in aperson, the company would continue to receive additional pay-ments for them. To this extent, the TLRS at least partiallyautomates the VBP proposal that the price paid for a technology

Fig. 2 – Net benefit probability map for a hypothetical innovative technology with cumulative net health benefit (NHB)measured in quality-adjusted life-years and the time horizon measured in years after treatment.

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should increase to reflect greater than expected benefits, as wellas decrease in the presence of lower than expected benefits,while still respecting the cost-effectiveness threshold used by thedecision maker.

Figure 2 uses the net benefit probability map (NBPM) [9] toillustrate how the standard up-front payment mechanism fornonchronic disease technologies transfers all the risk to thehealth payer. The NBPM uses the simulation data generated forstandard probabilistic sensitivity analyses of a cost-effectivenessanalysis to describe the distribution of uncertainty in net benefitover time. The bold central line is the cumulative expected netbenefit (net health benefit, measured in quality-adjusted life-years) over the time horizon of the cost-effectiveness analysis.The dashed plots are probability contours plotting the deciles ofthe cumulative net benefit distribution at each time point.

By displaying the uncertainty around the expected net benefitover time, the NBPM allows decision makers to understand theallocation of risk between the manufacturer and the health caresystem. In Figure 2, we can see that the risk regarding whether anew technology is good value is driven by uncertainty aboutwhether the new technology will deliver sufficient additionalhealth gain to cover its excess cost. In this illustration, byfollowing the second and third deciles, we can see that there is

Fig. 3 – Cost-effectiveness acceptability curve

approximately a 31% chance that the treatment will have dis-placed more health than it produced 20 years after it was paid for,and because of the risk of late treatment-related adverse events,this probability increases to 39% by 50 years.

On initial examination, the TLRS appears to be similar to otherwell-established forms of patient access schemes, in whichreimbursement is linked to observed effectiveness, and in someregards this is correct. The TLRS framework, however, allows theformal identification of the appropriate per period payment thatis consistent with the cost-effective utilization of the newtechnology on the same basis as other technologies that arereimbursed without a patient access scheme. Hence, it does notrepresent an essentially arbitrary departure from the standardreimbursement decision rules in the way that patient accessschemes do. Furthermore, in reducing the uncertainty in theexpected net benefit from the technology, the TLRS sits in thesame framework as the value of information analyses propo-sed to inform decisions about Only in Research and Onlywith Research funding of new technologies. Specifically, it willallow the identification of technologies for which a TLRS willallow full implementation in the health system when thedecision uncertainty otherwise indicated a “research only”reimbursement.

for trastuzumab in early breast cancer.

Fig. 4 – Net benefit probability map under standard reimbursement strategy.

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To understand the effect of the TLRS on the distribution ofcosts and benefits between the manufacturer and the health caresystem, the next section examines the effect of adopting a TLRSon payment for trastuzumab for early breast cancer using asimplified version of a published trastuzumab cost-effectivenessmodel [10].

Applying the TLRS to trastuzumab

Figure 3 is the estimated cost-effectiveness acceptability curvefor trastuzumab in early breast cancer, based on the modeldeveloped by Hall et al. [10]. Using Claxton et al’s estimate ofthe UK National Health Service cost-effectiveness range thresh-old [11,12], there is approximately a 50% chance that trastuzumabdisplaces more health than it produces. The expected incremen-tal cost-effectiveness ratio is £17,154 based on a drug cost of£21,184 incurred in year 1.

Figure 4 plots the NBPM for trastuzumab, showing that it takes19.5 years before the expected net health benefit is positiveand that the 90% credible range for the cumulative netbenefit at 50 years is �0.55 quality-adjusted life-years to þ0.76

Fig. 5 – Cost-effectiveness acceptability curve for trastuzumab inreimbursement strategy.

quality-adjusted life-years. The uncertainty in the expected netbenefit increases rapidly over the first 10 years. After 10 years, itincreases but at a decreasing rate, until effectively stabilizing byyear 40.

Given the price of trastuzumab is £21,184, and an averagerelapse-free survival period for a patient treated with trastuzu-mab is 10 years according to the model, the annual equivalentdrug cost for trastuzumab is £2,118.4 compounded each year at3.5%. This is paid up front each year for patients who haveremained in the relapse-free state (including those who developcardiac toxicities). Figure 5 plots the cost-effectiveness accept-ability curve for trastuzumab under the TLRS. The probabilitythat trastuzumab displaces more health than it produces, usingthe same threshold value estimated by Claxton et al. [5], isslightly lower at approximately 48%.

Figure 6 plots the NBPM for trastuzumab under the TLRS. Theexpected incremental cost-effectiveness ratio is £17,225, and theexpected net benefit is positive after 6.5 years. The difference inthe estimated incremental cost-effectiveness ratio between thestandard and TLRS is due to sampling variation. By year 10, thereis an 80% probability that trastuzumab has generated morehealth than it displaced. The proportion of the net benefit map

early breast cancer under a technology leasing

Fig. 6 – Net benefit probability map under a Technology Leasing Reimbursement Strategy.

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that is below the break-even curve increases slightly after 25years because of the possibility that trastuzumab is considerablymore effective than expected and thus the total health cost oftrastuzumab increases. The 90% credible range of the net benefitunder the TLRS, however, is substantially reduced, with an upperlimit of þ0.56 and a lower limit of �0.39.

Innovation and the TLRS

Innovative technologies either do things that have not been donebefore or they do things in ways that have not been used before.This novelty leads to large amounts of uncertainty and the riskthat health care payers may forego health to fund a newtechnology and not receive sufficient return on that investmentto justify the initial sacrifice. The increased certainty that comesfrom experience is by definition not available. As Walker et al. [1]demonstrate, when there is a high level of uncertainty about atechnology, it will sometimes be efficient to delay reimbursementto await further research even when the expected net healthbenefit is positive. Other things being equal, this leads to areduction in the likelihood of these treatments receiving funding,which may stifle future innovation in health care, with potentialnegative implications for economic growth more generally.

The TLRS addresses this issue by directly modifying the levelof risk associated with purchasing an innovative technology. Thisis in contrast to VBP scheme proposals that sought to modify thevalue of health produced by innovative technologies. By replacinga single up-front payment with a payment stream that has anequivalent expected value conditional on delivery of promisedhealth gain, the risk inherent in purchasing new technologies isreduced. The framework has the potential to deliver higherpayments if the technology outperforms expectations, by allow-ing the stream of payments to continue beyond the time point atwhich the target payment has been reached. By reducing thedecision uncertainty, the value to the health system of delayingreimbursement to await more research is substantially reduced,making it easier for innovative technologies to be implementedquickly into a health care system. Although the expected totalbudget impact for the technology is the same as under theconventional payment framework, the initial budget impact is

reduced and the value of the decision uncertainty is substantiallyreduced because failure to deliver the expected health gain islinked to reduced expenditure. The expectation of a lowercumulative budget impact in the years shortly after investmentalso leads to an earlier break-even point [9], that is, the timewhen the intervention has produced more population healththan is displaced elsewhere in the health system to pay for it.

The TLRS reduces the total budgetary impact of the technol-ogy in the presence of reduced effectiveness and hence theexpected cost of treatment failures. It correspondingly reducesthe value of further research at any given level of uncertaintyregarding effectiveness and safety. If the treatment proves to bebetter than expected, the TLRS allows the manufacturer toreceive additional revenue. This, in turn, makes it more likelythat an innovative technology can be made available as perlicensed indication and outside of the context of further research.For truly valuable technologies, the TLRS is a mechanism forpromoting their rapid uptake rather than an impediment akin toAEDs, without transferring the entirety of the risk associated withreimbursement to the health care system.

An obvious and potentially substantial disincentive for healthsystems to engage with the TLRS approach is the potentiallysubstantial administrative cost associated with monitoringpatients’ outcomes in response to treatment. In our example,some patients treated with trastuzumab might require monitor-ing for 50 years, some 45 years longer than current practice. Theincreasing use of electronic medical records to create routinesystem-wide data sets, however, may make this a smallerimpediment than would previously have been the case. Addi-tional costs associated with the operation of the scheme and theresponsibility for meeting them could be taken into accountwithin the lease agreement. For example, if a manufacturerproposes that a TLRS be used to make a technology availablethat had been refused reimbursement under standard criteria,these costs would have to be factored into the analysis thatestablished the price at which the technology was good value. Incontrast, if the reimbursement authority wished to use a TLRS fora technology that met the criteria for reimbursement understandard conditions (perhaps because of greater than normaluncertainty), it seems likely that the payer should bear thetransaction costs. Under such circumstances, the TLRS should

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also be compared with alternative mechanisms for managinguncertainty such as reimbursement for research purposes onefficiency grounds.

In the airline industry example that motivated our article, it isincumbent on the airline to adhere to certain processes thatpromote the reliability of the engines, most notably returningengines for services in line with a specified program. Airlines thatfail to adhere to these conditions should bear the excess costassociated with reduced performance. Similarly, for patients whodid not adhere to treatment, or where the technology had notbeen provided as part of the specified package of care, theagreement would need to protect the manufacturer from resul-tant losses. This may create pressure for patient contracts topromote adherence, although in reality, health care payers bearthe costs of poor implementation and nonadherence undercurrent arrangements and thus there is no logical argument asto why the changed relationship with the manufacturer shouldchange the relationship with the patient.

A parallel disadvantage for manufacturers is that streamingthe payments over a much longer time period would increase thetime-to-return on the research and development investments,with implications for investments in developing future innovativetechnologies. In principle, financial instruments such as bondscould be used to ameliorate some of these affects, but it is likelythat the supply of investment funds for health technologies wouldbe reduced to some degree. Against this concern must be balancedthe risks to the current model of health care funding in the absenceof innovative payment strategies and the value of increasing thelikelihood of market access at or close to licensing.

The consideration of the TLRS has focused implicitly on devel-opments in the United Kingdom. This reflects the fact thatdiscussions on the implementation of the VBP and the formal-ization of alternative reimbursement strategies are most advancedthere. Although we would argue that the direction of travel in manycountries is toward greater use of health technology appraisal andcost-effectiveness analysis in reimbursement decision making [13],the utility of the TLRS mechanism is not limited to such a setting.As Jaroslowski and Toumi [14], among others, report, there iswidespread use of patient access schemes across Europe and NorthAmerica [3,15]. The TLRS provides a systematic framework for thedesign of such schemes, allowing a consistency in patient accessstrategies across technologies and patient groups, thus facilitatingprocedural justice [16] in an area of reimbursement policy noted forits inconsistency and the presence of ad hoc policymaking [3].

Conclusions

Reimbursement authorities are under pressure to develop mecha-nisms that support the adoption of expensive new technologies byhealth care systems to complement the development of conditionallicensing by regulators [17,18]. In this article, we have described aspecific formulation of a payment-by-results patient access scheme,the TLRS, that sits within the cost-effectiveness–based reimburse-ment framework and is coherent with VBP and value of informa-tion–based research prioritization decisions. The TLRS can enablemore rapid implementation of innovative new technologies inhealth care systems at the same time as protecting health caresystems from the uncertainty inherent in such technologies. Bydoing so it reduces the time taken for investments in newtechnologies to break even from the health system perspective.

In managing risk at the individual unit of output, and calculat-ing periodic payments based upon a target net present value forthe total revenue stream, TLRS approach is consistent with stand-ard leasing arrangements. However, there are some superficialdifferences. For example, conventional leasing schemes seek toensure continuity of service by ensuring replacement of technology

in the case of failure. For many individual health care treatments,this is not possible. Instead the payment for the technology ceasesto ensure it is available to provide alternative health care. This maybe for the same patient or it may be other patients served by thesame health care budget. The principle of protecting against loss ofhealth production from the expenditure is parallel but not identicalto protecting against loss of services such as flying time in otherleasing environments. In addition, standard leasing arrangementsare for a finite period. As described here, the TLRS does not have afinite length. It would be perfectly possible for the TLRS to have theduration set equal to the period used to calculate the payment.However, this would close down the option of additional rewardfor treatments that are better than expected.

The effect of utilizing a TLRS will vary systematically betweentechnologies. Technologies with a large upfront cost and fewdownstream expenses, such as prostheses and implants with orwithout biologically active components, would likely see thelargest impact. The impact would also be modified according tothe degree of uncertainty in the evidence base, the duration ofeach payment period and the number of periods over which thefull benefit of the therapy was expected to be observed. Lowercost chronic treatments that could be self-administered by thepatients are unlikely to be appropriate technologies for reimburs-ing through TLRS.

The TLRS fits into the current portfolio of reimbursementpolicy tools. The TLRS would take the cost-effective price deter-mined through a VBP assessment. When the extent of decisionuncertainty is large, a TLRS strategy may not reduce the value offurther research sufficiently to support a positive reimbursementdecision. In such circumstances “Only in Research” would remainthe efficient reimbursement policy option.

There may be concern that TLRS commits payers futurebudgets thus reducing future financial flexibility. However, thedegree of future commitment will depend upon whether thefunded technologies deliver the claimed value. At a minimum,TLRS’s will deliver greater flexibility in the short- to mid-term;potentially at the expense of less flexibility in the future. How-ever, that lack of flexibility will be due to investment in tech-nologies of proven value, in the same way as employingphysicians and building hospitals tends to commit payers’budgets in the longer term. It is not obvious why long-termcommitments to invest in therapies should be judged differentlyfrom other health care investments.

As a structured and consistent approach to the design ofpatient access schemes for uncertain technologies, the TLRS hasthe additional attraction of being more closely aligned with theprinciples of accountability for reasonableness than the majorityof current processes for establishing such schemes [3,16].Although the implementation of the TLRS will likely incur trans-action costs, these can be incorporated into the analysis thatunderpins the design of specific schemes and should not there-fore represent an insurmountable barrier to its use.

Source of financial support: Christopher McCabe’s research issupported in part by the Capital Health Endowment in Emer-gency Medicine Research; Klemens Wallnerʼs work on the projectwas funded by the Stem Cell Network Global Research ProgramPublic Policy Core Grant Enhancing Translational Stem CellResearch: Innovative Models for Multi-Sectoral Collaboration.Drs. Hall and Edlin report no direct funding for this research.

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