physicians seeking for optimal clinical solutions based on a dual combination of
technology knowledge from firms and clinical knowledge rooted in their own
daily use of medical technology. In that sense, innovation in medical technology
emerges as a result of complex processes where people and artifacts recursively
influence each other.
The involvement of these physicians in user communities such as professional
associations allows medical users to shape perceived merits of new clinical
technologies for a broader community of practice (Pisano, Bohmer, &
Edmondson, 2001).
• Firms (medical imaging manufacturers).
As previously studied, the American, European, and Japanese medical imaging
markets are dominated by a small number of large multinational companies
(Gelijns & Rosenberg, 1999). The rate of innovative activity is high, resulting
in high-performance improvement. At the initial stage of development, manufacturers deliver privileged information to their medical lead users in order to ask
them validating from a clinical standpoint any technology innovation, as previously shown for CT and MR (Das & Ven, 2000). Lately, medical imaging
manufacturers tend to ask these privileged users to become local, regional, or
global “show sites” where the medical imaging system operates in optimized
conditions, under the leadership of opinion–leader physicians, in well-known
hospitals and clinics, creating a “word-to-mouth” marketing effect, in order to
promote firm’s technological innovation (Chatterji, Fabrizio, Mitchell, &
Schulman, 2008; Mitchell & Kulwant, 1996).
• Patients (individuals and emergent concerned groups).
Patients combine the dual role of end user (consumer) and supplier, by providing
physicians with unmet medical needs that may be emphasized by recently
emergent concerned groups (Callon & Rabeharisoa, 2008). Medical innovation
does follow a specific path in the sense that technological innovation is not selfselected but rather socially shaped (Williams & Edge, 1996). The meaning of
technical efficacy and effectiveness is not sufficient for its adoption in healthcare
until some clinical relevance has been demonstrated and legitimated by various
actors, from medical doctors to patients through regulatory bodies (Pisano et al.,
2001). Consequently, technological innovation in healthcare exhibits a “path
dependency” where the set of devices and correlated practices is the result of
negotiations over competing firms, regulatory, medical instances, and public
interests (Webster, 2002). Our framework helps us as well to understand how
technological trajectories and path dependencies in healthcare depend on the
coevolution of social institutions and patient needs. The variety in lifestyle across
countries drives important differences between various national healthcare systems. In our model, patients capture the overall conditions of a given population
and its trends, such as aging phenomenon in Japan, as a possible forcing function
for clinical innovation among the various stakeholders in multiple areas
(Kohlbacher & Herstatt, 2008).
Health Informatics and Co-Innovation: Connecting Patients, Clinical Practice,. . .
113
technology knowledge from firms and clinical knowledge rooted in their own
daily use of medical technology. In that sense, innovation in medical technology
emerges as a result of complex processes where people and artifacts recursively
influence each other.
The involvement of these physicians in user communities such as professional
associations allows medical users to shape perceived merits of new clinical
technologies for a broader community of practice (Pisano, Bohmer, &
Edmondson, 2001).
• Firms (medical imaging manufacturers).
As previously studied, the American, European, and Japanese medical imaging
markets are dominated by a small number of large multinational companies
(Gelijns & Rosenberg, 1999). The rate of innovative activity is high, resulting
in high-performance improvement. At the initial stage of development, manufacturers deliver privileged information to their medical lead users in order to ask
them validating from a clinical standpoint any technology innovation, as previously shown for CT and MR (Das & Ven, 2000). Lately, medical imaging
manufacturers tend to ask these privileged users to become local, regional, or
global “show sites” where the medical imaging system operates in optimized
conditions, under the leadership of opinion–leader physicians, in well-known
hospitals and clinics, creating a “word-to-mouth” marketing effect, in order to
promote firm’s technological innovation (Chatterji, Fabrizio, Mitchell, &
Schulman, 2008; Mitchell & Kulwant, 1996).
• Patients (individuals and emergent concerned groups).
Patients combine the dual role of end user (consumer) and supplier, by providing
physicians with unmet medical needs that may be emphasized by recently
emergent concerned groups (Callon & Rabeharisoa, 2008). Medical innovation
does follow a specific path in the sense that technological innovation is not selfselected but rather socially shaped (Williams & Edge, 1996). The meaning of
technical efficacy and effectiveness is not sufficient for its adoption in healthcare
until some clinical relevance has been demonstrated and legitimated by various
actors, from medical doctors to patients through regulatory bodies (Pisano et al.,
2001). Consequently, technological innovation in healthcare exhibits a “path
dependency” where the set of devices and correlated practices is the result of
negotiations over competing firms, regulatory, medical instances, and public
interests (Webster, 2002). Our framework helps us as well to understand how
technological trajectories and path dependencies in healthcare depend on the
coevolution of social institutions and patient needs. The variety in lifestyle across
countries drives important differences between various national healthcare systems. In our model, patients capture the overall conditions of a given population
and its trends, such as aging phenomenon in Japan, as a possible forcing function
for clinical innovation among the various stakeholders in multiple areas
(Kohlbacher & Herstatt, 2008).
Health Informatics and Co-Innovation: Connecting Patients, Clinical Practice,. . .
113