initiating position paper

Towards a knowledge network of quality to support and stimulate
innovation and improved decision making in the South African health system

by JA Louw Ph.D
Published by
Medical Research Council, PO Box 19070, Tygerberg 7505, South Africa
March 1998 / ISBN 1-874826-83-8

Planning 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.

Background
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.

Health status 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 of findings.

Current 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.

The need 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).

Issues impacting 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 sub-systems.

The South 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.

Häusler, 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

Such interaction 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 trial-and-error learning.

Linking 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".

The important 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 knowledge bases.

Joly 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

Tacit knowledge 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.

Developments 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
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

The use 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 making.

A 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.

The knowledge 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.

Although 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 via hyperlinks.

Summary
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.

The content 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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