Issues in Clinical Knowledge Management: Revisiting Healthcare Management

Abstract

The objective of this topic is to examine some of the key issues surrounding the incorporation of the Knowledge Management (KM) paradigm in healthcare. We discuss whether it would it be beneficial for healthcare organizations to adopt the KM paradigm so as to facilitate effective decision-making in the context of healthcare delivery. Alternative healthcare management concepts with respect to their ability in providing a solution to the above-mentioned issue are reviewed. This topic concludes that the KM paradigm can transform the healthcare sector.

introduction

In today’s information age, data has become a major asset for healthcare institutions. Recent innovations in Information Technology (IT) have transformed the way that healthcare organizations function. Applications of concepts such as Data Warehousing and Data Mining have exponentially increased the amount of information to which a healthcare organization has access, thus creating the problem of “information explosion”. This problem has been further accentuated by the advent of new disciplines such as Bioinformat-ics and Genetic Engineering, both of which hold very promising solutions which may significantly change the face of the entire healthcare process from diagnosis to delivery (Dwivedi, Bali, James, Naguib, & Johnston, 2002b).

Until the early 1980s, IT solutions for healthcare used to focus on such concepts as data warehousing. The emphasis was on storage of data in an electronic medium, the prime objective of which was to allow exploitation of this data at a later point in time. As such, most of the IT applications in healthcare were built to provide support for retrospective information retrieval needs and, in some cases, to analyze the decisions undertaken. This has changed healthcare institutions’ perspectives towards the concept of utility of clinical data. Clinical data that was traditionally used in a supportive capacity for historical purposes has today become an opportunity that allows healthcare stakeholders to tackle problems before they arise.

Healthcare Management concepts

Healthcare managers are being forced to examine costs associated with healthcare and are under increasing pressure to discover approaches that would help carry out activities better, faster and cheaper (Davis & Klein, 2000; Latamore, 1999). Workflow and associated Internet technologies are being seen as an instrument to cut administrative expenses. Specifically designed IT implementations such as workflow tools are being used to automate the electronic paper flow in a managed care operation, thereby cutting administrative expenses (Latamore, 1999).

One of the most challenging issues in healthcare relates to the transformation of raw clinical data into contextually relevant information. Advances in IT and telecommunications have made it possible for healthcare institutions to face the challenge of transforming large amounts of medical data into relevant clinical information (Dwivedi, Bali, James, & Naguib, 2001b). This can be achieved by integrating information using workflow, context management and collaboration tools, giving healthcare a mechanism for effectively transferring the acquired knowledge, as and when required (Dwivedi, Bali, James, & Naguib, 2002a).

Kennedy (1995, p. 85) quotes Keever (a healthcare management executive) who notes that “Healthcare is the most disjointed industry. ..in terms of information exchange… Every hospital, doctor, insurer and independent lab has its own set of information, and . no one does a very good job of sharing it.” From a management perspective, these new challenges have forced healthcare stakeholders to look at different healthcare management concepts that could alleviate the problem of information explosion. The following are some of the new paradigms and concepts that have caught the attention of healthcare stakeholders.

evidence based medicine (ebm)

EBM is defined as the “conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients” (Cowling, Newman, & Leigh, 1999, p. 149). A typical EBM process starts with an identification of knowledge-gaps in current healthcare treatment processes, followed by a search for the best evidence. This is then succeeded by a process to aid in the selection of appropriate electronic data/information sources and IT applications that focus on clinical competencies in the context of the best evidence generated.

The next step is to carry out a critical appraisal of the best evidence identified by carrying out checks for accuracy and diagnostic validity of the procedure/treatment identified by the best evidence generated. The costs and benefits of alternative procedures (i.e., the current best evidence procedure/treatment being recommended) are then considered. The last step is its application to patients’ healthcare which calls for integration of the best evidence with the General Practitioners’ (GP) clinical expertise so as to provide best treatment and care (Cowling et al., 1999).

model of integrated patient pathways (mipp/ipp)

Schmid and Conen (2000) have argued that the model of integrated patient pathways (MIPP/IPP) is a more comprehensive concept for healthcare institutions. As the acronym suggests, IPPs aim to enable better support for healthcare institutions by focusing on the creation of clinical guidelines for commonly accepted diagnostic and therapeutic procedures at a defined level of quality. This would lead to cost-efficient treatment. It could be argued that IPP calls for in-house development of standardized clinical treatment procedures for some pre-defined diagnoses and treatments.

Schmid & Conen (2000) elaborate that IPP aims to ensure that patients receive the right treatment which is based upon best practice guidelines that have sufficient evidence to warrant the label of “best practice” and which have been proven to be clinically adequate. They argue that when a hospital tries to implement IPP, it will automatically go through a circular chain process that calls for identifying sources of best practice, converting them to worldwide implementation practices and then, based upon their performance, converting them to benchmarks. Deliberation on current health reform is centered on two competing objectives: expanding access and containing costs. The challenge is to find an acceptable balance between providing increased access to healthcare services while at the same time conserving healthcare resources.

Pryga and Dyer (1992) have noted that, in the USA, hospitals receive a fixed amount per patient for each Medicare patient admission. As such, they have an objective of providing essential medical services whilst physicians are remunerated on the basis of the clinical service provided. The situation emerges where the physician and healthcare managers can have conflicting goals; such a dilemma is bound to affect formulation of best care practices particularly for preventive care.

clinical governance (cg)

Clinical governance (CG) was first introduced in the UK by way of a National Health Service (NHS) white paper (Firth-Cozens, 1999) and calls for an integrated approach to quality, team development, clinical audit skills, risk management skills, and information systems. A typical CG process can be delineated into a sequential process that calls for (a) the means to disseminate knowledge about relevant evidence from research, (b) best treatments rather than focusing just on recognition of poor treatments, (c) better appreciation of what IT led solutions can do for clinical governance, and (d) knowing what data/information is available so as to provide baselines for best care and treatments.

Melvin, Wright, Harrison, Robinson, Connelly, and Williams (1999) have remarked that the NHS has witnessed the incorporation and development of many approaches that support and promote effective healthcare, but in practice, none of them have been successful. Research by Zairi and Whymark (1999) submits that the problem lies in the lack of proper systems to support the measurement of organizational effectiveness (i.e., clinical) in a healthcare delivery context.

According to Sewell (1997), one of the biggest challenges in having concise summaries of the most effective clinical practices is establishing what is meant by “quality in healthcare” (i.e., a measurement standard for clinical effectiveness). Sewell (1997) elaborates that measurement standards in clinical practice will change from each context and that this is attributed to the linkage between measurement standards and values and the expectations of the individual healthcare stakeholders (which, in turn, originate from the shared values and expectations to which all the healthcare stakeholders subscribe).

Melvin, et al. (1999) have noted that, in the UK, the NHS has started to support the concept of clinical governance by identifying individual best effective clinical practices. This process provides concise summaries of the most effective clinical practices in all key clinical areas. Summaries that are successfully substantiated are then disseminated throughout the NHS. Sewell (1997) has noted that the USA, Canada, Australia and New Zealand have adopted a formal accreditation system for the healthcare sector based upon the ISO 9000 approach.

community health information networks (chin)

Modern day healthcare organizations have realized that in the future their survival would depend upon their ability to give the caregiver access to such information that would enable the caregiver to deliver personalized clinical diagnosis and treatment in real-time in very specific clinical contexts, a process termed Information Therapy (Dwivedi et al., 2002a). This vision has been translated into concepts such as Integrated Delivery System (IDS) and Community Health Information Networks (CHIN) (Lang, 1997; Mercer, 2001; Morrissey, 2000).

IDS refers to a Healthcare Information System (HIS), a business model based on computing technologies such as Object Orientation (OO) “to share key data, with partners and providers, that will allow faster and more accurate decision making . to deliver care to a broader population with fewer requirements for expensive and scarce resources” (Lang, 1997, p.18).

CHINs are integrated healthcare institutions based upon a combination of different technology platforms connected to enable support for data sharing amongst different healthcare providers (Mercer, 2001). Both IDS and CHIN are very similar in nature and both refer to an integrated network for allowing the delivery of personalized healthcare. CHINs were founded on the premise that patient information should be shared by competitors (Morrissey, 2000). The main aim of CHIN was to enable hospitals and other healthcare stakeholders to electronically exchange patient encounter summaries and medical records between emergency departments and related departments.

Another factor responsible for emphasis on CHIN was the perception in the healthcare industry that, for small-scale players to survive as individual entities, it was essential for them to form some sort of technological alliances (Huston & Huston, 2000). The original technological objective of CHIN was to enhance data-sharing capabilities amongst different healthcare stakeholders. The original technological infrastructure supported the creation of “point to point” connections. This did not succeed primarily due to limitations in technology coupled with the high amount offinancial resources required to establish the “point to point” technological infrastructure (Morrissey, 2000).

The objective behind the incorporation of the CHIN concept is that it allows users to collect data which could be used to formulate “best practice protocols for effective treatment at a low-cost”, that is, clinical best evidence practices for both healthcare diagnosis and delivery (Kennedy, 1995). It was anticipated that the advent of CHINs in conjunction with Internet technologies would empower healthcare stakeholders to provide healthcare to patients in real time whilst being in geographically distinct locations (Kennedy, 1995).

km taxonomies

KM has become an important focus area for organizations (Earl & Scott, 1999). It has been argued that KM evolved from the applications of expert systems and artificial intelligence (Liebowitz & Beckman, 1998; Sieloff, 1999). Almost all of the definitions of KM state that it is a multi-disciplinary paradigm (Gupta, Iyer & Aronson, 2000) that has further accentuated the controversy regarding the origins of KM. One of the main factors behind widespread interest in KM is its role as a possible source of competitive advantage (Havens & Knapp, 1999; Nonaka, 1991). A number of leading management researchers have affirmed that the Hungarian chemist, economist and philosopher Michael Polanyi was among the earliest theorists who popularized the concept of characterizing knowledge as “tacit or explicit” which is now recognized as the accepted knowledge categorization approach (Gupta et al., 2000; Hansen, Nohria & Tierney, 1999; Zack, 1999).

The cornerstone of any KM project is to transform tacit knowledge to explicit knowledge so as to allow its effective dissemination (Gupta et al., 2000). This can be best met by developing a KM framework. Authors such as Blackler (1995) have reiterated that the concept of knowledge is complex and, in an organizational context, its relevance to organization theory has not yet been sufficiently understood and documented. This is one of the fundamental reasons why KM does not have a widely accepted framework that can enable healthcare institutions in creating KM systems and a culture conducive to KM practices.

KM is underpinned by information technology paradigms such as Workflow, Intelligent Agents and Data Mining. According to Manchester (1999), a common point about software technologies such as (1) information retrieval, (2) document management and (3) workflow processing is that they blend well with the Internet and related technologies (i.e., technologies which focus on dissemination of information). Deveau (2000, p. 14) submits that: “KM is about mapping processes and exploiting the knowledge database. It’s taking people’s minds and applying technology.” Deveau (2000) also noted that information technology puts the organization in a position to state the currently available information in the organizational knowledge base. At this point, the role of IT ends and the role of KM commences.

As KM deals with the tacit and contextual aspects of information, it allows an organization to know what is important for it in particular circumstances, in the process maximizing the value of that information and creating competitive advantages and wealth.

applicability of the km paradigm in healthcare

A KM solution would allow healthcare institutions to give clinical data context, so as to allow knowledge derivation for more effective clinical diagnoses. In the future, healthcare systems would see increased interest in knowledge recycling of the collaborative learning process acquired from previous healthcare industry practices. This topic puts forward the notion that this sector has been exclusively focused on IT to meet the challenges described above and reiterates that this challenge cannot be met by an IT led solution.

KM initiatives should be incorporated within the technological revolution that is speeding across healthcare industry. There has to be balance between organizational and technological aspects of the healthcare process, that is, one cannot exist without the other (Dwivedi et al., 2001a). This topic emphasizes the importance of clinicians taking a holistic view of their organization. Clinicians therefore need to have an understanding of IT in a healthcare context and a shared vision of the organization. Clinicians and healthcare administrators thus need to acquire both organizational and technological insights if they are to have a holistic view of their organization.

The KM paradigm can enable the healthcare sector to successfully overcome the information and knowledge explosion, made possible by adopting a KM framework that is specially customized for healthcare institutions in light of their ICT implementation level. Adoption of KM is essential for healthcare institutions as it would enable them to identify, preserve and disseminate “best context” healthcare practices to different healthcare stakeholders.

prefatory analysis of alternative healthcare concepts

The failure of some healthcare management concepts propelled a new stream of thought that advocated the incorporation of the KM paradigm in healthcare (Health Canada, 1999; Mercer, 2001). KM could allow healthcare organizations to truly take advantage of the driving forces behind the creation of the CHIN concept. However, very few organizations have adopted a comprehensive healthcare KM system. The main reason attributed is the failure of healthcare stakeholders in properly creating a conducive organizational culture. Based on a literature review above, a preliminary conceptual analysis of alternative healthcare management concepts is presented in Table 1. As can be seen from the table, healthcare stakeholders are searching for alternative paradigms that support collaboration in order to synergisti-cally learn from others’ experiences, training and knowledge within specific organizational cultures. Healthcare institutions have realized that existing concepts such as EBM and CG do not enable healthcare stakeholders to achieve this challenge as they do not holistically support effective integration of IT within specific organizational cultures and processes. Contemporary concepts such as EBM, CHIN, ICHDS and IPP focus on

IT at the expense of having too little emphasis on people. This is further aggravated by the presence of dysfunctional organizational processes in the majority of healthcare institutions.

conclusion

For any healthcare organization to succeed, it needs to excel in a number of key processes (i.e., patient diagnosis, care treatment, etc.) that are necessary for it to achieve its mission. If the processes are repetitive, automation is possible via the use of IT. Modern IT applications in healthcare are not sufficient in meeting the information needs of current healthcare institutions as they lack the ability to deliver precise, accurate and contextual information to the desired caregiver at the desired time.

This topic has presented an analysis of alternative healthcare management concepts with respect to their ability in providing a solution to the issue of information management. Furthermore, this topic has examined the feasibility of the KM paradigm in solving the problem of information explosion in healthcare and has found validation for the proposition that the current focus on technological solutions will aggravate the problem of explosion in clinical information systems for healthcare institutions.

Table 1. Prefatory analysis of alternative healthcare concepts


Concept

Support for People

Support for Process

Support for Technology

Limitations

CG

Present

Insufficient

Present

Policy initiative

EBM

Insufficient

Insufficient

Present

Tacit Processes?

CHIN

Insufficient

Absent

Present

Limited Trials

IHCDS

Insufficient

Insufficient

Present

Technology focus

IPP

Insufficient

Present

Present

Tacit Knowledge?

KM

Present

Present

Present

Not validated

The topic has also presented the key requirements for creating a KM framework, which can act as a template in enabling healthcare institutions in their attempts to initiate KM projects. This topic concludes that any potential solution has to come from a domain that synergistically combines people, organizational processes and technology, thereby enabling healthcare stakeholders to have a holistic view of the entire healthcare continuum. This topic further concludes that KM is the only paradigm that combines the above-mentioned perspectives (i.e., people, organizational processes, and technology) into healthcare and as such, KM is the next indispensable step for integrated healthcare management.

Next post:

Previous post: