The role of product life cycle in medical technology innovation

Abstract

The purpose of this work is to review and synthesise prior research concerning the product life cycle concept in the specific context of medical technology innovation. Based on a review of both general and context specific literature in this field, it finds that medical technology innovation is strongly influenced by life cycle effects, particularly with respect to price erosion. It also finds that our general understanding of product life cycle indicates that individual curves are strongly influenced by supply side constraints, such as patent protection and barriers to entry, and demand side factors, such as market heterogeneity and diffusion mechanisms. Importantly, these two complementary domains have not been previously synthesised. This has important social and economic implications for access to improved therapies, healthcare spending and investment in innovation. This article represents a first attempt to bring together valuable work in strategic management and health economics and, by developing some postulates from the literature, attempts to inform future research in this area.

Keywords

Product life cycle pharmaceuticals medical technology health economics health technology assessment innovation healthcare

Introduction: An old concept with a new application

Access to new therapeutic technologies, either pharmaceutical, medical devices or other technologies, is an important and pressing issue for both developed and emerging economies. Limited economic resources, expanding technological capabilities and demographically driven demand combine to require that payers, whether public or private, make rational, evidenced-based choices about which technologies to make available and which to restrict to independent, private purchase. Inevitably, such decisions are often controversial, emotional and politically sensitive.

The principle mechanism for informing such difficult choices is health technology assessment (HTA), a process by which the benefits and costs of new therapeutic technologies are evaluated in health-economic terms, typically in comparison to extant therapies, and which results in recommendations regarding which technology is most appropriate in a given clinical scenario.¹ The rigour and validity of a HTA methodology is very important as it has serious consequences for patient outcomes, healthcare expenditures and the sustainability of an industry that depends on its profits to fund future innovation. It has been observed that HTA processes for pharmaceuticals were developed earlier and have advanced more quickly than those for medical devices and other medical technology and that, as a result, pharmaceutical HTA techniques are often used as a template or prolegomenon for HTA in medical devices or other medical technologies.²

Importantly, the decisions of a HTA have a temporal aspect. Whilst they are made in a particular chronological context of competing therapies and prices, assuming that situation is static may invalidate the decision. In particular, the extent and speed to which the price of a product may decline over time, in the face of competitive pressures, may make a large difference to the cost-benefit calculations that are the foundation of HTA. For example, assuming static or near static pricing may result in a negative HTA decision whilst assuming price erosion may produce the opposite result. Clearly, an understanding of market dynamics over time is an important consideration for any rigorous HTA.

The pre-eminent technique for understanding, describing and predicting how the market for a particular product may change over time is product life cycle (PLC), This concept synthesises ideas about diffusion of innovation³ and competitive dynamics to predict how sales growth rates and the level and type of competition varies over time in any given market. However, as this article will argue, the PLCs of pharmaceuticals and medical technologies are, due to their different social and legal environments, rather different. This implies that assumptions about market changes over time that are common in pharmaceutical HTA may be invalid in the HTA of medical devices or other medical technologies, with important consequences for societal access to new medical technologies It is reasonable, therefore, to assert that in, HTA and PLC, we have an unusually clear example of how a concept from the marketing literature may have an significant impact on an issue of great importance to society. HTA, made necessary by technological and social change, needs to allow for the way a particular product-market changes over time, the very phenomenon that PLC purports to describe and explain was developed. To examine this subject, this article reviews the relevant extant literature and makes recommendations for future research into the behaviour of medical technology life cycles and their relevance to HTA.

Jack of all trades: The history and characteristics of the PLC concept

The intellectual foundations of what was to evolve into the PLC concept can be found in the work of Dean⁴ who examined the phenomenon of degeneration of a product’s distinctiveness over time. Dean’s work identifies and discusses many of the features of the PLC but without introducing the term. For instance, he points to the trend towards technological imitation and standardisation and identifies stages (which he terms periods) in a product’s life cycle. Mercer⁵ claims that there were several, unidentified PhD theses on the subject of PLC in the late 1950s, but judges Levitt’s two influential papers in the mid 1960s^6,7 to be the true genesis of PLC thinking. Levitt’s work primarily concerned the use of PLC as a forecasting tool for individual products, although he was quite open in his admission that the challenge of correlating sales forecasts to life cycle analysis was unresolved.

Levitt’s work, largely conceptual rather than empirical, prompted serious, empirical attention to the subject of PLC. Prominent examples of this period of work are papers by Cox⁸ and Polli and Cook,⁹ both of which helped to clarify the previously unclear theoretical bases of PLC. From these and other attempts to verify and explicate the PLC concept came ideas that both complicated and challenged Levitt’s initial ideas. For example, Cox, studying 258 prescription drugs, identified six different groups of PLCs whilst Polli and Cook identify the responsiveness of PLCs to company activity such as promotion. Most importantly, however, this phase of work established two theoretical parameters that are important to the understanding of PLC. The first is the idea that the appropriate unit of analysis for PLC is not the individual product (as assumed by previous authors) but some higher level of analysis such as the product group or category. As we will discuss, this differentiation between PLC as an operational tool to manage a product versus PLC as a strategic tool to explain and predict the behaviour of a product category or market is an important one. The second is that theoretical parameter to emerge from this work was that, as it is based on assumptions about competitive dynamics, PLC works best in market conditions where the entry of new competitors is not restricted. As Polli and Cook described it:

‘(Product life cycle) applies best to those products where sales are not significantly affected by variations in supply conditions’ (p.397)

As examination of the PLC concept advanced, other criticisms and refinements of it were developed. Hofer¹⁰ developed the value of PLC as a strategic tool and saw it as ‘the most fundamental variable in determining an appropriate business strategy’.¹⁰ By contrast, Dhalla and Yuspeh¹¹ made further criticisms of PLC as an operational tool, pointing out that, due to the intrinsic irregularity in the development of market sales, it was almost impossible to predict sales accurately on the basis of PLC. They concluded:

‘PLC is a dependant variable which is determined by marketing actions; it is not an independent variable to which companies should adapt their marketing programs’ (p. 105).

Subsequent work added to the understanding of the PLC concept. de Kluyver¹² examined the life cycles of 350 industrial products in different categories and identified three types of PLC, each of which showed flattening of sales growth at different stages, the characteristics of which he suggested was related to the relative innovativeness of the product type. In identifying that sales growth rates and time were not the only two important variables in describing the PLC, de Kluyver echoed an earlier stream of work that suggested that factors such as strategy, structure and performance varied over the life cycle. This work was synthesised and developed by Thorelli and Burnett,¹³ whose work suggested that market innovation, market concentration, competitive entry, and spending on R & D and marketing were all variables that contributed to the characteristics of a PLC. In the 15 years following Levitt’s promotion of PLC, it had developed from a relatively simple model that related sales growth to time for a single product to one that suggested sales growth was but a single variable, dependent upon several other variables and which, in any case, seems to apply to a product group, rather than a single product, and then only in cases in which supply conditions do not significantly constrain the market. At this point, Day¹⁴ summarised current thinking on the value and limitations of PLC as follows:

‘The product life cycle is a versatile framework for organizing contingent hypotheses about appropriate strategy alternatives and directing management attention toward anticipation of the consequences of the underlying dynamics of the served market. To enhance both the descriptive and explanatory value of the concept, much more attention needs to be directed toward understanding recurring patterns of successful strategies organized according to the stages of the life cycle models that are adapted to differences in the important underlying forces’ (p. 65).

Day’s paper acted as a milestone in the development of ideas about PLC. Since then, researchers explore its value and refine its application but without significantly changing the basic concept. Some have continued to point to its value,¹⁵ whilst others have reinforced its limitations as a predictive tool.⁵ Others have explored the phenomenon of repeating life cycles¹⁶ whilst others have found little evidence for shortening PLCs.¹⁷ Still others have attempted to better explain PLC behaviour with novel theoretical concepts (e.g. informational cascades¹⁸). More recently, Chandrasekaran and Tellis¹⁹ and Bohlman et al.²⁰ have explored the reasons behind the significant variation the shapes of different PLCs and have attributed it to context-specific variations in market heterogeneity and diffusion dynamics within a market. All of this work represents significant progress in understanding PLCs but it seems reasonable to conclude that rather more work is needed, especially in market conditions where the supply side is constrained by regulation or other barriers to entry.

So as we consider what it might imply for market access to therapeutic technologies, we can be both positive and negative about the PLC concept. More than five decades of theoretical and empirical work has embedded, rather than refuted, the idea that the markets do seem to have life cycles during which sales growth rates and other variables do vary with time. However, that work has identified that the PLC concept applies more readily to product categories rather than single products. Moreover, it suggests that several components of competitive activity, from innovation to marketing activity, drive sales growth rates and so lead to PLC characteristics that are particular to market conditions. Finally, none of the work since Polli’s paper addresses markets where supply may be constrained, so leaving Polli’s limitation on PLC usefulness in supply-constrained markets as a valid point. Since Day’s summary in 1981, there has been some limited advance in explicating the complexity of specific PLCs and hence the concept remains, to use Day’s words, a versatile framework but cannot be said to have great power as a predictive tool except in the most general sense.

Hence PLC as a concept might be described, to use the English idiom, as a Jack of all trades but the master of none; its ubiquity makes it broadly useful in understanding how product- markets behave but the variability of individual life cycles limits the concept’s ability to address very specific cases with any accuracy.

Chinese whispers: The application of the PLC concept in medical technology markets

The application of PLC to medical technology markets, both pharmaceuticals and devices, is an example of what Schőn called the displacement of concepts,²¹ a phenomenon in which the displacement of an idea from one context to another is often accompanied by some distortion, just as words are distorted during a game of Chinese whispers. Some strategic management concepts are notorious for the way in which they are been distorted during displacement. Examples of this include SWOT analysis, which some researchers have suggested is so abused in practice as to worthy of a recall²² and market segmentation, a term which some authors find is often used mistakenly for what is in fact customer categorisation.²³ In these and other examples, some of the ideas inherent in the concept are taken but applied in an entirely different way to that intended by the original authors. To a degree, this seems to have been the case in the application of PLC to therapeutic technologies such as drugs and devices.

After Cox’s early application of PLC to prescription drugs,⁸ there have been relatively few applications of it to pharmaceuticals. Those that do exist do not attempt to verify the existence or determine the characteristics of pharmaceutical PLCs but instead use it as a tool to understand and manage other phenomena. This work falls into three categories. The first, which focuses upon the economics of drug development, is typified by Grabowski and DiMasi.^24,25 These authors use PLC in quite a different way from earlier workers, extending it backwards in time to include pre-launch expenditure and activity. In addition, their focus is on measuring net cash flow over time, as first adopted by Thorelli and Burnett,¹³ rather than the sales growth focus of other, earlier work. The principal findings of this work are that returns on new product development are strongly skewed, with only a few products contributing the large majority of returns. However, an interesting secondary finding is that the shapes of pharmaceutical PLC curves, although all roughly bell-shaped, vary greatly between product categories. This seems to echo earlier work especially that of Dhalla and Yuspeh and Thorelli and Burnett, who saw the shape of the PLC curve as a dependent variable rather than a predictable to which firms should react, but also the later work of Chandrasekaran and Tellis¹⁹ and Bohlman et al.,²⁰ who discuss variations in PLC in terms of market context. The second category of published work in which PLC is related to pharmaceuticals is that which focused on PLC management, that is the tactics of pricing, usage extension and distribution tactics aimed at enhancing the revenue stream of a pharmaceutical product over its life cycle. Typically,²⁶ this work refers to the life cycle of single product rather than a category and assumes a life cycle that is largely shaped by regulatory approval, patented-protected exclusivity and eventual genericisation of the market. The third category of PLC application to pharmaceuticals is that of Hoyle, which considers pricing and cost effectiveness.^27,28 This work considers how the calculations regarding the cost-effectiveness of a pharmaceutical are influenced by assumptions made about the price of a pharmaceutical over its life cycle (which is purported to be 33 years on average) and its future usage pattern. In particular, it compares traditional cost-effectiveness calculations with those made with a ‘life-cycle correction factor’, which allows for these factors. It concludes that this refinement to the cost-effectiveness calculations makes a very significant difference, predicting many drugs to be cost effective when, under the traditional calculation, they were not.

The application of PLC in medical device markets is much less extensive than in pharmaceuticals. In the ‘grey’, non-peer-reviewed literature,²⁹ the dominant theme is that medical technology life cycles are much shorter than those for pharmaceuticals because technological innovation is more incremental and less protected by patents and other intellectual property rights. Authors who have explored the nature of PLC in medical technology suggest normative models with stages ranging from concept through growth to decline, but this work is presented without any supporting observations.³⁰ This work applies the PLC concept in little more than name, distorting its meaning to no more than the period during which the product is in current usage and ignoring the research upon which the concept is based.

The peer-reviewed literature concerning the application of PLC to medical devices is sparse but can be categorised in manner similar, but not identical, to the three applications of PLC in pharmaceuticals. The first application area, related to the economics of product development is analogous to the work of Grabowski and DiMasi.^24,25 For example, work by Vallejo-Torres et al.³¹ uses Bayesian methodologies to resolve the complexity of price variation over time and its impact of product development decisions. Although this work assumes the importance of price variation over the life cycle, it does not explore its nature or causes. Similarly, Ijzerman and Steuten³² take price variation over the life cycle as a given when they consider the use of HTA methods to inform the development of medical devices, without exploring the antecedents or moderators of that price variation. A extension of this idea, focusing on ‘stage gates’ during the developmental, pre-launch phase of medical devices is used in a paper by Girling et al.,³³ but again this work assumes price variation post launch but does not consider the factors that might moderate this. The second application of PLC to pharmaceuticals has no real parallel in medical devices; there is no body of literature analogous to that concerning PLC management in pharmaceuticals. This is unsurprising, since that area of writing is framed by and dependent upon the exclusivity period inferred by pharmaceutical product development processes and intellectual property rights. In devices, the dominance of incremental development together with very different product licensing legislation makes this exclusivity period both shorter and less well defined. The third application of PLC to medical devices is, however, more comparable to its pharmaceutical analogue in that it more directly considers pricing and reimbursement. For example, Brown et al.^34,35 observe that the prices of medical devices decline over time, sometimes with complex, two-phase curves. Although these authors attribute this primarily to an experience curve, suggesting that prices are primarily driven by costs, their observations are equally attributable to PLC drivers such as increased competition. This is supported by Dixon,³⁶ who observes the competitive nature of the sector. Other work sheds light on the mechanics of this price erosion phenomenon. Provines³⁷ notes that medical technology companies often lack the capabilities to demonstrate the financial value of their innovations. In a review of factors that affect pricing and reimbursement, Hutchings³⁸ found little consideration of price variation over time. Similarly, explorations of the role of funding and procurement policies in the uptake of new medical technologies have found little consideration of price erosion over time.^39,40 Perhaps the nearest parallel between pharmaceutical and medical devices in this area of research is that between of Hoyle^27,28 and that of Firth et al.⁴¹ Firth’s work provides a case study in which price erosion of a product, stimulated by the market entry of a new, improved form of the product, led to a revision of the HTA.

So, whilst the application of the PLC concept to therapeutic technologies such as drugs and devices has been subject to Chinese whispers like distortion, it is still reasonable to conclude that the PLC phenomenon is observable in these markets. However, the factors that dictate the shape of the life cycle and the differences between product categories do not appear to be well understood. Some evidence exists that supply constraints and market specific factors, such as market heterogeneity and diffusion mechanisms, may shape the PLC in medical technology but little research exists that is specific to the market conditions typically seen in these markets. In addition to the scholarly importance of this gap in our knowledge, it may be expected to have significant practical implications for the effectiveness of HTA processes and hence for the availability of medical technology.

Discussion: Developing a model of PLC in medical technology

In the preceding sections of this article, the concept of the PLC has been considered with reference to the general literature and then with reference to its application in medical technology markets, both pharmaceuticals and medical devices. From a synthesis of this work, it seems reasonable to draw a number of putative conclusions that might shape future research.

Firstly, some kind of PLC phenomenon is observable in medical technology markets. Cox’s work⁸ demonstrates this well and there seems no fundamental reason why the concept’s described by Levitt^6,7 should not apply in these markets.

Secondly, the nature of the PLC is a dependent variable influenced by a number of supply side and demand side factors, as suggested by Polli and Cook.⁹ This suggests that the shape and behaviour of a PLC will differ not only between pharmaceuticals and medical devices but also within these categories, according to the nature of the supply and market context factors.

Thirdly, it is possible to postulate the demand and market context factors that might influence the shape of the PLC for any given product category. Taking a normal distribution ‘bell curve’ of sales over time as a starting point, we might expect the shape of the PLC to be influenced by:

The incremental benefits of the new product over existing products. Greater incremental benefits might be expected to accelerate adoption and pull forward in time the PLC curve.

The incremental costs of the new product over existing product. Greater incremental costs might be expected to retard adoption and push backwards in time the PLC curve.

The commercial attractiveness of the product category relative to other product categories. Greater commercial attractiveness might be expected to accelerate marketing activity and so accelerate adoption and pull forward in time the PLC curve.

The intellectual property, regulatory and technological barriers to entry. Greater barriers to entry might be expected to hinder market entry and marketing activity, so retarding adoption and push backwards in time the PLC curve.

The capabilities of the suppliers to demonstrate clinical and economic value. Greater capability might be expected to accelerate adoption and pull forward in time the PLC curve.

The assessment processes of the purchasers. Procurement processes that did not quickly or accurately compare the incremental costs and benefits of new medical technologies might be expected to moderate the adoption of more valuable products and so pull distort the PLC curve.

These factors, which may not be complete, provide at least a partial explanation of why PLC curves appear to differ between pharmaceuticals and devices and within those two sectors. In short, even product categories within a sector can have different market conditions and hence might be expected to have very differently shaped PLC curves.

However, the practical importance of these postulated factors concern their implications for innovation in medical technology. As Hoyle noted in pharmaceuticals, even small changes in assumptions about price variability over time implies large differences in the acceptance of new products by HTA and, as Ijzerman and Steuten note, assumptions about price variability over time can have a strong influence on product development decisions. Similarly, Firth’s work provides evidence of PLC effects making a real and practical difference to the availability of a life-saving device.

Since price variation over time is one of the characteristics of PLC, this suggests that predicting the future shape of the PLC for a product category is very important for both suppliers and purchasers in pharmaceuticals and medical devices. Different predictions about the shape of a product category life cycle might be expected to lead to different decisions either to develop a product or to grant it access to an economically regulated market. Such differences in decision have real and direct effects on patients’ lives, on the investment decisions of manufacturers and the funding strategies of healthcare providers. It is perhaps rare to see a concept in strategic management that has such a direct influence on lives and economies.

Given the global importance of healthcare spending and technological innovation, it is at first surprising that PLC effects have not been considered more fully in both product development and HTA. We may speculate that there are two reasons for this. Firstly, a simple lack of utility. At present, our understanding of and our ability to predict the PLC of a product category is, on the basis of existing work, not good enough to inform either supply side or demand side decisions. This would suggest that more research is needed in this area, perhaps by using the postulated factors above to examine and compare the historical life cycles of several product categories, in order to refine and develop our understanding of this important area. Secondly, this might be seen as an example of specialisation without integration between two scientific domains. Both health economists, in the field of HTA and management scientists, in the field of PLC, are exploring an academically interesting and practically important area but, as is not unusual in advanced research, without synthesising their separate but complementary domains. It is towards such a valuable synthesis that this article seeks to contribute.

Footnotes

Author Biographies

Brian D Smith is an adjunct Professor at SDA Bocconi in Milan and a visiting research fellow at the Open University in UK. His research concerns how firms in medical markets create and implement competitive strategies and he has published over 250 papers, books and articles in this area. He is also a Managing Consultant of Pragmedic, a specialist strategy consultancy.

Rosanna Tarricone is Director of CERGAS and Associate Professor in Public Administration at Universitá Bocconi. She is Director of the Master of International Health Care Management, Economics and Policy (MIHMEP) at SDA Bocconi School of Management. She graduated in Business Administration at the Bocconi University, MSc in Health Services Management and PhD in Economics at the University of London. Her main areas of research are HTA, health care management, health economics, economic analysis of health care services and health policy with a special focus on to different health care systems. She is author of many research papers in health economics, health policy and of textbooks on Economic Evaluation Analysis and Management of health care programmes and medical technologies. She is Scientific Director of the European Health Technology Institute for Socio-Economic Research.

Vincenzo Vella was a Research Assistant and Teaching Fellow at SDA Bocconi and is now Junior Executive at Casa di Cura La Madonnina – Gruppo Ospedaliero San Donato in Milano, Italy.

References

Gallio

Berto

. Health technology assessment (HTA): definition, role and use in the changing healthcare environment. Eur Ann Allergy Clin Immunol 2012; 39(Special Issue): 7–11.

Drummond

Griffin

Tarricone

. Economic evaluation for devices and drugs -same or different? Value Health 2009; 12(4): 402–404.

Rogers

. The diffusion of innovations, 1st edn. New York: Free Press, 1962.

Dean

. Pricing policies for new products. Harvard Bus Rev 1950; 28(6): 45–53.

Mercer

. A two-decade test of product life cycle theory. Br J Manage 1993; 4(4): 269–269.

Levitt

. Exploit the product life cycle. Harvard Bus Rev 1965; 43(6): 81–94.

Levitt

. Putting the product life cycle to work. Manage Rev 1966; 55(1): 19–19.

Cox

WEJ

. Product life cycles as marketing models. J Business 1967; 40(4): 375–384.

Polli

Cook

. Validity of the product life cycle. J Business 1969; 42(4): 385–400.

10.

Hofer

. Towards a contingency theory of business strategy. Acad Manage J 1978; 18(4): 784–810.

11.

Dhalla

Yuspeh

. Forget the product life cycle concept!. Harvard Bus Rev 1976; 54(1): 102–112.

12.

de Kluyver

. Innovation and industrial product life cycles. California Manage Rev 1977; 20(1): 21–33.

13.

Thorelli

Burnett

. The nature of product life cycles for industrial goods businesses. J Market 1981; 45(4): 97–108.

14.

Day

. The product life cycle: analysis and applications issues. J Market 1981; 45(4): 60–67.

15.

Paley

. A strategy for all ages. Sales Market Manage 1994; 146(1): 51–52.

16.

Christiansen

Varnes

Gasparin

. Living twice: how a product goes through multiple life cycles. J Product Innovat Manage 2010; 27(6): 797–827.

17.

Bayus

. Are product life cycles really getting shorter? J Product Innovat Manage 1994; 11(4): 300–308.

18.

Golder

Tellis

. Growing, growing, gone: cascades, diffusion, and turning points in the product life cycle. Market Sci 2004; 23(2): 207–218.

19.

Chandrasekaran

Tellis

. Getting a grip on the saddle: chasms or cycles? J Market 2011; 75(4): 21–34.

20.

Bohlmann

Calantone

Meng

. The effects of market network heterogeneity on innovation diffusion: an agent-based modeling approach. J Product Innovat Manage 2010; 27(5): 741–760.

21.

Schon

. The displacement of concepts, London: Tavistock, 1963.

22.

Hill

Westbrook

. SWOT analysis: it's time for a product recall. Long Range Plan 1997; 30(1): 46–52.

23.

Smith

Awopetu

. Mind set and market segmentation in pharmaceutical industry: an assessment of practice in the UK. J Pharmaceut Market Manage 2007; 17(3/4): 101–101.

24.

Grabowski

Vernon

DiMasi

. Returns on research and development for 1990s new drug introductions. PharmacoEconomics 2002; 20(15): 11–29.

25.

Di Masi

Hansen

Grabowski

. The price of innovation: new estimates of drug development costs. J Health Econom 2003; 22: 151–185.

26.

Bruce

. Defending value and maximising profitability of innovative pharmaceuticals over their entire life cycles. Int J Med Market 2003; 3(3): 195–195.

27.

Hoyle

. Future drug prices and cost-effectiveness analyses. PharmacoEconomics 2008; 26(7): 589–602.

28.

Hoyle

. Accounting for the drug life cycle and future drug prices in cost-effectiveness analysis. PharmacoEconomics 2011; 29(1): 1–15.

29.

Wilkinson

. An introduction to the medical technology industry, Cranfield: Cranfield University/Eucomed, 2008.

30.

Beever

Karbe

. The cost of medical technologies: maximising the value of innovation, New York: Booz, Allen and Hamilton, 2003.

31.

Vallejo-Torres

Steute

LMG

Buxton

. Integrating health economics modeling in the product development cycle of medical devices: a Bayesian approach. Int J Technol Assess Healthcare 2008; 24(4): 459–464.

32.

Ijzerman

Steuten

LMG

. Early assessment of medical technologies to inform product development and market access: a review of methods and applications. Appl Health Econom Health Policy 2011; 9(5): 331–347.

33.

Girling

Young

Brown

. Early-stage valuation of medical devices: the role of developmental uncertainty. Value Health 2010; 13(5): 585–591.

34.

Brown

Meenan

Young

. Marketing Innovation medical device prices follow the experience curve. J Med Market 2007; 7(3): 203–212.

35.

Brown

Meenan

Dixon

. Application of the experience curve to price trends in medical devices: implications for product development and marketing strategies. J Med Market 2008; 8(3): 241–255.

36.

Dixon

Brown

Meenan

. Experiences of new product development in the medical device industry. Med Device Technol 2006; 17(3): 20–22.

37.

Provines

. Overcoming organisational barriers to implementing value-base pricing in the medical device and diagnostics industry. J Med Market 2010; 10(1): 37–44.

38.

Hutchings A. Rewarding innovation? An assessment of the factors that affect price and reimbursement status in Europe. J Med Market 2010; 10(1).

39.

Torbica

Cappellaro

. Uptake and diffusion of medical technology innovation in Europe: what role for funding and procurement policies? J Med Market 2010; 10(1): 61–69.

40.

Cappellaro

Ghislandi

Anessi-Pessina

. Diffusion of medical technology: the role of financing. Health Policy 2010; 100(1): 51–59.

41.

Firth

Cooper

Fearn

. The appropriate role of cost-effectiveness in determining device coverage: a case study of drug-eluting stents. Health Affairs (Project Hope) 2008; 27(6): 1577–1586.