INTRODUCTION
Public health issues are priority issues for any government. According to WHO, health is a complete state of mental, physical and social well-being and not just the absence of disease or infirmity. In other words, a person with a balanced combination of mental, physical and social conditions is considered healthy. One of the core challenges of the current modern-day environment is the quality or the shortage of human resources. More than ever, it has stood at the centre of concerns in all countries, albeit with some acuteness in developing countries. However, while healthcare centres and hospitals around the world have striving to have performant human resources, they are expected to do the same in terms of knowledge management and sharing. The sharing of experiences plays a key role in optimizing the performance of health practitioners. And this inevitably entails a structured management of knowledge generated by the daily practice of the various health structures.
Performance remains one of the overarching goals of income-generating enterprises, including healthcare institutions. Given the challenges faced by health information systems, maximizing organizational performance is still an ideal. In the health sector like in other industries, identifying, accumulating and encoding knowledge are efforts that should be followed by a sound knowledge management for informed and improved clinical decision-making.
The aim of this article is to investigate the role of effective
knowledge management in selected hospital structures of
Yaoundé and even in other areas of Cameroon. To accomplish
this goal, we will try to answer the following big question: Can
we achieve an optimal level of performance in a hospital
structure following a successful practice of knowledge
management? To answer this question, our research model,
which is based on the models by Darroch[
Druker [4] argued that knowledge is "the only significant
resource" in business today. The resource-based enterprise
vision has acquired a new dimension in the theory of
knowledge. It can be viewed as a strategic asset of an
organization that must to be managed [
Researchers such as Davenport and Prusak [
H1: Technological capacity positively influences the transfer of knowledge within an healthcare setting.
Culture is defined as the system of beliefs, values, customs,
behaviours and artefacts that are used by stakeholders of a
humanity to face their world and interact, and which are
transmitted from generation to generation through learning.
[
Generally, culture enhances knowledge, helps its creation,
sharing and application while promoting an open climate for
the free flow of ideas [
H2: The better the organizational culture within a healthcare setting, the more its staff will be able to transfer knowledge.
Researchers and academics have not yet reached a
consensus on the definition of knowledge transfer, as this
concept is being interpreted from different perspectives,
especially from the perspective of the interaction of knowledge
[
H3: Knowledge transfer within a healthcare organization reinforces the process innovation of knowledge.
H4: Knowledge transfer has a positive influence on organizational performance in health care.
Process innovations are those that occur in the technical
parts of an organization and are directly linked to the main
work activity of that organization. They may be a work in
progress, or the introduction of new elements into the
production or service operations of an organization [
Fig. 1. Research model
Organizational performance is about how every groups is
organized to reach its targets and how it manages to achieve
them [
H5: The higher the process innovation capacity of a healthcare structure, the better its performance.
To analyse the aforementioned hypotheses, we have opted
for a research methodology based on a hypothetico-deductive
approach whose process follows a number of steps, including
the elaboration of the questionnaire using a seven-level Likert
scale, and data collection and analysis (with a choice of the
sample size, the administration of the questionnaire, and the
collection and processing of data). Regarding the questionnaire
development phase and the choice of the sample size, it should
be noted that our questionnaire had exactly 78 questions on all
the different items of research models. The questionnaire was
then adapted to our research environment, and pre-test was
carried out by 11 people (10 students from the Management
and Information System (MSI) at the Catholic University of
Central Africa, and 1 medical staff.) In addition, the software
GPower3 and the method of calculation of Hair and Al[
The administration of the questionnaire was done using a
door-to-door approach and paper forms. A pilot phase
consisting in analyzing remarks from 30 medical respondents
had been conducted beforehand in order to ensure the
reliability of our constructs and the stability of our research
model. The 400 administered questionnaires yielded only 131
usable observations, which were collected and recorded on an
Excel file to initiate the data processing process. The data
processing was conducted by means of ADANCO, version
2.0.1, which is a software application for analysing structural
equation models based on the PLS partial least squares method
[
IV.
We note from Table 1 above that our 131 respondents were made up of 64 men and 67 women and that most of them were aged between 31 and 40. In addition, about 65.08% of this population had at least 5 years of work experience.
With regard to the validity of our research hypotheses, the
stability of our research model and the quality of our
constructs, we would like to recall some theoretical standards.
The elimination of overt variables is not a game of chance.
Hair and al. [
As indicated in Table 2, the Cronbach’s alpha values and the Composite Reliability values are above the 0.7 threshold, thereby suggesting that our constructs are reliable and have good internal consistency. In addition, the Average Variance Extracted (AVE) values are greater than the threshold of 0.5, which is evidence of a convergent validity for the measurement indicators of each construct.
Based on Table 3, we can conclude that there is good
discriminant validity of our constructs since all HTMT values
are well below the threshold of 0.85 or 0.9. So our assumptions
consist of constructs that are distinct from each other. Indeed,
the HTMT ratio is an estimate of the correlation between the
constructs, its measurement allows us to see whether there is a
lack of discriminant validity or not; or more specifically, to
know if the constructs are distinct from each other.[
Structural Model. The use of the bootstrapping method
enabled us to test the significance of both the relationship
between model constructions (through the interpretation of
tstatistics) and the correlation between these constructs (by
looking deeply at the values of the correlation coefficient). The
t-statistic must be greater than 1.96 to express a
significance[
Table 4 above shows results obtained by means the version 2.01 of ADANCO boostrapping. It clearly appears that all our research hypotheses (H1, H2, H3, H4, and H5) are verified and supported. Table 5 below shows the various results from the testing of hypotheses. H5 : Process Innovation >Organisational Performance ***P < 0.001; **P < 0.01; *P < 0.05;
As indicated in this table, the different influences between our constructs are analyzed as follows:
THE INFLUENCE OF TECHNOLOGICAL CAPACITY
From the results obtained, following the analysis of the data
and those contained in the table above, we observe that for a
level of significance equal to 99.9%, the technological capacity
does not have a significant influence on the transfer of
knowledge. This could mean that managers or leaders of urban
Cameroonian health centers or hospitals do not necessarily
have to invest heavily in technological capacity for efficient
knowledge transfer. This result is also consistent with that
highlighted by researchers such as N. Theriou, D. Maditinos,
and G. Theriou [
THE INFLUENCE OF ORGANIZATIONAL CULTURE
Our study shows that organizational culture significantly
influences the transfer of knowledge. This may mean that
governments or hospital officials need to increase investment
in education and cultural change in this sector. This influence
holds true for researchers such as N. Theriou, D. Maditinos,
and G. Theriou [
Our study shows that knowledge transfer significantly
influences organizational performance and has a direct and
positive effect on innovation. As a result, it could mean that
any improvement on knowledge management processes (such
as knowledge transfer) also encourages innovation and implies
that investing in this process in health care could lead to a
significantly improved organizational performance in the
health sector. This result has been proved by several other
researchers, including M. Slavković and V. Babić [
Based on the results obtained, it is clear that although innovation may be a partial mediating effect in the relationship between knowledge transfer and organizational performance, it has a significant influence on organizational performance in the public health domain.
Fig. 2. Research model obtained by ADANCO 2.0.1
It would therefore be wiser for decision-makers to invest
heavily in their ability to develop industry processes as well as
for the quality of care provided in their field of competence, for
highly improved health care performance. This result is in
contradiction with the one obtained by Darroch [
V.
This work aimed at demonstrating the major impact of
knowledge management through knowledge sharing on the
organizational performance of health structures; it appears that
all the assumptions made have been verified. This indicates
how interesting our research model may be in terms of
contribution to an effective and formal practice of knowledge
management in the health structures of Cameroon. Indeed, our
study shows that organizational culture significantly influences
knowledge sharing. This may mean that governments or
hospital officials need to increase investment in education and
cultural change in this sector. Because this influence remains
true for researchers like N. Theriou, D. Maditinos, and G.
Theriou [
This study shows that knowledge sharing significantly influences organizational performance and has a direct and positive effect on process innovation. This could mean that any improvement in knowledge-sharing processes also encourages innovation and implies that investing in the development of knowledge management in health care can lead to improved organizational performance in the health sector. It is clear that process innovation is a partial mediator of the relationship between knowledge sharing and organizational performance, but it significantly influences organizational performance in the public health domain. It would therefore be wise for decisionmakers in hospital structures to invest heavily in capacity building, non-retention and proper dissemination of knowledge, so as to improve the quality of care provided while maximizing their chances for sustained organizational performance. In addition, although technological capacity positively influences knowledge sharing, it remains a success factor for knowledge management and knowledge sharing. Yet our results showed that it is less important than organizational culture in the Cameroonian context.
Our work has had two main limitations: on the one hand, the absence of a qualitative study of the phenomenon, which could not enrich our study through obtaining richer and more elaborate results. On the other hand, the survey that was conducted targeted only the city of Yaoundé and better still, could not even cover of all the hospitals of the area.