2. Knowledge management process model 19
degree in Business Administration (MBA) from University of Malaya and his
PhD from Brunel University, United Kingdom. His area of research includes
information systems implementation, radio frequency identification (RFID),
open source software (OSS), healthcare information systems and social media.
This paper is a revised and expanded version of a paper entitled ‘Developing
process model for management of knowledge-intensive organization - a case
study of a hospital presented at The 19th Pacific Asia Conference on
Information Systems, 5–9 July, 2015, Singapore.
1 Introduction
Knowledge management (KM) has received much attention from both practitioners and
researchers. Practitioners are interested because they want to create new business
knowledge while researchers investigated strategies, enablers, models, tools and
techniques of KM and organisational outcomes (Adams and Lamont, 2003; Carneiro,
2000; Chapman and Magnusson, 2006). Studies on KM suggest that effective
implementation of KM has become a vital part in achieving a company’s long-term goals
and has some impact on performance (Andreeva and Kianto, 2012; Soon and Zainol,
2011). Besides private business enterprises, KM approach has also spread into other
fields such as education, urban planning and development, governance and healthcare. As
interest in KM continues to grow, organisations from various fields embrace the concepts
associated with KM and leverage on its opportunities to ensure efficiency in carrying out
operations and achieve competitiveness (Ergazakis, Metaxiotis and Psarras, 2004).
Scholars argue that developing a KM culture within the public sector is more
challenging than in the private sector. The organisational goals in public organisations are
typically more difficult to measure and conflicting, they are affected differently by
political influences and have specific labour divisions that are a disincentive for
knowledge sharing (Amayah, 2013; Edge, 2005; Gau, 2011). Healthcare organisations,
particularly those in public sectors are facing these challenges including medical errors,
shortage of specialised personnel and the increasing demand for more effective cures in
disease management (Camilleri and O’Callaghan, 1998; Porter and Teisberg, 2004;
Wills et al., 2010). In healthcare settings, knowledge is needed in more mission-critical
situations where real-time decisions can have life or death consequences. It is evident that
healthcare organisations are knowledge-oriented and their services involve knowledge-
intensive process (Hojabri, Borousan and Manafi, 2012). For example, clinicians must
have access to numerous information, i.e., more than 10,000 known diseases, thousands
of medications in use, some 1,100 laboratory tests, more than 300 radiology procedures
(Jih, Chen and Chen, 2006). In today’s increasingly complex clinical environment, a
well-organised and effective strategy for KM in healthcare is important. Therefore, there
is a need to understand how KM is evolving within the context of public healthcare
organisations. In general, much of the literature in the area of KM has focused on the
private sectors. Public sectors work in a unique context in which their stakeholders and
accountability differ significantly from those of the private sector, hence blindly applying
private sectors KM tools and models may be counterproductive (Massaro, Dumay and
Garlatti, 2015).
3. 20 N. Bahar and S. Bahri
Studies on KM particularly in healthcare lack two crucial elements. First, many
studies fall short of incorporating the whole process of KM by exploring KM
relationships in separation. Study found 372 relevant articles from 31 journals, which
were categorised as specific KM process (Wills et al., 2010). Thus, there is a lack of
study that captures the entire process of KM. Second, few studies have investigated how
KM can operate in public organisations that provide healthcare (Beveren, 2003).
Therefore, little is known on how to apply reliable knowledge and embedding KM into
the clinical process and work environment (Buranarach, Supnithi and Chalortham, 2009).
The clinical process can be classified as diagnosis, treatment, monitoring and prognosis.
There are two distinct roles involved in these process: clinicians and patients. This paper
focuses on clinicians (doctors and nurses) as they are often faced with multiple, vague
symptoms requiring access to a broad knowledge base for effective decision-making
(Essex and Healy, 1994). Given the multiple dimensions and complexity of clinical
knowledge and the high accuracy requirements in clinical decision-making, there is a
need to organise and consolidate KM process model for clinical work environment
(Wills et al., 2010). To fill this gap, this study focuses on the following research
objectives:
i to investigate how doctors and nurses practice KM process alongside with the
clinical process
ii to identify the KM activities practised by the doctors and nurses
iii to develop a KM process model for clinical work environment.
The paper proceeds as follows. First, a brief literature overview is provided. Second, the
research method is described. Third, the findings are presented and discussed. The final
section presents a conclusion offering a future research agenda and the research
implications.
2 Literature review
This section presents a brief review of the literature that is relevant to this study. Section
2.1 describes KM in general. Section 2.2 covers the previous research on KM process
model and Section 2.3 discusses KM in healthcare settings.
2.1 Knowledge management
The recent interest in managing organisational knowledge gave rise to the field of KM.
The literature is rich with various definitions of KM, but most authors have defined KM
as “a practice that finds valuable information and transforms it into necessary knowledge
critical to decision making and action” (Beveren, 2002). KM is vital to increase
innovativeness and responsiveness, to support enterprises in the new business
environment, and the idea seems to be an important prerequisite for success and viability
(Ragab and Arisha, 2013; Hackbarth, 1998; Wiig, 1997). The growing interest in KM
studies cover many different disciplines and areas of interest such as perspectives and
issues: economics, intellectual capital, engineering approaches, aspects of computing and
knowledge media, organisational studies, epistemology and other aspects of classification
4. Knowledge management process model 21
and definition informed by artificial intelligence and human resource issues (Quintas,
Lefrere and Jones, 1997).
Despite numerous studies that have been conducted in this area, fewer have
investigated how KM can operate in public sector that are not profit-based by nature
(Beveren, 2003; Massaro, Dumay and Garlatti, 2015). KM has the potential to influence
greatly and improve the public sector renewal process and it is a powerful enabler in the
current drive for increased efficiency in all areas (Edge, 2005; McAdam and McCreedy,
2000). Hence, there is a need to examine how KM operates in public organisations that
provide healthcare services.
2.2 KM process model
KM still has many issues related to the basic process, the pursued objectives and the
appropriate measures to ground the KM activities are still a matter of debate for both the
scientific and business community (Diakoulakis et al., 2004). Furthermore, there is a lack
of classification of suitable KM models to be used in conducting further research,
literature evaluation and organisational applications (McAdam and McCreedy, 1999).
Public sector organisations, for example, should not import KM tools and models from
private companies that have been developed without the consideration of the public
sector context (UNPAN, 2003).
Many studies have investigated KM process in various fields mainly in private sector
business enterprises. Table 1 summarises the major KM process proposed by different
scholars. Likewise, in this paper, the authors have attempted to present a process model
for clinical work environment that incorporates clinicians practice and clinical process
through KM concepts.
Table 1 Summary of KM process
Author KM process
Anderson and APQC (1996) Applying, sharing, creating, identifying, collecting,
adapting, organising
Demarest (1997) Construction, embodiment, dissemination, use
Spek and Spijkervet (1997) Developing, distributing, combining, holding
Little (1998) Acquisition and creation, saving, dissemination, use
Lee and Kim (2001) Accumulation (acquisition and creation), integration,
reconfiguration
Bose (2003) Knowledge creation, knowledge structuring,
knowledge dissemination and knowledge application
Diakoulakis et al. (2004) Exploration of the external environment, internal
scanning, sharing/access of knowledge,
retention/systemisation of knowledge,
combination/creation of knowledge
Amirkhani et al. (2012) Specifying strategic knowledge goals, acquiring the
required knowledge, assessment and organisation of
knowledge, sharing knowledge, empowerment and
sustainable human resources development
5. 22 N. Bahar and S. Bahri
McAdam and McCreedy (1999) have discussed and evaluated three KM models. They
found that Demerest’s (1997) adaptation of Clark and Staunton’s (1989) model of KM
emphasise the construction of knowledge within the organisation, not limited to scientific
inputs but was seen as including the social construction of knowledge. They also found
that the model was similar to that of Jordan and Jones (1997) who speak of knowledge
acquisition, problem solving, dissemination, ownership and storage. There are also
similarities with Kruizinga, Heijst and Spek’s (1997) model that includes knowledge
policy, infrastructure and culture. There are also parallels with Scarbrough’s (1996)
approach that cover strategic knowledge, structural and cultural knowledge, systems
knowledge and communities of practice and routines (McAdam and McCreedy, 1999).
The model in Figure 1 is attractive because it does not assume any given definition of
knowledge but rather invites a more holistic approach to knowledge construction. The
limitations of this model imply that recursive flows are less important than the simplistic
approach (McAdam and McCreedy, 1999).
Figure 1 Demerest’s knowledge management model
2.3 KM in healthcare
KM in healthcare can be broken down into four discrete activities: knowledge
production, knowledge transfer, knowledge reception and knowledge use (Treasury,
2006). These activities are usually conducted during the clinical process of diagnosis,
treatment, monitoring and prognosis. For example, the first step in all of these process
includes the collection of data in the form of patient interviews, laboratory tests, imaging
studies, medical history and risk factors among others. This step is then followed by data
analysis (Wills et al., 2010). Clinicians are one of the important roles involved in the
process of clinical care. They are the physicians, mid-level providers (nurse practitioners,
physician assistants) and nurses. Each has specific knowledge requirements (Wills et al.,
2010).
6. Knowledge management process model 23
There is a well-established literature on implementing clinical evidence into practice.
For example in the 1990s, evidence-based medicine sought to maximise efficiency of
medical practice by adopting a more rationally ordered means of predicting health
outcomes and organising of service provision. This model of medical practice organises
‘knowledge’ into levels of rational validity with double blind randomised control trials as
the most trustworthy type of explicit medical knowledge based on statistical inference
(Sackett and Rosenberg, 1995). The overall intent is to increase the scientific rigor of
clinical investigations and treatments as well as increase the utilisation of scientific
research in the practices of medical professions (Nutley, Walter and Davies, 2003; Wood,
Ferlie and Fitzgerald, 1998). In principle, this is endorsed by clinicians, but remains
problematic in application (Dawson et al., 1999; Ferlie et al., 2005; Freeman and
Sweeney, 2001; Wood, Ferlie and Fitzgerald, 1998). In addition to the expanding
research literature being difficult to access in a timely fashion, gaps in the current
understanding of health and disease process, and the difficulty of interpreting the results
of research publications (Mykhalovskiy and Weir, 2004; Wood, Ferlie and Fitzgerald,
1998). Study also found there is still less consideration of how management
and organisational knowledge gets into practice in healthcare organisations
(Ferlie et al., 2012).
3 Research method
This section discusses the research method used in this study. Section 3.1 explains the
initial research model. Section 3.2 explains the research approach. In the later sections,
data collection and analysis are discussed.
3.1 Research model
The research model is adopted from Nag and Gioia (2012). Figure 2 depicts the study’s
initial research model. The model is chosen because it enables the study to encapsulate
the multifaceted and vigorous characteristics of KM. In this model, there are three
dimensions that constitute the core of the overall process model:
i knowledge scheme
ii knowledge scanning
iii knowledge use.
Figure 2 The initial model shows the linkages between knowledge scheme, scanning and use
Nag and Gioia (2012) emphasise the importance of understanding how one schema
relates to the interpretation, search for and utilisation of knowledge. Since there is a lack
of attention paid to the influences on scanning and actual information acquisition
7. 24 N. Bahar and S. Bahri
behaviours, there is a need to appreciate executive scanning as a key of knowledge
acquisition behaviour (Boyd and Fulk, 1996; Garg, Walters and Priem, 2003; Hambrick,
1982; Nag and Gioia, 2012). It is essential to investigate whether differences in the ways
that executives scan for information might lead to the acquisition of different kinds of
knowledge that might be useful in practice (Nag and Gioia, 2012). Based on observations
from the schema, scanning and practice literature suggest the need for a more
concentrated focus on the beliefs, knowledge-seeking orientations, interpretations and
actions of key agents in firms, and specifically, a more integrated consideration of
process by which they identify, search for and use knowledge (Nag and Gioia, 2012).
Table 2 shows the descriptions of the initial model.
Table 2 Descriptions of the initial model
Dimensions Descriptions References
Knowledge
schemes
Frameworks of tacit knowledge that allow people to
impose structure upon and impart meaning to
ambiguous situational information
Gioia (1986)
Knowledge
scanning
The amount of knowledge and information search
conducted in a given domain - events and relationships
in a company’s outside environment, the knowledge of
which would assist top management in its task of
charting the company’s future and commonly
operationalised as the amount of time and effort
managers invest in information search.
Hambrick (1982) and
Sutcliffe (1994)
Knowledge
use
The modes of using knowledge Nag and Gioia
(2012)
3.2 Research approach
The authors adopted a qualitative research approach by conducting an in-depth
interpretive case study. This research method relied primarily on how clinicians described
how they practice KM in their day-to-day work. This methodology is suitable
for exploratory study (Eisenhardt, 1989; Yin, 2013). Finally, the authors follow
Mathiassen et al.’s call for case studies of the relationship of practices, of how and why
particular practices are adopted (Mathiassen et al., 2007). Case study research allows
gaining rich, contextual insights into the dynamics of phenomena under the investigation,
KM practice in clinical care environment (Dyer and Wilkins, 1991). Given the research
objectives, the authors concentrated on understanding the content of clinicians’ schemas
(belief structures) about knowledge, their knowledge scanning tendencies and the use of
knowledge in clinical practices.
3.3 Data collection
The research was conducted in a public hospital in Malaysia. Approval was sought from
the Ministry of Health Malaysia (MOH) in order to conduct research in the hospital. The
ministry requires all research activities to be registered and representative from MOH to
be involved. It took a couple of months to get the field-study collaborator from the
hospital and nearly a year for the research to be reviewed before it was finally approved.
8. Knowledge management process model 25
The authors followed a purposeful sampling approach in selecting the informants in
the study. The authors interviewed a number of informants including 12 doctors,
13 nurses, 5 assistant medical officers from the Medical department and 5 are head of
department (HoD), senior staff and key members from the hospital’s research centre.
Over a three-month period, the authors performed 37 interviews involving all the
informants. The authors had more than one interview sessions with the HoD, key
members and senior staff because they used the interviews to develop an understanding
of the common issues facing the industry and to gain a historical perspective on the
evolution of the industry especially on clinical environment. The authors conducted
on-site interviews with the clinicians of different roles that played key parts in the
execution of KM process in the clinical care. Table 3 provides a breakdown of the
informants. The different types of roles in the organisation were treated as multiple
sources for assessing similarities and differences in KM practices, which enabled the
generation of emergent framework and their interrelationships. The authors also spent
time at the medical clinic observing the flow of work and engaging in impromptu talks
with clinicians. During data collection, to ensure the credibility of the data from the
informants, the authors encouraged them to provide concrete examples to support their
commentary for most of the questions. This approach is important to reach confidence in
ascribing the reliability of the informants’ claims.
Table 3 Informants
Role Number of Informants Number of interviews
Head of department 1 3
Key members 2 2
Senior staff 2 2
Doctors 12 12
Nurses 18 18
Total 35 37
3.4 Data analysis
The interview data were analysed while the interviews took place. Drawing on Miles and
Huberman’s (1984) suggestions, the data analysis focuses on coding data segments for
category, theme and pattern development. From the field study, the authors have
collected information in the form of handwritten and audio recordings. The recordings
were then, transcribed into text. On to the methods, the authors began with first cycle
coding, then second cycle or pattern codes, and the process of deriving even more general
categories or themes through jotting and analytic memoing (Saldana, 2013). Then, the
authors assigned labels on the data to summarise in a word or most often with a noun.
These eventually provided an inventory of topics for indexing and categorising. As the
authors discerned codes that were similar and collated them into first-order categories,
the authors continued to use subcoding1
, a second-order tag assigned after a primary code
to enrich the entry, the authors then assembled the second-order themes. An example
comes from interview transcripts about the importance of knowledge in a participant’s
profession (Table 4).
9. 26 N. Bahar and S. Bahri
Table 4 Coding data segments for category, theme, and pattern development
First cycle
coding
Second cycle
coding
Medicine is a caring profession and doctors provide a
service to the public by diagnosing and treating diseases.
There is a need for strong knowledge in my profession as
a doctor. The diagnosis made by doctors places a patient
between life and death. So, it is vital that we continue
learning new skills and training in order not to be left
behind. As such life-long learning is integral to medicine -
none of us want to be treated by a doctor who is not up-to-
date on new treatments and techniques.
Knowledge
significance
Knowledge is
important
Scanning
knowledge
The usefulness
of knowledge
Discovering1
Acquiring1
Applying1
4 Findings
This section discusses the model that represents KM process for clinical work
environment.
4.1 KM process model
Based on the analysis, the authors developed a process model for KM. According to this
model, KM in clinical process consists of five key concepts:
1 knowledge schemes
2 knowledge scanning
3 knowledge store
4 knowledge use
5 knowledge transfer.
The authors also uncovered process for each key concept. Figure 3 illustrates the
interplay among the key concepts, its process and their linkages.
Figure 3 Knowledge management process model
10. Knowledge management process model 27
4.1.1 Knowledge schemes
Knowledge schemes refer to one’s belief structures about the nature of valuable
knowledge (Nag and Gioia, 2012). The informants displayed a clear pattern in how they
understood and evaluated the role of knowledge in their day-to-day work. For example,
most of clinicians believe that one’s ability and competency in diagnosing are critical to
place the patient between life and death. Thus, doctors must keep their knowledge and
skills up-to-date by engaging in lifelong learning. This has long been recognised by
doctors as a responsibility integral to the medical professionalism which underpins the
relationship between themselves and the public, and which helps to maintain trust.
According to one of the doctors:
“As doctors, we must keep our knowledge and skills up-to-date throughout our
working life. We should be familiar with relevant guidelines and developments
that affect our work. We should regularly take part in seminars, medical
courses and training that maintain and further develop our competence and
performance in treating our patients. Furthermore, we must keep up-to-date
with and adhere to, the laws and codes of practice relevant to our work. Our
viewpoints about patients’ needs especially those with chronic disorders are
very important to ensure we can cure diseases and save lives.”
Having a strong belief about the importance of knowledge as well as acquiring the most
recent one for their profession, it helps to develop the awareness of the need to
continuously discover new knowledge or to update the existing ones. Discovering
knowledge is uncovering where the knowledge is hidden in the data sources of the
organisation (e.g., databases, data warehouses) or from the external sources of the
required knowledge (Abou-Zeid, 2002; O’Leary, 1998). The authors found common
techniques practiced by the informants in the discovery process, research and
development, shared problem solving and communities of practice. Discovering
knowledge by itself is not enough. Once the knowledge has been discovered, the
knowledge identification process begins to identify what knowledge an individual needs
to perform in his or her work.
The authors provide the data structures for this study as shown in Table 5. It includes
first-order categories (those meaningful to the informants) and second-order themes
(induced by the researchers) that led to the generation of the key concepts.
Table 5 Data structure for knowledge schemes
First-order categories Second-order themes Key concepts
• The changing nature of knowledge requires us to
bring our know-how to date. It is very important
to search for the latest information especially the
diagnosis made by doctors will place a patient
between life and death.
• We are expected to remain up-to-date with new
knowledge.
• We need to attend seminars, medical courses and
training for certain days in a year. Furthermore,
there is a frequent update on medications and
prescription drug information.
Discovering
knowledge
Knowledge
Schemes
11. 28 N. Bahar and S. Bahri
Table 5 Data structure for knowledge schemes (continued)
First-order categories Second-order themes Key concepts
• There are numerous sources where I can look for
medical information but it is very important to
know whether the information is valid.
• For uncommon diseases, we have to search
information worldwide. For example, some
foreign patients were infected by a disease origin
from their country. It usually takes a lot of work
to identify the information retrieved from
multiple external sources.
Identifying
knowledge
Knowledge
schemes to
knowledge
scanning
4.1.2 Knowledge scanning
Knowledge scanning is the amount of time and effort the clinicians invest in information
seeking and examining the identified knowledge that typically combines electronic and
human approaches. The organisation has no formal or centralised scanning process and
leave the scanning up to individuals. In this study, the authors found human analysts
bring the most value to the scanning process by using one’s own knowledge to interpret,
compare and organise. The relational analyses of the data suggested that beliefs about the
value of a knowledge related to how clinicians scanned for knowledge. The stronger they
believe in the importance of knowledge, the more intensively they will do the scanning.
Once the newly acquired knowledge is organised, the analysing process begins before
storing the information. Table 6 shows the data structure for knowledge scanning.
Table 6 Data structure for knowledge scanning
First-order categories
Second-order
themes Key concepts
• We consulted experts from another hospital if they are
not available in our hospital. At times, CPG alone is
insufficient.
• Most of practitioners in my department will be
referring to UpToDate website.
• The external sources are very important especially in
dealing with international diseases.
Acquiring Knowledge
Scanning
• Medicine is a caring profession and doctors provide a
service to the public by diagnosing and treating
diseases. We should not take any information before
deliberating it among peers and seniors.
• I will consult my seniors and consultant besides my
own search.
Analysing Knowledge
scanning to
knowledge
storing
4.1.3 Knowledge store
Knowledge store is the act of keeping or accumulating knowledge for future use. This
study found, knowledge in healthcare organisation exists in databases, documents such as
clinical practice guidelines (CPGs), standard operating procedures (SOPs), in individual
experts and network of practitioners. The analysis suggested that in clinical work
12. Knowledge management process model 29
environment, knowledge mainly possessed by individuals, who are the clinicians. They
are the main actors to capture knowledge that includes collecting and organising the
documents in a meaningful manner for easy access to and retrieval of knowledge content.
Table 7 shows the data structure for knowledge store.
Table 7 Data structure for knowledge store
First-order categories
Second-order
themes Key concepts
• Most of the common clinical procedures are available in
CPGs and internal SOPs.
• I use my personal storage device to keep all the information.
• I use my own computer to store my files.
• I have a compilation of notes from my day-to-day work.
Capturing Knowledge
storing
• I normally access information from journals and CPGs.
• I will ask doctors or any seniors when faced with problems.
• Doctors are one of the sources considered during searching.
• I always refer to specialists and consultants.
Accessing Knowledge
storing to
Knowledge
use
4.1.4 Knowledge use
Knowledge use refers to modes of applying knowledge in clinical care practice such as
assessment, diagnosis, treatment, monitoring and prognosis. The data and analyses
suggested that a consistent pattern emerged showing that most informants viewed
knowledge as embedded in practices especially in the process of clinical care. At the
clinical level, knowledge use is seen as a process through which practitioners formulate a
solution in order to solve their day-to-day problems in managing diseases. Throughout
the interviews, a similar pattern emerged showing doctors or nurses, when faced with a
problem, they perform intensive scanning and sharing knowledge to find a solution for a
specific problem. To them, knowledge has a high value if they can solve critical problems
in their practices as it helps to enrich decisions and actions. Table 8 shows the data
structure for knowledge use.
Table 8 Data structure for knowledge use
First-order categories Second-order themes Key concepts
• When diagnosing disease and providing
treatment to patients.
• Decision-making and long-term planning.
Applying Knowledge use
• New case of disease requires us to do
numerous laboratory tests.
• Every patient has a different reaction to
medicine or treatment. We need to find out the
most suitable treatment for them.
Experimenting
13. 30 N. Bahar and S. Bahri
4.1.5 Knowledge transfer
Knowledge transfer helps to increase the visibility of knowledge by sharing it or
transferring it from one bearer (the knowledge provider or owner) to another one (the
knowledge seeker). The knowledge bearer could be artefacts, such as technical
documents or best practice databases, or human, such as experts in a certain domain. It
occurs at various levels: transfer of knowledge between individuals; from individuals to
explicit sources; from individuals to groups; between groups; across groups; and from the
group to the organisation (Alavi and Leidner, 2001; Ferlie et al., 2012). The mode of
distribution depends on the form of the available knowledge and the nature of the
provider and seeker. For explicit knowledge, this process includes the activities that aim
at increasing the visibility of the existing explicit knowledge that is stored in physical
media. Examples of such activities are pushing/pulling, searching/retrieving and
professional training. In the case of tacit knowledge, the process may include activities
such as socialisation, mentorship and apprenticeship. For example, doctors and nurses do
effectively communicate with each other in their clinical practices. This is when they
exchange and share knowledge about their past experiences and professional clinical
knowledge to make a collective decision about particular treatment for patients. On the
other hand, CPGs, and in-house SOPs are the examples of explicit sources developed by
individuals and become as a resource for others. Table 9 shows the data structure for
knowledge transfer.
Table 9 Data structure for knowledge transfer
First-order categories Second-order themes Key concepts
We work in a team. Doctors and nurses work together
to provide care to patients.
Senior staff and doctors are always there to guide me
and share knowledge.
It is common for clinicians to conduct continuing
medical education (CME) on a weekly basis.
We always share new knowledge among our team
members.
Distributing Knowledge
transfer
5 Discussion
The KM process model developed in this study constitutes a framework for embedding it
into the clinical process and work environment. Such a practice becomes feasible because
the proposed KM process model consists of all major KM process and the concrete
context linking together the whole process. Many other process models formulated from
previous studies have outlined a number of KM process such as knowledge creation,
knowledge structuring, knowledge dissemination and knowledge application (Bose,
2003). The initial model the authors adopted for this study consists of only three
elements:
i knowledge scheme
ii knowledge scanning
iii knowledge use (Nag and Gioia, 2012).
14. Knowledge management process model 31
As the authors conducted this study in healthcare setting, the authors uncovered other
important elements, which are knowledge store and knowledge transfer.
Networks amongst healthcare professionals play an important part in healthcare
delivery (Conner, 2001). In general, doctors and nurses transfer technical skills, academic
knowledge, cultural knowledge, management know-how and administrative skills
between individuals, from individuals to explicit sources, from individuals to groups,
between groups, across groups and from the group to the organisation. Several
researchers have noted that the transfer of knowledge among healthcare practitioners
(physicians, nurses, technicians) is dependent on professional networks and communities
of practice. Hence, these should be leveraged by healthcare delivery organisations as an
important means of diffusing medical evidence and best practices across organisational
boundaries (Addicott, McGivern and Ferlie, 2006; Brice and Gray, 2003; Gabbay et al.,
2003; Lathlean and Le May, 2002; Tagliaventi and Mattarelli, 2006). As such, knowledge
transfer is one of the important elements in the KM process model for healthcare
organisations.
In clinical environment, knowledge may be explicit, which means the knowledge is in
a structured form that is suitable for easy storage and processing such as knowledge
stored in databases and knowledge bases; or it may be tacit, which means knowledge is in
a subjective form that needs to be structured before it is used for storage and processing
such as ideas, insights, values and judgments of individuals (Bose, 2003). Clinicians’
skill and their knowledge are mainly resided in the human brain, it requires the individual
who holds the knowledge to transform it into information so that it can be communicated
to other persons. It is important to note that knowledge store is another essential element
in the whole process but still lacking attention towards a better implementation in
healthcare setting. Healthcare organisation is proposed to have an operational knowledge
store that consolidates shared knowledge from multiple business process and source
systems. It must be computed by standard business rules to ensure consistency of results
for other knowledge containers.
6 Conclusion
In conclusion, this paper proposes a process model of KM. The main suggestion from this
paper is that an effective KM should be used for an optimal clinical process and decision-
making. This study also represents an attempt to help clinicians to identify the KM
process they need to perform in their work tasks. This study has several implications.
Theoretically, this study aims to provide a process model that will add to the existing
models on KM process and to extend the initial model used in this study by examining
the contribution of different knowledge workers to the model. This study has helped to
uncover a KM process that appropriately suits clinical process and decision-making. The
development of this model would help the healthcare administrators and professionals to
evaluate their current KM practices and the potential to further improve the process. The
informative concepts and relationships derive from this study can be used by the
practitioners to make deeper and richer assessments of the ways in which they
understand, seek, and use knowledge. The paper has limitations. It is based on a single
case study organisation; hence, the single organisational setting influences the findings.
However, the depth of the study and its findings provide opportunity for further research
in other healthcare or industry settings to test the findings presented here and extend the
15. 32 N. Bahar and S. Bahri
scope of this work. Another direction for future research is to increase the practicality of
the process model. For example, researchers could examine as to whether analysts can
create a KMS, identify the technology and design the information system infrastructure to
aid clinical decision-making.
References
Abou-Zeid, E-S. (2002) ‘A knowledge management reference model’, Journal of Knowledge
Management, Vol. 6, No. 5, pp.486–499.
Adams, G.L. and Lamont, B.T. (2003) ‘Knowledge management systems and developing
sustainable competitive advantage’, Journal of Knowledge Management, Vol. 7 No. 2,
pp.142–154.
Addicott, R., McGivern, G. and Ferlie, E. (2006) ‘Networks, organizational learning and
knowledge management: NHS cancer networks’, Public Money and Management, Vol. 26,
No. 2, pp.87–94.
Alavi, M. and Leidner, D.E. (2001) ‘Review: knowledge management and knowledge management
systems: conceptual foundations and research issues,’ MIS Quarterly, Vol. 25, pp.107–136.
Amayah, A.T. (2013) ‘Determinants of knowledge sharing in a public sector organization’, Journal
of Knowledge Management, Vol. 17, No. 3, pp.454–471.
Amirkhani, A.H., Tajmirriahi, J., Mohammadi, M. and Dalir, M. (2012) ‘Assessing the
effectiveness of knowledge management in empowering and development of human
resources: a case study on Ati Luleh Sepahan company’, Interdisciplinary Journal of
Contemporary Research in Business, Vol. 3, No. 12, p.131.
Anderson, A. (1996) The APQC, The Knowledge Management Assessment Tool.
Andreeva, T. and Kianto, A. (2012) ‘Does knowledge management really matter? Linking
knowledge management practices, competitiveness and economic performance’, Journal of
Knowledge Management, Vol. 16, No. 4, pp.617–636.
Beveren J.V. (2002) ‘A model of knowledge acquisition that refocuses knowledge management’,
Journal of Knowledge Management, Vol. 6, No. 1, pp.18–22.
Beveren, J.V. (2003) ‘Does health care for knowledge management?’, Journal of Knowledge
Management, Vol. 7, No. 1, pp.90–95.
Bose, R. (2003) ‘Knowledge management-enabled health care management systems: capabilities,
infrastructure, and decision-support’, Expert Systems with Applications, Vol. 24, No. 1,
pp.59–71.
Boyd, B.K. and Fulk, J. (1996) ‘Executive scanning and perceived uncertainty: a multidimensional
model’, Journal of Management, Vol. 22, pp.1–21.
Brice, A. and Gray, M. (2003) ‘Knowledge is the enemy of disease’, Library Information Update,
Vol. 2, No. 3, pp.32–35.
Buranarach, M., Supnithi, T. and Chalortham, N. (2009) A Semantic Web Framework to Support
Knowledge Management in Chronic Disease Healthcare MTSR 2009, CCIS 46, Springer-
Verlag, Berlin Heidelberg, pp.164–170.
Camilleri, D. and O’Callaghan, M. (1998) ‘Comparing public and private hospital care service
quality’, International Journal of Health Care Quality Assurance, Vol. 11, No. 4, p.127.
Carneiro, A. (2000) ‘How does knowledge management influence innovation and
competitiveness?’, Journal of Knowledge Management, Vol. 4, No. 2, pp.87–98.
Chapman, R. and Magnusson, M. (2006) ‘Continuous innovation, performance and knowledge
management: an introduction’, Knowledge and Process Management, Vol. 13 No. 3,
pp.129–31.
Clarke, P. and Staunton, N. (1989) Innovation in Technology and Organisation, Routledge,
London.
16. Knowledge management process model 33
Conner, M. (2001) ‘Developing network-based services in the NHS’, International Journal of
Health Care Quality Assurance, Vol. 14, No. 6, pp.237–244.
Dawson, S., Sutherland, K., Dopson, S. and Miller, R. (1999) ‘Changing clinical practice: views
about the management of adult asthma’, Quality in Health Care, Vol. 8, No. 4, pp.253–261.
Demarest, M. (1997) ‘Understanding knowledge management’, Long Range Planning, Vol. 30,
No. 3, pp.321–384.
Diakoulakis, I.E., Georgopoulos, N.B., Koulouriotis, D.E. and Emiris, D. M. (2004) ‘Towards a
holistic knowledge management model’, Journal of Knowledge Management, Vol. 8, No. 1,
pp.32–46.
Dyer, W.G. and Wilkins, A.L. (1991) ‘Better stories, not better constructs, to generate better
theory: a rejoinder to Eisenhardt’, Academy of Management Review, Vol. 16, No. 3,
pp.613–619.
Edge, K. (2005) ‘Powerful public sector knowledge management: a school district example’,
Journal of Knowledge Management, Vol. 9, No. 6, pp.42–52.
Eisenhardt, K.M. (1989) ‘Building theories from case study research’, Academy of Management
Review, Vol. 14, No. 4, pp.532–550.
Ergazakis, K., Metaxiotis, K. and Psarras, J. (2004) ‘Towards knowledge cities: conceptual analysis
and success stories’, Journal of Knowledge Management, Vol. 8, No. 5, pp.5–16.
Essex, B. and Healy, M. (1994) ‘Evaluation of a rule base for decision making in general practice’,
British Journal of General Practice, Vol. 44, No. 382, pp.211–213.
Ferlie, E., Crilly, T., Jashapara, A. and Peckham, A. (2012) ‘Knowledge mobilisation in healthcare:
a critical review of health sector and generic management literature’, Social Science and
Medicine, Vol. 74, p.1297e1304.
Ferlie, E., Fitzgerald, L., Wood, M. and Hawkins, C. (2005) ‘The nonspread of innovations: the
mediating role of professionals’, Academy of Management Journal, Vol. 48, No. 1,
pp.117–134.
Freeman, A.C. and Sweeney, K. (2001) ‘Why general practitioners do not implement evidence:
qualitative study’, British Medical Journal, Vol. 323, No. 7321, p.1100.
Gabbay, J., le May, A., Jefferson, H., Webb, D., Lovelock, R., Powell, J. and Lathlean, J. (2003) ‘A
case study of knowledge management in multiagency consumer-informed communities of
practice: implications for evidence-based policy development in health and social services’,
Health, Vol. 7, No. 3, pp.283–310.
Garg, V.K., Walters, B.A. and Priem, R.L. (2003) ‘Chief executive scanning emphases,
environmental dynamism, and manufacturing firm performance’, Strategic Management
Journal, Vol. 24, pp.725–744.
Gau, W.B. (2011) ‘A study of tacit knowledge management in the public sector’, Journal of
Knowledge Management Practice, Vol. 12, No. 1, pp.1–13.
Gioia, D.A. (1986) ‘Symbols, scripts, and sensemaking: creating meaning in the organizational
experience’, in Sims, H.P. and Gioia, D.A. (Eds.): The Thinking Organization, Jossey-Bass,
San Francisco, pp.49–74.
Hackbarth, G. (1998) ‘The impact of organizational memory on IT systems’, AMCIS 1998
Proceedings, 197.
Hambrick, D.C. (1982) ‘Environmental scanning and organizational strategy’, Strategic
Management Journal, Vol. 3, pp.159–174.
Hojabri, R., Borousan, E. and Manafi, M. (2012) ‘Impact of using telemedicine on knowledge
management in healthcare organizations: a case study’, African Journal of Business
Management, Vol. 6, No. 4, pp.1604–1613.
Jih, W.J., Chen, C.H. and Chen, A. (2006) ‘Effects of knowledge management implementations in
hospitals: an exploratory study in Taiwan’, International Journal of Knowledge Management,
Vol. 2, No. 3, pp.1–20.
17. 34 N. Bahar and S. Bahri
Jordan, J. and Jones, P. (1997) ‘Assessing your company’s knowledge management style’, Long
Range Planning, Vol. 30, No. 3, pp.322–398.
Kruizinga, E., Heijst, G. and Spek, R. (1997) ‘Knowledge infrastructures and intranets’, Journal of
Knowledge Management, Vol. 1, No. 1, pp.27–32.
Lathlean, J. and Le May, A. (2002) ‘Communities of practice: an opportunity for interagency
working’, Journal of Clinical Nursing, Vol. 11, No. 3, pp.394–398.
Lee, J.H. and Kim, Y.G. (2001) ‘A stage model of organizational knowledge management: a latent
content analysis’, Expert Systems with Applications, Vol. 20, No. 4, pp.299–311.
Little, A.D. (1998) ‘Knowledge Management: Reaping the Benefits’, Prism, Second Quarter.
Massaro, M., Dumay, J. and Garlatti, A. (2015) ‘Public sector knowledge management: a structured
literature review’, Journal of Knowledge Management, Vol. 19, No. 3, pp.530–558.
Mathiassen, L., Saarinen, T., Tuunanen, T. and Rossi, M. (2007) ‘A contingency model for
requirements development’, Journal of the Association for Information Systems, Vol. 8,
No. 11, pp.569–597.
McAdam, R. and McCreedy, S. (1999) ‘A critical review of knowledge management models’, The
Learning Organization, Vol. 6, No. 3, pp.91–101.
McAdam, R. and McCreedy, S. (2000) ‘A critique of knowledge management: using a social
constructionist model’, New Technology, Work and Employment, Vol. 15, No. 2, pp.155–168.
Miles, M.B. and Huberman, A.B. (1984) Qualitative Data Analysis: A Source Book of New
Methods, Beverly Hills, CA: Sage.
Mykhalovskiy, E. and Weir, L. (2004) ‘The problem of evidence-based medicine: directions for
social science’, Social Science and Medicine, Vol. 59, No. 5, pp.1059–1069.
Nag, R. and Gioia, D.A. (2012) ‘From common to uncommon knowledge: foundations of
firm- specific use of knowledge as a resource’, Academy of Management Journal, pp.421–457.
Nutley, S., Walter, I. and Davies, H.T. (2003) ‘From knowing to doing a framework for
understanding the evidence-into-practice agenda’, Evaluation, Vol. 9, No. 2, pp.125–148.
O’Leary, D. (1998) ‘Knowledge management systems: converting and connecting’, IEEE
Intelligent Systems, Vol. 13, No. 3, pp.30–33.
Porter, M. and Teisberg, E.O. (2004) ‘Redefining competition in health care’, Harvard Business
Review, Vol. 82, No. 6, pp.65–72.
Quintas, P., Lefrere, P. and Jones, G. (1997) ‘Knowledge management: a strategic agenda’, Long
Range Planning, Vol. 30, No. 3, pp.385–391.
Ragab, M.A.F. and Arisha, A. (2013) ‘Knowledge management and measurement: a critical
review’, Journal of Knowledge Management, Vol. 17, No. 6, pp.873–901.
Sackett, D.L. and Rosenberg, W.M. (1995) ‘The need for evidence-based medicine’, Journal of the
Royal Society of Medicine, Vol. 88, No. 11, pp.620–624.
Saldana, J. (2013) The Coding Manual for Qualitative Researchers, 2nd ed., Sage, London.
Scarbrough, H. (1996) Business Process Re-Design: The Knowledge Dimension, ESRC Business
Process Resource Centre, University of Warwick, Coventry.
Soon, T.T. and Zainol, F.A. (2011) ‘Knowledge management enablers, process and organizational
performance: evidence from Malaysian enterprises’, Asian Social Science, Vol. 7, No. 8,
pp.186–202.
Spek, R. and Spijkervet, A. (1997) ‘Knowledge management: dealing intelligently with
knowledge’, Knowledge management and its integrative elements, pp.31–59.
Sutcliffe, K.M. (1994) ‘What executives notice: accurate perceptions in top management teams’,
Academy of Management Journal, Vol. 37, No. 5, pp.1360–1378.
Tagliaventi, M.R. and Mattarelli, E. (2006) ‘The role of networks of practice, value sharing, and
operational proximity in knowledge flows between professional groups’, Human Relations,
Vol. 59, No. 3, pp.291–319.
18. Knowledge management process model 35
Treasury, H.M. (2006) A Review of UK Health Research Funding: Report by Sir David Cooksey,
HMSO, London.
UNPAN, (2003) Knowledge Management in Government Organizations and Programmes, Geneva,
pp.1–10.
Wiig, K.M. (1997) ‘Integrating intellectual capital and knowledge management’, Long Range
Planning, Vol. 30, No. 3, pp.399–405.
Wills, M.J., Sarnikar, S., El-Gayar, O.F. and Deokar, A.V. (2010) ‘Information systems and
healthcare XXXIV: clinical knowledge management systems—literature review and research
issues for information systems’, Information Systems, Vol. 26, Article 26.
Wood, M., Ferlie, E. and Fitzgerald, L. (1998) ‘Achieving clinical behaviour change: a case of
becoming indeterminate’, Social Science & Medicine, Vol. 47, No. 11, pp.1729–1738.
Yin, R.K. (2013) Case Study Research: Design and Methods, Sage Publications, Thousand Oaks.
Note:
1
Subcoding is a second-order tag assigned after a primary code to enrich the entry.
