1 Background
1.1 Introduction
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decision support systems helping clinical experts to deal with complicated interventional cases
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better data integration and presentation to avoid information overflow in an area where ever more powerful systems acquire constantly increasing amounts of data
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seamless flow of information among connected medical systems [10]
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usability aspects when developing stronger methods and algorithms that are part of the systems software
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expectations among the user groups that may change around the world. Expectations should be carefully taken into account—for example the iso-centre position of the system should be made adaptable to the height of the operator, or ensuring that disposable medical devices such as catheters are clinically available, e.g., FDA approved, when introducing associated new imaging systems.
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addressing the special needs at each customer site by a special customizable system setup
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straightforward system installation processes avoiding the need of experts that may not be locally available, and
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system concept minimizing total cost of ownership (TCO) to reduce the cost of healthcare and overcome global inequities in access to medical equipment [13].
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expanding development cycles while market cycles are contracting
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increased price and cost pressure
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managing dynamic load on development teams
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controlling and optimizing of project costs and quality.
1.2 Theoretical framework
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the Phase-Review Process by Hughes [24],
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the Stage-Gate Process in its various evolutions by Cooper [25],
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the Value Proposition Cycle by Hughes [24],
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the process model according to Ulrich and Eppinger [26],
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the model of simultaneous activities by Crawford [27],
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the phase model by Brockhoff [30],
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the phase model by Pleschak [31],
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the innovation process according to Witt [32],
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the innovation process according to Vahs [20] and
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the process of the requirements specification engineering according to Ebert [33].
1.3 Methodology
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the collection of sufficient data comprising key process parameters, key roles and key product components of the current processes at a representative manufacturer of angiography systems
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the analysis of this data and the deduction of suitable conclusions and recommendations
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the definition of an appropriate state-of-the-art process model that that meets the above-mentioned requirements with respect to the supply of medical devices for treating deadly diseases such as CAD.
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- process time per topic: time between initial input until realization/ implementation,
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- number of process steps / task owners per topic,
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- time of owning a task,
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- key roles: input provider, connector, problem solver,
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product components essential to the solution.
2 Results
2.1 The definition of a new extended innovation and development process model
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feedback from their use in the clinical routine,
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trends that can be extrapolated from a larger number of iterative enhancements and
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Two sources show the innovation process as closed loop. All other visualized it as unidirectional, one-time effort, which ends with the production or market introduction.
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One source contains quantitative information for problem solving methods.
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users (physicians, medical personnel, consumer, customers, clinical community)
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sales,
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employees as named in the literature are further differentiated in:
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product management including innovation (PLM),
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service,
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customer relationship management (CRM)
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training/ customer education,
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research and development (R&D),
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industry partners (suppliers and industry collaboration partner),
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catalysts,
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competition.
2.2 Quantitative assessment
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20% of the problems in using the medical product were pointed out by the customer and solved by R&D. PLM came up in 5% and CRM in 2% of the topics.
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25% of the problems in using the systems were flagged by sales and solved by PLM. CRM got involved in these in 21% of the cases.
3 Discussion
3.1 Main results
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The defined innovation and development process model reflects the state-of-art, fulfils the requirements towards the supply of angiography systems and is unique in comparison to the well-established models promoted by Brockhoff, Cooper, Crawford, Durfee, Ebert, Eppinger, Hughes, Pleschak, Thom, Ulrich, Vahs and Witt.
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The collection of 672 data points for 302 individual topics taken from the innovation and development process of angiography systems over a period of 47 months allows the assessment of the process time with a statistical power of 0.96.
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The retrospective analysis of this data reveals key process parameters, key process roles, usage of problem-solving methods and key technologies for providing solutions.
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A relation between the number of task owners and process time could be established.
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The working hypothesis was confirmed by identifying a potential of about 15% shorter process time in our data and resulting cost savings that can be realised with a suitable model, a proper setup of the organisation and the empowerment of the employees.
3.2 Implications
3.3 Limitations & future research
Time in weeks | sales | Service | CRM | PLM | R&D |
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min | 1 | 3 | 1 | 0 | 2 |
1. quartile | 4 | 4 | 3 | 3 | 4 |
2. quartile | 7 | 11 | 6 | 10 | 11 |
3. quartile | 16 | 13 | 14 | 20 | 25 |
max | 133 | 13 | 86 | 108 | 34 |
data points | 288 | 8 | 95 | 251 | 98 |