Final presentation for Service Innovation course

1. Service Innovation in
Healthcare: A Path to
Value Constellations
Mahmoud Elzein
Cecily Quintana
Karen Shrock
Merissa Sibley
Spring Wedlund
MKTG 410
Service Innovation
Spring 2013
Dr. Harmon
June 3, 2013
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2. Agenda
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Intro to Service Innovation in Healthcare……………….3
Recap of findings…………………………………………………4-9
Telemedicine Case Study 1………………………………10-13
Telemedicine Case Study 2………………………………14-16
Telemedicine Case Study 3………………………………17-19
Co-creation Innovation Model: The Portland
Experience……………………………………………………...20-29
• Conclusion……………………………………………………………30
• Future Research……………………………………………………31
• References………………………………………………………32-33
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3. Regulations and Stakeholders
Major regulations that will affect the future of innovation in healthcare include:
• American Recovery and Reinvestment Act (ARRA) 2009, enacted the Health Information Technology for
Economic and Clinical Health Act (HITECH Act). Under ARRA the US Department of Health and Human
Services (HHS) is spending $25.9 billion to promote and expand the adoption of health information
technology.
• Patient Protection and Affordable Care Act (PPACA) 2010, also known as “Obamacare”, will require all
Americans to have health insurance. This affects service innovation of healthcare because as a country
that is trying to provide affordable healthcare to all citizens, the goal is to find a cost-effective method to
achieve this, while reducing waste and inefficiencies within the system.
Regulatory bodies under HHS that impact service innovation in healthcare include:
• Agency for Healthcare Research and Quality (AHRQ)
• Centers for Disease Control and Prevention (CDC)
• Centers for Medicare and Medicaid Services (CMS)
• Health Resources and Services Administration (HRSA)
• National Institute of Health (NIH)
Stakeholders:
• Doctors, nurses, healthcare providers, front & back office staff
• Customers: patients, caregivers, and families
• Communities
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4. Early Technology Barriers
Benefits of technology
•
•
•
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Improved quality
Prevent medical errors
Reduce health care costs
Increase administrative efficiencies
Decrease paperwork
Expand access to affordable care
Overview
Interviews with IT
experts from for
medical universities
and health provider,
and a medical
research expert
Issues to Overcome
• Managers & policy makers lack of access
to information
• Gaps in care provided
• Inconsistent quality among professionals
• High expenditures, lack of infrastructure
• Legal and privacy issues
• Limitations of individual technologies
Significance
Future Research/Challenges
Application
As of 2008: Service portion of health care is not as advanced
in technology as other service industries. Health care is not
taking advantage of improving efficiency and quality. The
authors foresee the following benefits of better technology
for a health care provider: improve health care quality,
prevent medical errors, reduce health care cost, increase
administrative efficiencies, decrease paperwork, and expand
access to affordable care
Health care data have diverse information
but staff representing many fields ranging
from medical to administrative will be using
it. A major challenge will be to get the
collective responsibility of government,
managers, planners, and policy makers.
Future research: E-health, wearable
monitors, radio frequency identification
The health care service
industry can highly benefit
from using technology to
increase efficiency and health
care quality while reducing
costs.
4

5. Frameworks
Impact of Network and Environmental Factors on SI
• Looked at the direct and indirect effects of formal and
informal institutional pressure, and competitive pressure on SI
in healthcare.
• Found that large networks and informal regulatory forces limit
and even stifle providers’ service innovation, while
competition increases it.
• Questions whether regulation is good for SI.
Experience-based Design: Reframing
• Identify every touch point where customers interact with
healthcare service, identify best and worst practices, and
work with patients and providers to design healthcare
experiences, versus systems and processes.
• Open Door Community Hospital prototype
Balanced Scorecard Study in Taiwan
• First study to shed light on the role of department-level
strategic planning tool for service innovation.
• Interactive system for providing signals to the organization
about management objectives, stimulating debate, improving
quality, and achieving organizational learning
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6. Innovative Solutions
Medical Tourism:
• Increasing in popularity due to increases in medical
costs in developed countries, diminishing staff,
increased pressure of aging populations, long wait
times, and globalization
• Lack of global governing legislation and benchmarks
for medical tourism enterprises creates a barrier for
many consumers
Remote Healthcare:
• Remote patient monitoring (RPM) enables monitoring of patients outside conventional clinical
settings (e.g. in the home). May increase access to care and decrease healthcare delivery costs
• MeMD based in Albuquerque, NM offers doctors’ visits and urgent care services over the internet,
webcam and telephone , 24 hours a day, seven days a week
• Telecardiology uses electrocardiogram (ECG) signals from a patient, acquired by sensors, and
transmits them in real time to medical personnel across a wireless network
• INCASA, an IT SI architecture unlike any other remote healthcare model. Focuses on citizen-centric
technologies that protect frail, elderly people, prolonging the time they can live well in their home
• Teledermatology represents part of a general shift in medicine towards the increasing use of
technology to address problems of inefficiencies in healthcare provision in the context of increasing
demand for services, and to overcome inequities in access to services across geographical regions.
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7. IT: Enabling Healthcare Service Innovations
Four major areas in which (IT) will revolutionize healthcare:
• More offshore services (Telemedicine and Teleradiology)
• Integration of health information systems (RFID, electronic personal health
record solutions (ePHR), and electronic clinician record solutions (eCHR)
• Drug safety monitoring on a global scale (Medwatch)
• More high quality information to doctors and patients (WebMD, Epocrates)
The role of SmartPhones and Smart Devices:
• Patient care and monitoring (iWander, Diabeo and other similar apps)
• Health apps for the layperson (iTriage, ZocDoc, fitness, weight loss, etc.)
• Communication, education, and research (“Outbreaks Near Me” app, etc.)
• Physician or student reference apps (Epocrates, Skyscape, etc.)
• Context Awareness Computing – the Future of Healthcare
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8. The Linear Innovation Model
Step by step process that hinders co-creation. Patients, caregivers and medical providers and
staff must be able to communicate their needs with each other, and to be able to integrate and
translate those needs into ideas that engineers can understand in order to provide IT solutions
that improve the service for all stakeholders. Therefore a new model is required that will allow
for this communication exchange to take place: a Co-Creation Model.
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9. The Co-creation Service Innovation Model
Co-experience: Enabling the co-creation of an environment where personalized, evolvable experiences are
the goal, and products and services are a means to that end. Co-experience is the result of medical lead users
co-creating their own unique value with patients, supported by technological change from firms and a
community of practice.
Co-definition: When physicians use and experiment with medical solutions among their patient
communities a collaborative learning process occurs, where firms and medical lead users learn from each
other and build a shared knowledge model, or co-definition.
Co-elevation: Creation of a positive
feedback loop when knowledge from
one entity is diffused among other
entities, therefore closing the cognitive
knowledge gap among practitioners,
and service to patients.
Co-development: Co-innovation
generated by the relations among the
various entities. The cognitive gap
among entities is the driver of a
collaborative process where entities
exchange heterogeneous knowledge
bases to contribute to a codevelopment of solutions.
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10. Successful Telemedicine Case Study
Alaska’s Underserved: Throughout 2011, provide breast cancer risk-reducing counseling for high risk
native Alaskan women.
Collaboration:
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Alaska Native Medical Center: Main hub of medical care for native Alaskans supporting regional
clinics throughout Alaska.
Mayo Clinic Breast Clinic: Provided specialized breast cancer physicians for the counseling.
Mayo’s Center for Innovation: Employed a team to design and enable the telehealth platform.
Alaska Federal Health Care Access Network: provided telehealth sharing of medical information
through firewalls.
Model:

Using a navigator to facilitate patient interactions, subscription billing contract, and a Cisco networking system
handling audio and video conferencing to connect Alaskan clinic to Mayo physician.
Overview
Significance
Future Research/Challenges
Application
Survey recipients after
implementing the telemedicine
service model which consisted of a
Cisco network system that allowed
both video and phone
communication
Overwhelming success with remote
patients. Overall satisfaction was
99%. The lowest rate of 93% was for
quality of seeing and hearing the
specialist. There were three rated
100%: satisfied with consultation,
questions answered, and patient
would use telemedicine service
again.
Better implementation strategies
would help reduce costs. And
future locations need to be
closer to patient's home. Need to
expand licensing and credentials
for US-wide telemedicine license.
Government needs to lift barriers
of licensing that discourage
telehealth models.
With the use of a person
facilitating the process,
telemedicine can be well
received by patients. Once
implemented it is possible to
reduce costs and stress of
traveling for patients when a
specialist in another city is
needed.

11. Successful Telemedicine Model
Source: Pruthi, 2013

12. Successful Telemedicine Findings
Survey: Random sample of 60 patients were selected, 15 (25%)
recipients completed the survey.
Source: Pruthi, 2013

13. Successful Telemedicine Lessons Learned
Authors’ Key Takeaways:
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Make sure enough time is scheduled for implementation of the model.
Technology is matching for all involved and support is available.
Logistics for dual site coordination, transfer of medical records and maintaining
documentation.
Cost of coordination and downloading of patient records.
Scheduling appointments, licensing, and credentialing
Recruitment of dedicated navigator and telehealth coordinator.
Future Research:
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Appropriate reimbursement payment models need to be supported by
government procedures.
Lifting of licensure barriers to expand to additional remote areas closer to
patient’s home.
Integration into collaborating clinics varying workflows due to differing size,
location, and specialty care.

14. Case Study: Teledermatology
The U.K.’s Underserved: Throughout 1994-2005, provide dermatology access remotely to patients in the
U.K., where inequities in access to services across geographical regions result in long waiting lists.
Collaboration:
•
National Health Service (NHS) provision of teledermatology in the U.K. consisting of 12 known
services dating back from 1994 to 2006.
• One government sponsored (T1)
• A commercial provider (no longer in operation – T4)
• Research studies that were discontinued (T2, T3, T5, T6)
• GP-based systems still in operation (T7, T8, T10)
• Nurse-led systems still in operation (T9, T11, T12)
Methods:
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A longitudinal (1997-2005) qualitative study was conducted in the U.K. including data from indepth semi-structured interviews, observations of systems in practice, and public meetings
Overview
Significance
Future
Research/Challenges
Applications
Paper identifies factors that promote successful use
of teledermatology as a part of routine service
provision. A longitudinal qualitative study of
teledermatology was conducted, drawing on data
from in-depth structured interviews; observations of
systems in practice; and public meetings. Data was
analyzed collectively by the research team using
established qualitative techniques to identify key
thematic categories.
This study is unique in that is analyzes
the development of most of the known
teledermatology services on a national
level (in the U.K.), over a significant
period of time (8 years), thus providing a
sound analysis of the differences
between success and failure in
implementation efforts in this context.
The original 'policy' vision
of how teledermatology
would be utilized, as a
technological fix for long
waiting lines and
consultant shortages,
failed to be realized.
This technology is
revolutionary to service
innovation in the field of
healthcare. However, it
brings up some questions
and fears among
practitioners who must
implement it. In order to
provide truly innovative
service, what are the
ethical and political
implications?
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15. Teledermatology
Teledermatology has been practiced
both in real time through the use of live
interactive videoconferencing and as
store-and-forward systems which
transmits still images and textual
information for remote assessment and
later view. There has been considerable
global research done to demonstrate
and evaluate the potential of
teledermatology. In the U.K, efforts were
initially focused on real-time
teledermatology, but store-and-forward
systems have become increasingly
preferred as being more cost-efficient
and convenient for health care providers.
Teledermatology is also used for various
purposes, including triage, diagnostic
and management services, and
advice/opinion for primary care
practitioners.
Finch, Tracy L., F.S. Mair, and C.R. May. (2006) “Teledermatology in the U.K.: Lessons in Service Innovation.”
British Journal of Dermatology, 156 (June) 521-527.

16. Teledermatology Lessons Learned
Author’s Key Takeaways:
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By enabling access to specialist services remotely, teledermatology has the potential to revolutionize
the delivery of dermatology services.
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Results of the study indicated that requirements for using and integrating teledermatology into
practice include:
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Perceived benefit and relative commitment that outweighs effort
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Pragmatic approaches to proving efficacy and safety
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Perception of risk as being manageable on the basis or professional judgment
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High levels of flexibility in practice (in terms of individuals, technology and organization)
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Reconceptualizing professional roles
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Political support
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Successful execution of teledermatology as a routine service necessitates better understanding of and
attention to the relationship between technical and social aspects of teledermatology, and how this is
accommodated by health care professionals and the organizations in which they work.
Challenges:
•
Respondents of the study questioned whether the additional effort needed to conduct
teledermatology was worth it, unless the objectives were clear.
•
Concerns were occasionally raised about whether teledermatology services and telehealthcare
services in general, were trying to shift responsibility for care from secondary to the primary care
sector.
Finch, Tracy L., F.S. Mair, and C.R. May. (2006) “Teledermatology in the U.K.: Lessons in Service Innovation.” British Journal
of Dermatology, 156 (June) 521-527.

17. Failure in Telemedicine
Case Study
Michigan’s Underserved: isolated Beaver Island, MI, population 550, encounters harsh weather and
transportation issues to and from the island, making it difficult to obtain emergency or specialized
healthcare.
Collaboration:
• Beaver Is. Rural Health Center: Gatekeeper for island health services, providing a full range of
primary care and minor emergency services
• Healthcare organizations and health related educators in the region
Model in Theory:
• Create Telemedicine technical infrastructure
• Staff clinic with a second nurse practitioner or physician assistant
• Build a new heath-care complex that supports telemedicine
• Increase in-home access to telemedicine
Overview
Significance
Future Research/Challenges
Application
Case study of a success and failure
in two rural telemedicine projects.
Multiple data collection strategies
were employed during the study
period of one year. Methods
included patient, administrator
and health service provider
interviews, surveys of physicians,
nurses and patients, clinical
outcomes, and archival data.
This study shows that in t is imperative
to have resources and expertise in place
to ensure success. In addition, success
was due to a more formalized
organizational structure for the
telemedicine application. Telemedicine
programs must not exist in a vacuum and
must exist in a larger healthcare
organization that has been carefully
examined.
Rural communities lack essential
resources including technical
infrastructure and support, stable
administrative staff and long term
financial support. There are existing
successful models in telemedicine
that must be researched going
forward to enable the success of
future projects.
By studying the effects of not
having a co-creation or
constellation service innovation
model in place, future rural
telemedicine projects can learn
valuable lessons regarding the
early identification of major
barriers an/or inefficiencies
before embarking on a
telemedicine project in their
communities
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18. Failure in Telemedicine
Lack of Service Innovation Model
No initial adoption of a co-creation or value
constellation service innovation model
Lack of technical infrastructure or innovations to support
service distribution
•
No defined model of service innovation created through
collaboration between patients, the Beaver Island Medical
Board and mainland healthcare organizations
•
No co-definition process built on shared knowledge
between experienced practitioners of telemedicine and the
key stakeholders of the Beaver Island project.
•
Unable to contain costs in order to create a stable network
structure that would create a successful telemedicine
model.
•
No co-creative “Value Constellation” conceptual flowchart
created emphasizing the collaborative, collective, and path
dependent function of innovation.
Co-Definition:
Shared access that integrates all
participating entities user-based
knowledge.
Requires I.T. infrastructure.
Requires cross licensing agreement,
joint patents, co-innovation patents.
Requires knowledge management
model.
Requires diluting exclusive property
rights control in order to pursue joint
invention.
Requires access and communication
between health providers L.I.M.S. and
manufacturers M.E.S.
Co-Elevation:
Value generated from one particular
entity, in which the value generated
diffuses among the other entities.
Entity focused, in terms of coinnovation led by particular group.
Diffusion
•
Co-Experience:
Enables the co-creation of an
environment.
Personalized, evolvable experience are
the goals.
Requires I.T. infrastructure for
communication exchange.
Requires cross licensing agreement.
Requires custom co-experience
function in H.I.T. system.
Requires knowledge management
model.
Adoption
•
Co-Development:
Co-innovation generated by the
relation among the various entities.
Entities exchange heterogeneous
knowledge to contribute to co
development solutions.
Relation focused, in terms of coinnovation generated by the relation
among various entities.
Whitten, Pamela, Inez Adams (2012), "Success and Failure: a Case Study of Two Rural Telemedicine Projects." Journal of
Telemedicine and Telecare, 9(3), 125-129.
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19. Issues in Telemedicine
Lessons Learned
Authors’ Key Takeaways:
o
o
Telemedicine programs must be positioned within a larger health organization rather than operate in a
vacuum
The people who would benefit most from telemedicine face the greatest barriers due to lake of essential
resources including:
o Technical
o Lack of telecommunications infrastructure in rural communities that would enable the
transmission of data and video
o Unreliable mode of transportation for shipping key equipment and supplies
o Unreliable technical support in the case of system failures or equipment malfunction
o Administrative
o Lack of qualified health professionals in the rural communities
o High turnover of key personnel
o Resistance from mainland doctors to use telemedicine to treat patients
o Financial
o No stable funding source
o Community reliant on grants and volunteerism to keep programs afloat
Future Research:
o
Organizational and cultural models that focus on fiscal, geographical, technical and personnel
environments to ensure successful telemedicine projects in rural communities
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20. New Model: A Co-Creative Value
Constellation
 New Model:
 A conceptual flowchart indicating heterogeneous entities and
their relationships in a context of co-creation for medical
innovations, in which technological innovation is a service
distribution function among entities
 Enables firms, manufacturers, researchers, and medical lead
users to be included in a different conception of “open
innovation”
 Emphasizes the collaborative, collective and path-dependent
function of innovation in medical technology and the salient
aspect for service innovation through medical lead users
organized within a community of practice
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21. New Model: Co-Creative Value
Constellation Flowchart
Tech
H3
H2
H1
H.I.T. Co Exp
H.I.T.
H.I.T. Co Exp
CoExperience
CoDefinition
F1
Co Exp
CoElevation
CoDevelopment
F2
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22. Path Dependencies for Co-Creative (VC)
Flowchart
 Success of flow chart relies on all participants:
 Initiated into co-creation initiative by firm
 Connected by common mission, vision, goals, and values
 Connected by compatible I.T. infrastructures
 Connected by contracts of joint invention, cross-licensing
agreement, joint patents, co-innovation patents
 In agreement over the knowledge management model for coexperience and co-definition function
22

23. Co-creation Service Innovation Model
Co-Definition:
Shared access that integrates all
participating entities user-based
knowledge.
Requires I.T. infrastructure.
Requires cross licensing agreement,
joint patents, co-innovation patents.
Requires knowledge management
model.
Requires diluting exclusive property
rights control in order to pursue joint
invention.
Requires access and communication
between health providers L.I.M.S. and
manufacturers M.E.S.
Overview
Significance
A service dominant logic to thinking
about medical innovation in terms
of service provision, in which
technological innovation is a
service distribution function among
entities. The view contributes to
bridge service systems 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.
The model explores and elaborates on
the concept of value co-creation by
distinguishing different underlying stages
for its generation and diffusion, and it
develops a model of service innovation
from a complex and adaptive network of
defined entities, namely, firms, medical
organizations and patients. Lead user
knowledge, both in relation to the entity
where it is generated and to the
interactions among other entities, can
affect future service innovation.
Co-Elevation:
Value generated from one particular
entity, in which the value generated
diffuses among the other entities.
Entity focused, in terms of coinnovation led by particular group.
Diffusion
Adoption
Co-Experience:
Enables the co-creation of an
environment.
Personalized, evolvable experience are
the goals.
Requires I.T. infrastructure for
communication exchange.
Requires cross licensing agreement.
Requires custom co-experience
function in H.I.T. system.
Requires knowledge management
model.
Co-Development:
Co-innovation generated by the
relation among the various entities.
Entities exchange heterogeneous
knowledge to contribute to co
development solutions.
Relation focused, in terms of coinnovation generated by the relation
among various entities.
Future Research/Challenges
“Spill overs” of knowledge and
their artifacts, patents and
licenses, are therefore limited to
allow knowledge transfer
between users and firms.
Co-definition process requires a
shared knowledge model built
between firms and medical lead
users where learning from each
other is pivotal.
Driven by the capabilities of I.T.
Application
In depth exploration of innovation process for
new ideas into the ongoing debate over a costcontainment environment and medical
technological innovation.
The very network structures that support the
discovery and the diffusion of clinical
innovations represent an important and unique
repository of outside knowledge that can be
accessed by firms. Along with other firms and
universities for basic research, medical lead
users can now be included in a different
conception of “open innovation”
Galbrun, J.; Kijima, Kyoichi (2010), “Innovation in Medical Imaging Technology: Toward a Systemic Service Perspective,”
Service Systems and Service Management (ICSSSM), 2010 7th International Conference on, 1(7) 28-30.
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24. Path Dependencies for Model: CoCreative Service Innovation Model
Co-Definition:
Shared access that integrates all
participating entities user-based
knowledge.
Requires I.T. infrastructure.
Requires cross licensing agreement,
joint patents, co-innovation patents.
Requires knowledge management
model.
Requires diluting exclusive property
rights control in order to pursue joint
invention.
Requires access and communication
between health providers L.I.M.S. and
manufacturers M.E.S.
Co-Elevation:
Value generated from one particular
entity, in which the value generated
diffuses among the other entities.
Entity focused, in terms of coinnovation led by particular group.
Diffusion
Adoption
Co-Experience:
Enables the co-creation of an
environment.
Personalized, evolvable experience are
the goals.
Requires I.T. infrastructure for
communication exchange.
Requires cross licensing agreement.
Requires custom co-experience
function in H.I.T. system.
Requires knowledge management
model.
Co-Development:
Co-innovation generated by the
relation among the various entities.
Entities exchange heterogeneous
knowledge to contribute to co
development solutions.
Relation focused, in terms of coinnovation generated by the relation
among various entities.
24

25. Path Dependencies for Model: Patents

Patents represent valuable innovation milestones within R&D strategies and inform the future market options
available to a firm

Co-innovation patents, joint patents, cross licensing agreements enable joint invention strategies in which firms
leverage and share knowledge that may have utility for each individual participant, which can lead to synergetic
outcomes beyond the individual knowledge inputs

Before agreeing to joint invention strategies participating entities should:
 Balance intellectual and transactional ownership costs and interests that arise from jointly owned inventions
 Consider how collaboration addresses the interests and private benefits of the external actors participating
 Understanding why, when, and with whom firms should consider diluting exclusive property rights control in
order to pursue joint inventions
Overview
Significance
Study proposes that capabilities
evolve by way of a firm’s solo and
joint invention experiences, and
contends that these capabilities are
uniquely shaped by the firm’s
history of patenting with two
specific types of ties, upstream and
down stream
Prior joint invention experiences
diversifies the capabilities of the firm and
broadens its strategic options.
Capabilities evolve differently according
to the firms unique joint invention
experiences
Future Research/Challenges
Path-dependent outcomes are difficult to
untangle with aggregated patent data.
Initially, firms regard joint-patents as a
“second best option” to solely owned
patents.
Application
Research on How R&D strategies impact
capability development. Research on
capabilities by accounting for how the
path dependent role of shared property
rights influences the technological
trajectory of the firm Research on joint
invention conditions and the moderating
roles
Khoury, T. A., Pleggenkuhle-Miles. E. (2011). “Shared Inventions and the Evolution of Capabilities: Examining the
Biotechnology Industry.” Research Policy, 40(7): 943-956
25

26. Path Dependencies for Model:
I.T. Infrastructures
I.T. system
Definition
Functions
Application
Health information
technology H.I.T.
Umbrella framework to describe
the comprehensive management
of health information across
computerized systems and its
secure exchange between
consumers, providers,
governments, and quality entities
Improve healthcare quality and
effectiveness. Reduce health care
costs. Technical and social
framework that enables
information to move electronically
between organizations. Tracks data
overtime. Sharing laboratory
results with providers.
Source for data exchange from
lead user to external entities
Laboratory information
management system
L.I.M.S.
A software based laboratory and
information management system
that offers a set of key features
that support a modern laboratories
operations.
Enables workflow and datatracking support. Flexible
architecture. Enables smart data
exchange interface
A functional database that can be
used to exchange qualitative and
quantitative data from lead users
to external entities
Manufacturing execution
systems
M.E.S.
Concept conceived from the
demand on the manufacturing
enterprise to fulfill the
requirements of the markets from
a point of view of reactivity,
quality, respect of standards,
reduction in costs, and deadlines
operations scheduling, resource
allocation and status, dispatching
production units, document
control, product tracking and
genealogy, performance analysis,
labor/
maintenance/process/quality
management, data
collection/acquisition
Program provides a common user
interface and data management
system for integrating multiple
point systems.
Stephan, C., Kohl, M., Turewicz, M., Podwojski, K., Meyer, H. E. and Eisenacher, M. (2010), Using Laboratory Information
Management Systems as central part of a proteomics data workflow. Proteomics, 10: 1230–1249.
doi: 10.1002/pmic.200900420
B. Saenz de Ugarte, A. Artiba, R. Pellerin (2009), “Manufacturing Execution System-A literature review.” Production
Planning & Control, 20(6)
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27. Path Dependencies for Model:
Shared Knowledge Management Model
•
Knowledge management (KM) is a concept that has been applied in other settings to
explain performance differences among organizations and improve outcomes.
•
(KM) reflects an integrated framework focusing on effective knowledge process
management to impact performance and work relationships in ways that enhance learning
and decision making
•
(KM) model consists of:
• Enablers – provide the foundation necessary for the organization to increase its
effectiveness
• Critical processes – basic operations
• Outcomes of (KM) – facilitates decision making, sense making, and learning to achieve
mission and enhance performance
Overview
Significance
Future Research/Challenges
Application
In an environment of burgeoning body of healthcare
research and the adoption of technology tools,
physicians can benefit from understanding effective
(KM) practice. A (KM) model is presented that borrows
from recent information science scholarship in (KM) and
is intended to inform intervention protocols for
effective (KM) to improve quality of care
(KM) is a beneficial
framework to help
healthcare professionals
manage their practices
and ultimately
administer quality care
to their patients.
Research in how (KM) is employed
in organizations informs us that
(KM) methods can not be
implemented haphazardly as they
can interact to enhance or detract
from desired outcomes
KM could be viewed as a partial solution to
inadequate knowledge sharing between lead
users and external actors, (KM) provides essential
insights into understanding successful primary
care practice improvement, and as a result, has
the potential to influence favorably the overall
improvement in the health of residents in the
United States and around the world
Orzano, John, Claire R. McInerney, Davida Scharf, Alfred F. Talia, and Benjamin F. Crabtree (2008), “A Knowledge
Management Model: Implications for Enhancing Quality in Healthcare.” Journal of the American Society for Information
Science and Technology, , 59(3) 489-505.
27

28. (KM) Model
Orzano, John, Claire R. McInerney, Davida Scharf, Alfred F. Talia, and Benjamin F. Crabtree (2008), “A
Knowledge Management Model: Implications for Enhancing Quality in Healthcare.” Journal of the
American Society for Information Science and Technology, , 59(3) 489-505.
28

29. Hypothetical Case Study
Tech
H3
H2
H1
H.I.T. Co Exp
H.I.T.
H.I.T. Co Exp
CoExperience
CoDefinition
F1
Co Exp
CoElevation
CoDevelopment
F2
29

30. Conclusions
•
By forging external collaborations and facilitating the cross-fertilization of ideas,
firms can actively manipulate their capabilities to better guide their market
pursuits, gain access to complementarities, and shorten development time,
while spreading the significant costs and risks associated with R&D .
•
Offers implications for how inventions, their attributes and their defined
ownership boundaries can be more aptly leveraged within R&D strategies to
evolve a firm’s capabilities.
•
The co-creative model infrastructure is an In-depth exploration of innovation
process for new ideas into the ongoing debate over a cost-containment
environment and medical technological innovation.
•
The intensity and variety of interactions between all participating actors
indicates the value network/value constellation.
30

31. Future Research
• What are the incentives for entities involved in program other than
progress for greater good?
• How to measure success and failures of model application, to
indicate usefulness of entities participating.
• Future research on the variables necessary in the co-experience
function of the systemic service model.
• Future research on the models affect on free-market medical
systems and universal healthcare systems in an effort to understand
bureaucratic pressures.
• Future research on refining the conceptual framework of the cocreative service innovation model towards a functional framework.
• Future research on steps/guidelines to manage co-creative service
model in context of value constellations.
31

32. References
Bessant, John and Lynne Maher (2009), “Developing Radical Service Innovations in Healthcare – The Role of Design Methods,”
International Journal of Innovation Management, 13(4) (December), 555-568.
Caballero-Daniel, Sara, Chipo Mugomba (2007), “Medical Tourism and its Entrepreneurial Opportunities – A Conceptual Framework
for Entry into the Industry.” Master Thesis, School of Business, Department of Economics and Law, Goteburg University.
Daim, T.U., Tarman Tarcan, and N Basoglu (2008), “Exploring Barriers to Innovation Diffusion in Health Care Service Organizations:
An Issue for Effective Integration of Service Architecture and Information Technologies,” Proceedings of the 41st Annual Hawaii
International Conference on System Sciences, Conference Publications, 7-10 Jan. 2008 IEEE, 1-10.
Dearden, A., P. Wright, S. Bowen, F. Rahman, M. Cobb, and D. Wolstenholme (2010), "User-Centered Design and Pervasive Health: A
Position Statement From The User-Centered Healthcare Design Project," 2010 4th International Conference on Pervasive
Computing Technologies for Healthcare, Conference Publications, 22-25 March 2010 IEEE, 1-4
Errol Ozdalga. Ark Ozdalga. Neera Ahuja (2012), “The smartphone in medicine: A review of current and potential use among
physicians and students,” Journal of Medical Internet Research (JMIR), J Med Internet Res; 14(5): e128.
Finch, Tracy L., F.S. Mair, and C.R. May. (2006) “Teledermatology in the U.K.: Lessons in Service Innovation.” British Journal of
Dermatology. 156 (June) 521-527.
Galbrun, J.; Kijima, Kyoichi (2010), “Innovation in Medical Imaging Technology: Toward a Systemic Service Perspective,” Service
Systems and Service Management (ICSSSM), 2010 7th International Conference on, 1(7) 28-30.
Giegerich, Andy (2012), “Quick-care Medical Clinic Models Grow,” Portland Business Journal, 7 (September) 24-25.
Khoury, T. A., Pleggenkuhle-Miles. E. (2011) “Shared Inventions and the Evolution of Capabilities: Examining the Biotechnology
Industry.” Research Policy, 40(7): 943-956.
Lamprinakos, George E., Kosmatos, D. Kaklamani, I.S. Venieris (2010), “An Integrated Architecture for Remote Healthcare
Monitoring,” Informatics (PCI), 14th Panhellenic Conference n, 12(15) 10-12.
32

33. References (Continued)
Luo, Chih-Ming A., Hung-Fan Chang and Chi-Hung Su (2012), “’Balanced Scorecard’ as an Operation-Level Strategic Planning Tool for
Service Innovation.” The Service Industries Journal. 32(12) 1937-1956.
Nair, M. (2011), “Understanding and Measuring the Value of Social Media.,” J. Corp. Acct. Fin., 22: 45–51. doi: 10.1002/jcaf.20674
Oliveri, Denise (2007), ” Pros and Cons of Urgent Care Centers,” (accessed on 4/29/13) *Available at http://suite101.com]
Omachonu, Vincent K., Einspruch, Norman G. (2010), “Innovation in Healthcare Delivery Systems: A Conceptual Framework,” The
Innovation Journal: The Public Sector Innovation Journal, Volume 15(1), Article 2.
O’Malley, Ann S., Joy M. Grossman, Genna R. Cohen, Nicole M. Kemper, and Hoangmai H. Pham (2010) “Are Electronic Medical
Records Helpful for Care Coordination? Experiences of Physician Practices.” J Gen Intern Med. 25(3) (March) 177–18
Orzano, John, Claire R. McInerney, Davida Scharf, Alfred F. Talia, and Benjamin F. Crabtree (2008), “A Knowledge Management Model:
Implications for Enhancing Quality in Healthcare.” Journal of the American Society for Information Science and Technology, , 59(3) 489505, 2008
Ruby P. Lee, Ginn, Gegory O., & Naylor, Gillian (2009), “The Impact of Network and Environmental Factors on Service Innovativeness,”
Journal of Services Marketing, 23(6), 397-406
B. Saenz de Ugarte, A. Artiba, R. Pellerin, (2009) “Manufacturing Execution System – A Literature Review.” Production Planning &
Control, 20(6)
Saviano, Marialuisa, Clara Bassano, and Mario Calabrese (2010) “A VSA-SS Approach to Healthcare Service Systems: The Triple Target
of Efficiency, Effectiveness and Sustainability.” Service Science, 2(April) 41-61.
Stephan, C., Kohl, M., Turewicz, M., Podwojski, K., Meyer, H. E. and Eisenacher, M. (2010), Using Laboratory Information Management
Systems as central part of a proteomics data workflow. Proteomics, 10: 1230–1249. doi: 10.1002/pmic.200900420
Whitten, Pamela, Inez Adams (2012), "Success and Failure: a Case Study of Two Rural Telemedicine Projects." Journal of Telemedicine
and Telecare, 9(3), 125-129
http://www.hhs.gov/regulations/index.html
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