different clinical areas and domains of know-how (Nelson, 2003). The proposed
model of innovation suggests that technological advance follows an evolutionary
process in the sense that it derives from technological change, clinical practice, and
understanding of several actors, beyond a strict planning of a scientific search
(Gelijns, 1991). The model presumes that it is determined by consensus of a
technological community who are cooperatively involved in advancing the art
(Powell, Koput, & Smith-Doerr, 1996) and in exchanging information, as shown
in the relational trajectory of medical knowledge through medical publications
(Mina et al., 2007).
The coevolution is of firm technology, physicians in non-firm organizations, and
unmet patient needs. Because coevolutionary innovation—defined as the joint
development and implementation of a new product or service by one firm and at
least one medical user to solve patient problems—is characterized by differentiation
from firm technological knowledge, accessing medical user knowledge is paramount. This knowledge is difficult to transfer (i.e., “sticky”) because it is rooted in
the accumulated experiences of the medical users. More broadly, the model builds
on the coevolution of interrelated organizations and the institutional context in which
they cooperate in order to produce innovative products and solutions.
The supply-side and the demand-side interact according to a coevolutionary
pattern: firms request opinion-leading medical organizations to define their
medical-oriented needs. The field study describes the specific elements and some
causal drivers of this co-evolution process. This coevolution has two distinct stages
or aspects: one, which moves from variation to selection, one from selection to
adoption as illustrated in Fig. 5.
This means that the evolution of scanning techniques is essentially interdisciplinary and interinstitutional in nature; that is, it requires the medical profession to create
alliances with scientists and technologists, often in industrial firms with expertise in
scanning techniques, image processing, and image post-processing. These interactions between clinicians, often in academic medical centers, as illustrated by our field
study, and technologists, often in industrial firms, are important for the development
of first-generation clinical solutions. Yet in medicine, where research and development (R&D) and adoption are closely linked, the rate and direction of the subsequent
improvement process are also linked to the experience of the early medical users and
by the effectiveness with which the lead user information is fed back to the device
manufacturer.
2.6 Co-Creation Service Innovation Model in Radiology
Informatics
This view contributes to bridge service system and lead user innovation in the
context of progress in healthcare by focusing on the unique processes linked to
user knowledge for incumbent service innovation. Medical users hold potential
Health Informatics and Co-Innovation: Connecting Patients, Clinical Practice,. . .
115
model of innovation suggests that technological advance follows an evolutionary
process in the sense that it derives from technological change, clinical practice, and
understanding of several actors, beyond a strict planning of a scientific search
(Gelijns, 1991). The model presumes that it is determined by consensus of a
technological community who are cooperatively involved in advancing the art
(Powell, Koput, & Smith-Doerr, 1996) and in exchanging information, as shown
in the relational trajectory of medical knowledge through medical publications
(Mina et al., 2007).
The coevolution is of firm technology, physicians in non-firm organizations, and
unmet patient needs. Because coevolutionary innovation—defined as the joint
development and implementation of a new product or service by one firm and at
least one medical user to solve patient problems—is characterized by differentiation
from firm technological knowledge, accessing medical user knowledge is paramount. This knowledge is difficult to transfer (i.e., “sticky”) because it is rooted in
the accumulated experiences of the medical users. More broadly, the model builds
on the coevolution of interrelated organizations and the institutional context in which
they cooperate in order to produce innovative products and solutions.
The supply-side and the demand-side interact according to a coevolutionary
pattern: firms request opinion-leading medical organizations to define their
medical-oriented needs. The field study describes the specific elements and some
causal drivers of this co-evolution process. This coevolution has two distinct stages
or aspects: one, which moves from variation to selection, one from selection to
adoption as illustrated in Fig. 5.
This means that the evolution of scanning techniques is essentially interdisciplinary and interinstitutional in nature; that is, it requires the medical profession to create
alliances with scientists and technologists, often in industrial firms with expertise in
scanning techniques, image processing, and image post-processing. These interactions between clinicians, often in academic medical centers, as illustrated by our field
study, and technologists, often in industrial firms, are important for the development
of first-generation clinical solutions. Yet in medicine, where research and development (R&D) and adoption are closely linked, the rate and direction of the subsequent
improvement process are also linked to the experience of the early medical users and
by the effectiveness with which the lead user information is fed back to the device
manufacturer.
2.6 Co-Creation Service Innovation Model in Radiology
Informatics
This view contributes to bridge service system and lead user innovation in the
context of progress in healthcare by focusing on the unique processes linked to
user knowledge for incumbent service innovation. Medical users hold potential
Health Informatics and Co-Innovation: Connecting Patients, Clinical Practice,. . .
115