Digital healthcare ecosystems

Service thinking and design: From pipeline to platform

Thorsten Knape; Christoph Rasche

The healthcare sector is beset by digital myths and fads when it comes to the Medicine 4.0 agenda. Digitization and media adoption provide societies and economies with a flurry of business development opportunities. An all-encompassing digital health vision requires a paradigm shift to patient-centric solutions. Prospective MedApps and MedBots must well serve the-end-to-end integration of patient demands across the product lifecycle and product design that can be achieved with the Digital Health Platform Dashboard (DHPD).

1. User-Driven Platform Design: Service Design in Healthcare

Service design and service thinking demonstrate the kernel of a platform of contemporary service management that incorporates the seeds of business model innovation (Rasche/ Margaria/ Floyd 2017). Service design combines the technical as well as the aesthetic and experiential features of service infrastructures, services processes and services outcomes, this way having a strong impact on the perceived benefit of the patient (Margaria 2006). Service design should not be reduced to its technical sphere because wearables or body-near sensor systems interfere with our lifestyles, habits and traits. Service thinking goes beyond pure reconfiguration and optimization: it's about new business model development and innovation in the service sector (Taylor / Ronte / Hammett 2014).

User-driven design and patient focus:

Service thinking determines the future by means of innovative healthcare solutions, by transforming service design plans into action through viable business models in healthcare. Smart services include infrastructures for adaptive therapy, precision medicine, bot-assisted therapies, interactive service robots or big data-based decision support (Rasche 2013). The mantra of Ambient Assisted Living (AAL) promotes the idea of knowledge infused smart homes that automatically take care of our well-being.

The new business models represent the power engines of the healthcare institutions due to their embeddedness in the current ecosystem, the increasing social complexity and the sophisticated technical components. These features make them less vulnerable in the digital world to the omnipresent threat of substitute services to survive the next business tsunami. This could include the digitalization of outpatient care and the surge of distance-based interventions (Rasche, Braun von Reinersdorff, Knoblach & Fink 2017).

2. Digital Health Platform Dashboard: Beyond the business model canvas and pipeline architectures

The competitiveness of the healthcare industry hinges increasingly on the strategic competence to create value for patients, insurance companies, employees and investors alike under conditions of hyper-turbulence. Our main argument for IT-induced change in healthcare is its implication for economic, medical and ethical value creation. Medical outsourcing, remote surgery, telemedicine, homecare networked concepts and real-time computing, as well as AAL solutions can all contribute to higher efficiency and effectiveness without compromising quality. These goals are condensed in the Digital Health Platform Dashboard (DHPD), which resembles in its utilization a unifying tool to co-align dispersed healthcare agents (Alstyne/ Parker/ Choudary 2016)

Digital Health Platform Dashboard (DHPD)

Figure 1: Digital Health Platform Dashboard (DHPD)

The DHPD is still in its infancy as the result of a design thinking process by experts. The philosophy of the approach has been validated in case studies of innovation exploration in the Industry 4.0 context (Steffen & Boßelmann, 2018). Opposite to the business model canvas (Osterwalder & Pigneur, 2011) the DHPD stands for a special purpose approach also incorporating strategy and realization issues such as minimal viable products. The DHPD platform tool can be used to model open, closed or hybrid business models. Commercial agents may interpret and utilize a platform as a transaction-based deal making institution while patients, medical consultants and welfare bodies benefit from special contractual conditions of a platform model. Unlike marketplaces with exclusively digital offerings, the platform has the characteristics of a commercial and social ecosystem when it enables interactions and transactions between platform-registered parties. The platform also promotes app adoption in healthcare by modeling mobile services offerings. Beyond digital marketplaces, with the DHPD-Tool platforms can be designed with a social ecosystem when enabling interactions as well transactions between platform enrolled parties.

3. Outlook

The mantra of digitalization entering the healthcare sector increasingly. Digitalization is characterized by a platform character that leads to a variety of applications and (business) opportunities. It provides a kind of health care master plan for the coordination of hardware (e.g., smartphone), software (e.g. apps), brainware (implicit and explicit knowledge), and peopleware (talent, competence, motivation) to gain competitive advantage.

We would like to take the logic of the "Digital Health Platform Dashboard" as a starting point for digital value transformation in health care, as digital devices or apps and bots only find their usefulness in cases where a high utility value is the basis. The latter "ecosystematically" force the digital value creation of the p2p2p2p2p process in the healthcare sector, whereby the acronym p2p2p2p2p stands for "from the patent over the prototype to the product to the patient for the profit". The digital realization of the DHPD is a topic of future research. To realize the potential of digitalization in healthcare, we should promote digital options on business models, strategies and patient-centered value creation.


Margaria, T./ Steffen, B. (2006): Service Engineering: Linking Business and IT, IEEE Computer, Vol. 39, N. 10, S. 45–55, IEEE CS Press.
Rasche, C./ Margaria, T./ Floyd, B.D. (2017): Service Model Innovation in Hospitals: Beyond Expert Organizations, in: Pfannstiel, M./ Rasche, C. (eds.): Service Business Model Innovation in Healthcare and Hospital Management – Models, Strategies Tools, Wiesbaden, S. 1-19.
Rasche C. (2013): Big Data – Herausforderung für das Management, in: WISU, Jg. 42, Heft 8-9, S. 1076-1083.
Rasche, C./ Braun von Reinersdorff, A./Knoblach, B./Fink, D. (2017): Digitales Unternehmen im Gesundheitswesen, in: Pfannstiel, M.A./ Da-Cruz, P./ Rasche, C. (Hrsg.): Entrepreneurship im Gesundheitswesen III, Wiesbaden, S. 1-31.
Steffen B./ Boßelmann, B. (2018) GOLD: Global Organization alignment and Decision – Towards the Hierarchical Integration of Heterogeneous Business Models. ISoLA (4) 2018: 504-527
Taylor K./ Ronte H./ Hammett S. (2014) Healthcare and Life Sciences Predictions 2020 – A bold future?, Deloitte, London.
Van Alstyne, M. W./ Parker G. G./ Choudary S. (2016): Plattform statt Pipeline. Harvard Business Manager, Juni 2016, S. 22–31.
Osterwalder A./ Pigneur Y. (2011): Aligning profit and purpose through business model innovation, in: Palazzo G., Wentland M. (Hrsg.) Responsible Management Practices for the 21th Century, Paris, pp. 61-75.

de_DEGerman en_GBEnglish