a knowledge network of quality to support and stimulate
innovation and improved decision making in the South African
JA Louw Ph.D
Medical Research Council, PO Box 19070, Tygerberg 7505, South
March 1998 / ISBN 1-874826-83-8
This paper highlights the need to capitalise on the macro-level
initiatives to further an information society in South Africa
with the specific aim of creating a knowledge network in the content
area of health. The aim of such a knowledge network is to support
and stimulate innovation within the health system, as well as
serving as an instrument for improved decision making, based on
quality-controlled and evidence-based information.
of the knowledge network must take into account the dynamics
of the innovation process, in particular the interaction and
knowledge flow among players in the health system.
Furthering the information society is viewed as an essential
challenge to meet the socio-economic demands of modern society,
which is recognised to be in a fast transition from the Information
Age to the Knowledge Age.1 This drive was highlighted at the
G7 summit of 1995. As an invited speaker at the summit, South
African Deputy President, Thabo Mbeki, pointed out that this
challenge has to take equity issues into account as well, with
a large population of people still without even basic telephone
services. This debate was further continued at the Information
Society and Development Conference (ISAD) held in South Africa
in May 1996, where the United Nations Economic Commission for
Africa (UNECA) launched the African Information Society Initiative
(AISI). At this conference Thabo Mbeki stressed that "the
ability to use information effectively is now the single most
important factor in deciding the competitiveness of countries".2
AISI has since been adopted by the G7 countries, Russia and
various influential global organisations, such as the World
Bank and UNESCO. Agreement exists that African countries should
use information and communication technologies to inter alia
address development issues, to avoid marginalisation in the
world economy and to build human capacity. Several African countries,
including South Africa, have since started to address information
society development issues.
One of the
most crucial issues impacting on the development of a nation
is its health status. The AISI action framework (United Nations
Economic Commission for Africa, 1996)3 therefore also identified
specific goals in terms of the way in which information and
communication technologies can be used to achieve more efficient
and affordable health care.
is the result of a complex system, involving various players.
Interaction among these players, involving researchers, health
services, industry, health policy makers and communities in
an iterative process, is the basis for the Essential National
Health Research (ENHR) approach. ENHR has formally been adopted
by the MRC and the national Department of Health as a philosophical
framework. For ENHR to succeed it must be supported by efficient
knowledge management promoting the logical transformation
of data first to information then to knowledge in a systemic
way, thereby enabling the innovation process for the creation
of new knowledge and knowledge dissemination aimed at implementation
information systems in the South African health context are
disparate and not integrated. Although there is an abundance
of websites, no single entry point exists to provide access
to quality-controlled health information resources, or to allow
for reciprocal sharing of information.
clearly exists to establish a virtual knowledge network, which
will provide for specific applications that will support and
stimulate innovation through efficient knowledge management
and as a decision-support instrument for government and
the health services sector. Such a network will complement the
initiatives undertaken under the umbrella of the National Health
Information System of South Africa (NHIS/SA).
on the dynamics of innovation
As a point of departure it is necessary to understand the dynamics
of various factors impacting on the innovation process. Fortunately
much work has been done in this regard and one can draw extensively
on the existing literature on various topics related to this
field. Such work emphasised the systemic nature of innovation
with the interdependencies of technical, economic and social
African White Paper on Science and Technology4 issued by the
Department of Arts, Culture, Science and Technology (DACST)
in 1996 sets the agenda for a National System of Innovation
(NSI). NSI is a well-established concept. Freeman (1987)5 refers
to NSI as a network of institutions in the public and private
sectors whose activities and interactions initiate, import,
modify and diffuse new technologies. It is clear that one can
only expect 'innovation' as an output of such a system if the
necessary interaction and information flow between the various
players happens at a sophisticated level. Many developing countries
have fallen prone to systemic incoherence, in particular in
the African context.6 The challenge is to understand the complexity
of the system and to improve its functioning.
et al.7 ,also with reference to the work of the Organisation
for Economic Co-operation and Development8, Kline and Rosenberg9
and Teece10 , emphasise that the traditional linear concept
of innovation has become obsolete. The linear model in essence
supported the notion that, through a sequential flow, basic
research supports applied research, which then produces results
which are used in development efforts. It conceives invention,
innovation and diffusion as separate stages in an essentially
linear process.11 Alternative (and more appropriate) models
for innovation must be able to incorporate notions such as (reciprocal)
feedback between scientific research, technical development
and production. They must also allow for simultaneous research
and development activities, the interactive nature of innovation
processes and the interdependence between the various players
in the R&D system. Häusler, et al.7 stress that the
modern organisational aspects of innovation should provide for
institutional structure that is "extremely variegated and
involves a complex network of backward, forward, horizontal
and lateral relationships and linkages within and among firms
and organizations such as universities". In such an interactive
model of innovation, implementation is an important aspect.
Innovation is therefore viewed as a spiralling rather than a
linear process, with crucial innovation taking place at both
the design and implementation stages continually feeding
back into future rounds of technological change.12
among players in an innovation network highlights the existence
(and formation) of innovation communities those organisations
directly involved in the innovation process.13 This is consistent
with the views of Gray14 that a domain approach is necessary
for collective problem-solving processes the domain consisting
of actors (individuals, groups, or organisations) involved in
solving a set of interrelated scientific and technological problems.
In a particular innovation community such as the South
African health system one should note the existence of
a substructure and a superstructure. According to Lynn, et al.13
organisations in the substructure produce either the 'innovation'
or its technological complementaries, while superstructure organisations
provide for collective goods, such as specialising in co-ordinating
the flows of information. Superstructure organisations therefore
are 'linking organisations' providing for the necessary links
between diverse bodies of knowledge, competencies and techniques,
thereby creating a convergence of interdependent and complementary
action within the innovation community. In the establishment
of a knowledge network for the 'innovation community of health'
the MRC should assume the role of a superstructure player, although
the activities of its various programmes can be regarded as
constituting important substructure components.
It is also
worth noting the types of networking that can be present in
the system of innovation, as described by Langlois and Robertson.15
Centralised networks exist where players are tied to a 'lead'
firm, typical of the Japanese automobile industry, in a star-type
configuration. Decentralised networks with multiple interaction
between the players in essence a network of competitors
employing a common standard of compatibility are more
common. A decentralised network based on modularity will benefit
the innovation process to the extent that it involves experimenting
with many alternate approaches simultaneously, leading to rapid
with such networking is the concept of strategic partnering
between players. Hagedoorn16 states that the research and development
intensity or the level of technological sophistication of sectors
(technological communities) is positively correlated with the
technology partnering that takes place. Such inter-firm co-operation
is particularly viable, and often necessary, in the era of increased
international competition and rapid technological change. Strategic
partnering has led to tighter networks of co-operation. In such
networks the nodal partners (generally) increasingly create
webs of co-operation with a large number of partners, for interaction
in terms of joint ventures, joint research and development,
and technology sharing arrangements. Hagedoorn16p.226 concluded
that "the 'open' character of these networks, with some
degree of stability, indicates the dynamic character of the
partnering behaviour of many leading companies that use their
alliances as part of a wider competitive strategy".
role of information and knowledge in the innovation system is
clear. Häusler, et al.7 indicate that the players in the
innovation system must establish a norm of "informational
reciprocity". Clarysse, et al. 17 indicate that during
research collaboration, the players in the system benefit from
mutual learning and knowledge exchange, enabling them to overcome
complex, and often indivisible, technical problems. However,
Fincham, et al.18 indicate that there may be difficulties in
ensuring information flows between the various expert and specialist
groups, taking into account their differing perspectives and
Mangematin19 conclude that the output of research is not information,
but rather knowledge (which is an essential driver of the iterative
innovation process). Knowledge can be coded or tacit. Coded
knowledge, also referred to as explicit knowledge, is knowledge
that is transmittable in formal, systematic language.20 The
more knowledge is coded, the easier its absorption into the
innovation system. However, the user (receiver) of coded knowledge
needs certain know-how and assistive technology (such as information
and communication technologies) to benefit from the knowledge.
The absorption process is an integral part of research, in that
research by virtue of the creation of information and knowledge
is a learning process, which increases absorptive capacity.
To benefit from the results of academic research (although in
coded format) the receiver needs to 'know the code'.19 Translation
of coded knowledge is also aided by fundamental research by
the receiver used as an interface to enhance the absorption
rather than producing original knowledge. Through publication
and patent activities, research organisations therefore posit
their knowledge in a certified way making it available
to other players in the technological community. Indeed it is
argued that the access of organisations to multiple external
sources, of which knowledge is the most powerful, positively
correlates with their chances of surviving or persisting.17
is another important driver in the innovation process. Joly
and Mangematin19 indicate that when knowledge is tacit the learning
processes are localised and cumulative. Access to tacit knowledge
may offer a competitive advantage to players in the technological
community. Tacit knowledge is also embodied in the absorptive
capacity of a particular organisation. According to Clarysse,
et al.17 , collaboration between a focal research organisation
and other players in the community will increase the research
organisation's access to external sources of tacit knowledge,
thereby increasing the likelihood of continued persistence.
Access to multiple knowledge sources may thus have a positive
effect on the persistence of an organisation to continue its
efforts in a particular field. The more information flows in
the system, the more likely players are to arrive at useful
solutions. This process is further influenced by the level of
communication between organisations.
in information and communication technologies (ICT) offer a
major opportunity for improving the way in which research and
development is operated, structured and co-ordinated. Howells21
highlighted the following benefits of ICT in this regard: economic
and resource-based benefits in terms of economies of scale;
access benefits relating to better interaction with specialist
equipment or staff and reduction of isolation; time-based benefits
linked with the similtude and interactive nature of new ICT
facilities; and spatial flexibility. Clearly ICT needs to adapt
to a knowledge-centred approach which emphasises knowledge transfer.22
Knowledge management, which is a new field emerging from the
confluence of organisation theory, management strategy and management
information systems, is viewed as an essential driver for innovation.
According to Malhotra "Knowledge Management caters to the
critical issues of organisational adaption, survival and competence
in face of increasingly discontinuous change. Essentially it
embodies organisational processes that seek a synergistic combination
of data and information processing capacity of information technologies,
and the creative and innovative capacity of human beings".23
of a knowledge-management approach can also be extrapolated
to the greater health system in South Africa. In such a system
appropriate reciprocal flow of knowledge between the players
in the system is necessary to stimulate innovation (as a source
for further research and development) and for improved decision
knowledge network for health
The amount of biological and medical information is growing
at an exponential rate. For the effective utilisation of available
information, in particular in the case of the South African
health system, it is necessary to implement a knowledge network.
Such a knowledge network should also deliver 'trusted' information
and, in the context of health innovation, should stimulate the
flow of evidence-based information.
network proposed would be a virtual network with various players
participating as end-users, but also contributing to knowledge
sources (refer to the notion of the role of superstructure and
substructure players outlined in section 2 above). The knowledge
network will make use of modern IT drivers, and by using standard
web browsers, users will be able to access knowledge sources
on the network. Fouché24 pointed out that the aim of
a knowledge network is to build and organise a network of local
and global knowledge resources of relevance to the particular
community of members and users. Furthermore it enables the players
in the system to interact with each other and with remote suppliers
of knowledge sources for the purpose of collaborative action
and goal achievement. In the context of the South African health
system, it is necessary to superimpose the ENHR priority areas
(or thrusts) on the planning and functioning of the knowledge
network. The knowledge network therefore evaluates, indexes
and links relevant 'knowledge nodes' and provides the facilities
and functionalities to communicate, interact, transact and work
collaboratively. The emphasis should remain on the 'human side'
of knowledge management, as also stressed by Malhotra.23 Typically
a knowledge network should provide a range of functionalities
and applications including e-mail, file transfer, information
retrieval, electronic publishing, document managing, mediated
discussion forums ('chat facilities'), video conferencing (on
demand) news services, access to experts, user training and
support. It should also provide a knowledge map or inventory
to assist users in accessing relevant knowledge sources and
should allow for selective access and selective (closed) interaction
by implementing virtual private networks (on demand). Where
appropriate, push-technology should also be used to provide
coded knowledge to appropriate users in the health system. Figure
1, on the next page at a high level, depicts proposed components
of such a national health knowledge network.
the knowledge network should use the latest appropriate IT,
it should also cater for communities that are poor in terms
of telecommunication infrastructure. In this regard it should
link with the initiatives of the Universal Service Agency (USA)
established by the South African Telecommunications Regulatory
Authority (SATRA) to provide appropriate knowledge flow to communities
via multi-purpose community information centres or telecentres
in areas accessible by the community. USA collaborates with
Intekom, a subsidiary of Telkom South Africa, in this regard.
For a health
knowledge network to be of value to the players in the health
system involved in the innovation process, and for improved
decision-making, particular care must be taken to populate the
network with quality information. In this regard it would be
necessary to establish a mechanism (such as peer-review panels)
to vet information sources which will become modules of the
knowledge network, as well as those which might be pointed to
The South African health system needs two very specific national
information system initiatives. One is the NHIS/SA initiative
which, from a macro perspective, provides for a vertical operational
system aimed at the efficient management of the public health
services sector. A parallel development is needed to provide
a systemic knowledge flow in terms of the various information
and knowledge sources which could have direct impact on improved
decision making in the health care sector, as a decision-support
basis for the policy-making environment, and as a platform for
interaction among players involved in the innovation process.
This can be done by creating a knowledge network with
the underlying principle of being a trusted single entry-point
resource providing quality-controlled and evidence-based information.
No intervention should be undertaken or supported without a
clear understanding of the existing knowledge base in a particular
field or on a particular problem situation.
modules of the knowledge network and its value-adding services
layer must be of such a nature as to ensure sustainability,
after an initial financial injection from government over the
first 3 years.
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