Knowledge Management in Healthcare

Abstract

Healthcare organizations are facing many challenges in the 21st Century due to changes taking place in global healthcare systems. Spiraling costs, financial constraints, increased emphasis on accountability and transparency, changes in education, growing complexities of biomedical research, new partnerships in healthcare and great advances in IT suggest that a predominant paradigm shift is occurring. This shift is necessitating a focus on interaction, collaboration and increased sharing of information and knowledge which is in turn leading healthcare organizations to embrace the techniques of Knowledge Management (KM) in order to create and sustain optimal healthcare outcomes. This topic describes the importance of knowledge management systems for healthcare organizations and provides an overview of knowledge management technologies and tools that may be used by healthcare organizations.

Introduction

Knowledge Management (KM) is an essential tool in today’s emerging healthcare system. Hospitals that seek to deploy KM systems need to understand the human element in the process. Earlier, success factors were only restricted to a few healthcare variables such as patient care and cost, but over the years, technology (both clinical and administrative) has evolved as a differentiating variable, thus redefining the doctrines of competition and the administration of healthcare treatments. For example, in today’s healthcare environment we are now treating patients with an emphasis on prevention and managing the patient through good health throughout their life. Such an approach requires significant investment in knowledge assets. One of the key objectives of a KM system is to insulate a hospital’s intellectual knowledge from degeneration (Elliot, 2000).

Most hospitals are unaware of their acquired knowledge base. Further, knowledge capital is often lost from a hospital through employee attrition, high turnover rates, cost-saving measures and improper documentation (Chase, 1998). Specific KM tools and metrics help focus the hospital on acquisition, retrieval and storage of knowledge assets both tangible and/or other for activities such as learning, strategic planning and decision making (Oxbrow, 1998). This goes a long way in crafting a coherent and well-designed growth plan for the hospital (Allee, 1997, 1999). KM treats intellectual capital as a managed asset. Improved patient care is directly proportional to a hospital’s intellectual assets. The tactical expertise and experience of individual workers should be fully captured and reflected in strategy, policy and practice at all levels of the hospital management and patient care activity (Conklin, 1998). The intangible asset of knowledge of the employee can nurture radical innovation in advance planning, change management, hospital culture and well balanced approaches. Fostering a knowledge-sharing attitude and competency of patient care processes are vital for any KM program in healthcare (Burca, 2000; Matheson, 1995). Hospitals managing and sharing their knowledge assets effectively will have benefits of cycle time reduction, cost reduction, improved return on investment, higher satisfaction index, and better medical and paramedical education levels (Antrobus, 1997; Atkins et al., 2001).

knowledge management

Knowledge Management (KM) is an emerging, interdisciplinary business model dealing with all aspects of knowledge within the context of the firm, including knowledge creation, codification, sharing and how these activities promote learning and innovation (Choo, 1998). Unfortunately there’s no universal definition of KM, just as there’s no agreement as to what constitutes knowledge in the first place (Beckman, 1999). For this reason, it’s best to think of KM in the broadest context:

KM is a discipline that promotes an integrated approach to identifying, managing, and sharing all of an enterprise’s information assets, including database, documents, policies and procedures, as well as unarticulated expertise and experience resident in individual workers (Wickramasinghe, 2003). There are many dimensions around which knowledge can be characterized such as storage media, accessibility, typology and hierarchy Each of these dimensions is explained in this topic (Brailer, 1999; Broadbent, 1998; Skyrme, 2001, 1999, 1998; Davenport & Prusak, 1997, 1998).

Knowledge storage Media

There are several media in which knowledge can reside including: the human mind, an organization, a document and/or a computer. Knowledge in the mind is often difficult to access; organizational knowledge is often dispersed and distributed; document knowledge can range from free text to well-structured charts and tables; while computer knowledge can be formalized, sharable and often well structured and well organized. In order to effectively manage KM it is important to pay careful attention to the most useful storage media.

knowledge Accessibility

Intellectual and knowledge-based assets fall into one of three major categories (Nonaka, 1994; Nonaka & Nishguchi, 2001; Sharma & Wickra-masinghe, 2004):

• Tacit (human mind, organization): accessible indirectly only with difficulty through knowledge elicitation and observation of behavior.

• Implicit (humanmind, organization): accessible through querying and discussion, but informal knowledge must first be located and then communicated.

• Explicit (document, computer): readily available, as well as documented into formal knowledge sources that are often well organized, often with the help of IT.

In order for effective KM to ensue, it is necessary to understand these categories of knowledge as well as their subtle nuances.

knowledge Typologies

Typologies are defined, characterized and described in terms of knowledge type-conversion, structural features, elementary properties, purpose and use, and conceptual levels. Knowledge typologies play an integral role in a robust KM system.

knowledge Hierarchy

A further dimension considers the premise that knowledge can be organized into a hierarchy. Several authors draw distinctions between data, information and knowledge (Allee, 1997; Deven-port & Prusack, 1998; Leonard, 1998).

• Data: Facts, images and sounds.

• Information: Formatted, filtered and summarized data.

• Knowledge: Instincts, ideas, rules and procedures that guide action and decisions and are context dependent.

Strictly speaking, KM is a process that identifies and creates knowledge assets. In healthcare, KM optimally utilizes these assets to fulfill the core healthcare objectives. Knowledge assets in hospitals are intangible but they can be defined as knowledge that a medical/paramedical/non-medical person has with respect to patient care, medical needs, operating environment and technologies, something that he or she can utilize in routine medical and healthcare management. KM identifies and maps intellectual assets within the hospital, thereby generating precious knowledge capital for competitive advantage within the medical institution. Since knowledge is dynamically imbedded in organizational and healthcare networks and processes as well as in the staff that use them, hospitals need to have a built-in KM system that “crisscrosses” with its healthcare networks (Jackson, 2000). The result is that employees will then be better informed and continuously updated on the latest tools and best practices. It is important that the techniques adopted to enable KM must take into account some basic factors such as the type of hospital, its culture and its needs to ensure a successful KM system for a healthcare setting (Gokce, 2002; Johnson, 1998; Keeling & Lambert, 2000).

The Need For km IN healthcare

The health sector is large, accounting for between 6% to 12% of GDP across OECD countries. Though the use of healthcare services varies between nations, public expectations of them globally have risen dramatically everywhere since 1950 and the trend is still upwards. Fresh demands arise from the appearance of new drugs and the invention of new technology, from advances in prevention and diagnosis as well as therapy, and from new categories of demand, such as care of the elderly (Eisenberg, 2002). The health sector is complex and includes a range of key actors: patients, providers, practitioners, payers, purchasers, pharmaceutical industry, and professors. The interaction among these actors shapes what counts as relevant knowledge as well as how it is produced, mediated, and used (Conner, 2001). Further, the domain of medical knowledge has expanded to such a degree that a human mind can no longer retain it all. There are now some 20,000 medical journals in the world. A professor of medicine spends on average one day a week to remain abreast of studies in his/her field of interest as well as for his/her research. What can a generalist physician do? How much time can he/she devote to “keeping up”? In France, there are some 7,000 prescription drugs based on some 3,500 active ingredients. A physician has the right to prescribe them all. Can he/she be familiar with all of them? He/she must also be aware of some 300 medical references, some 800 biological tests, more than 1,000 imagery tests, and more than 1,500 surgical interventions. If he/she prescribes six drugs, he/she must also be aware of some 720 potential sources of interaction. The figure reaches 3,328,800 if 10 drugs are prescribed. In addition to the therapeutic value of each molecule, the physician should also know their price and potential effect on specific population groups (diabetics, the obese, children, the elderly, etc. The growth in knowledge has necessarily led to specialization, which too has meant “balkanization” and lack of coordination, especially in hospitals but also in private practice (Halpern, Perry & Narayan, 2001; Dean, 2002). As knowledge is shared, responsibility and decisions about treatment should be shared as well (Eisenberg, 2002). Hospital Information Management (HIM) professionals, like other healthcare personnel, have always sought, used, and valued knowledge about their practice. Managers hire experience because they understand the value of knowledge that has been developed and proven over time. Unfortunately, they are bombarded each day with information in the form of e-mails, voice mails, faxes, reports, memos, and so on — much of which is repetitive or simply not useful. On the other hand, the same professionals spend a great deal of time looking for the information they need by accessing the Web, sending e-mails, making phone calls, and scouring computerized reports. It is in this process that KM can make a difference. Studies have shown that managers get two-thirds of their information from face-to-face meetings or phone conversations. Only one-third comes from documents or other knowledge bases. Unlike material assets, which decrease in value as they are used, the value of knowledge increases with use. For example, new ideas on records storage or retrieval breed other new ideas, and shared knowledge stays with the giver while it enriches the receiver (Jadad, Haynes, Hunt & Browman, 2000). The potential for new ideas arising from the store of knowledge in any healthcare organization is to provide a common entry point for corporate knowledge, such as formularies, clinical road maps, and key financial indicators (Einbinder, Klein & Safran, 1997). Thus what we can see is that the need for KM in healthcare is critical and becomes significant when it begins to focus on the needs of individual users, departmental indicators, and key processes in order to capture and display relevant, useful, and usable knowledge in a customized fashion (Sorrells & Weaver, 1999a, 1999b, 1999c).

Approaches to capture, store and share knowledge

For companies that need to leverage their corporate knowledge, the following four initiatives may help you establish a knowledge sharing system of your own. These initiatives draw upon a predominate, repository model but are also relevant to other models (Morrissey, 1998).

Build the Infrastructure using Appropriate Technology

Technology enables connectedness to take place in ways that have never before been possible. Harnessing intellectual capital can be expedited through a network-computing infrastructure. Technology has emerged to support each different approach to knowledge management. Document management systems expedite document storage and retrieval. Web-casts allow synchronous communication between experts while discussion groups enable asynchronous interaction. Learning management systems track an employee’s progress with continuous learning while data warehousing mines powerful SQL databases, which organize and analyze highly structured information. Paramount to the successful use of these technologies is naturally a flexible, robust IT infrastructure (Sharma & Wickramasinghe, 2004).

Build a conceptual Infrastructure with competencies as the Backbone

Technology is important in harnessing intellectual assets, but integrated solutions encompass more than that. You must rethink the conceptual infrastructure of your business. For example, you may need to: ensure intellectual assets reflect your vision and values; articulate the theoretical framework for your processes; establish a taxonomy or categorization scheme to organize your information; create cross references that reflect relationships between entries; or index your information using attributes or meta-tags. The notion of competence plays a critical role in knowledge indexing and sharing. Karl Erik Sveiby, noted Swedish expert on managing and measuring knowledge-based assets, observes, “The concept of competence, which embraces factual knowledge, skills, experience, value judgments and social networks is the best way to describe knowledge in the business context.” Once competencies or target proficiencies are defined, they become the backbone, which connects users to useful, relevant knowledge.

create a Repository of Reusable components and other Resources

Before the Industrial Revolution, products were handcrafted; each piece was unique and couldn’t be reused. The genius of the Industrial Revolution centered on making reusable parts and components became standardized and interchangeable. The Information Revolution is similar. Instead of crafting a unique solution each time, knowledge sharing creates a warehouse of “stored parts” — e.g., standardized and interchangeable components which can be reused and adapted: skills, best practices, models and frameworks, approaches and techniques, tools, concepts, specific experiences, presentation aids, white papers, etc. Adding to this, resources such as directories of experts indexed by their field can help you gain access to knowledge outside of your core competencies.

Set High standards for Quality and usability

Ensure that your information complies with high quality standards because it is the foundation upon which to build a knowledge-centric healthcare organization. In addition, it is important to make sure that the system meets the users’ needs, which may involve reworking or restructuring information. Leonard Caldwell observed: “Critical information must first be reorganized so that information is presented in a way that mirrors users’ needs and parallels a thought process occurring within a job function or task.” Establishing consistent patterns helps end-users find information quickly. Online coaching can provide users with tips and techniques on how to modify, customize, or tailor information. Leveraging organizational knowledge is not an option — it is an imperative if one is to flourish in the marketplace. It can lead into a new phase of quality and innovation.

It will reduce cycle time and gives a competitive advantage as a company. The synergy will also contribute to growth as individuals. Companies who have the foresight to manage their knowledge capital now will have an advantage in the future (Herbig, Bussing & Ewert, 2001).

km tools and technologies

The paraphernalia of the information revolution — computers, communications networks, compact discs, imaging systems and so on — are now widely expected to make a vital contribution to helping doctors and other medical professionals do their work better (Gokce, 2002). New information technologies include:

• Electronic patient records, which are more up to date, easier to access, and more complete than paper ones;

• Standardized medical terminologies and languages, both within and across natural language communities;

• Methods and tools to support faster dissemination of information via the Internet that leads to new scientific understanding of diseases and their treatment;

• More timely and reliable methods and tools to support better communication and coordination among members of healthcare teams;

• A creative approach to KM can result in improved efficiency, higher productivity and increased revenues in practically any business function.

The technical goal of KM initiatives is to give the organization the ability to mine its own knowledge assets, which could include creating such tools as a centralized search capability, automatic indexing and categorization, content analysis and preparation, data analysis, and customizable features integrated in a digital dashboard. Process improvement is a precursor to providing a knowledge-centered environment. Before an organization can foster collaboration and knowledge sharing, the organization must possess an understanding of information flows and of the overall knowledge infrastructure. There is no such thing as the perfect KM product. Instead, different tool sets can be integrated with the organization’s legacy systems (Heathfield & Louw, 1999). Technical issues that KM projects must address include:

• Setting up electronic delivery strategies for information

• Identifying information sources and services

• Building decision support tools and data-mining templates

• Establishing enterprise-wide business rules

• Implementing process improvement techniques

Knowledge Mapping

Knowledge management is rapidly becoming a critical success factor for competitive organizations. Carrying out knowledge management effectively in an industrial environment requires support from a repertoire of methods, techniques and tools, in particular knowledge engineering technology adapted for knowledge management. Knowledge mapping creates high-level knowledge models in a transparent graphical form. Using knowledge maps, management can get an overview of available and missing knowledge in core business areas and make appropriate knowledge management decisions. Knowledge mapping is a good example of a useful knowledge management activity with existing knowledge acquisition and modeling techniques at its foundations (Straw-ser, 2000). Knowledge mapping is a technique rather than a product. A knowledge map could be used as a visual example of how information is passed from one part of an organization or group to another and is usually a good place to start understanding what types of intellectual assets the organization has at its disposal. Most organizations that have implemented KM applications provide a context and framework for the way knowledge is gained. KM is usually an integral part of continuous quality improvement or total quality management projects. Several consultants offer knowledge-mapping methodologies (Heathfield & Louw, 1999).

Process-Based Knowledge Map

A process-based knowledge map is essentially a map or diagram that visually displays knowledge within the context of a business process. In other words, the map shows how knowledge should be used within the processes and sources of this knowledge. The overview of the business process is prepared before the knowledge and the sources are mapped to this process. Any type of knowledge that drives the process or results from execution of the process can be mapped. This could include tacit knowledge (knowledge that resides in people such as know-how, experience, and intuition) and explicit knowledge (codified knowledge that is found in documents); customer knowledge; knowledge in processes; etc.

Intelligent Agents

In the early days of online information retrieval systems, individuals met with search intermediaries who were trained to use the online systems. The intermediaries were often knowledgeable about the information seeker’s area of interest. Today, technology in the form of personal computers and the Internet provides users with the means to access the online databases from their own offices. However, distributed sources of online information, e.g., the World Wide Web (WWW), compound the problem of information searching.

Both novice and experienced users still need support with the search process and the integration of information. To address this problem, agents have been developed for information management applications. The goal of intelligent search agents is to allow end-users to search effectively, be it either a single database of bibliographic records or a network of distributed, heterogeneous, hypertext documents. The approaches range from desktop agents specialized for a single user to networks of agents used to collect data from distributed information sources. Intelligent agents use a combination of profiling techniques, search tools, and recognition algorithms to “push” information to the decision maker on a regular basis. Because intelligent agents use a standard Web analogy, users can quickly set up “net casts” of internal information to automatically receive knowledge bases when they become available. For example, a physician can request that lab results be forwarded to his or her individual dashboard as soon as the lab has completed the procedure. One cautionary note: using push technologies can result in an information flood if filters are not configured to reduce unwanted or unnecessary data (Strawser, 2000).

web Browsers

Web browsers such as Microsoft’s Internet Explorer are practical because of their cost and relative ease of use, and they have become the preferred presentation layer for accessing knowledge bases. The productivity potential inherent in browsers is similar to that of wireless phones. The freer the knowledge worker is of place, time, medium, and device, the less time is spent on the process of messaging, and the more time is available for results. The less time spent on process, the shorter the knowledge cycle, which can be a significant productivity advantage (Strawser, 2000).

KM Applications

Most new KM applications consist of two major elements (often integrated into one interface): a means for employees looking for specialized knowledge to hook up with other people in the organization with the same knowledge (usually via a web application), in other words, an easy way for employees to tap into tacit knowledge resources (people); and a means for employees looking for specialized knowledge to search relevant documents/data (also usually via a web application), in other words, an easy way for employees to tap into explicit knowledge. KM applications are usually designed to support a particular information set in an organization, such as length-of-stay margin management, physician profitability, or accounts receivable recovery. Some consulting firms offer a base set oftemplates as a core application, focusing on desktop applications, whereas others have developed information sets that provide encyclopedic knowledge of a particular healthcare segment, such as physician issues (Strawser, 2000).

Workflow Applications

In the software world, and in particular in the imaging subset of that world, the need arose to send a particular (bit-mapped) document to a particular workstation or users on a network. This simple routing and distribution was called “workflow.” It was quickly learned that these work items could be “tracked,” which allowed the accumulation of data about not only where an item had been but also on what happened to it along the way. Who worked on it, how long it was there, the status it had leaving a point, and where it went next was starting to look much more like the manufacturing model. If data was also accumulated about the workers in this operation (how many did they complete, to what status, how long did it take for each) the model was complete. Workflow applications, such as Lotus Notes or Outlook 2000, also play an important role in a KM implementation. For example, a KM solution based on Office 2000 could serve as a nurse triage application, integrating automatic call distribution and transaction-processing systems, in concert with a knowledge base of typical responses to patient questions and symptoms (Strawser, 2000). These described technologies and tools can be exploited to create data banks, knowledge banks and a KM software as shown in Table 1, which will be a great help for providing better solutions for healthcare.

These data banks can be readily accessed through a network (Internet or intranet) if the user has at his/her disposal a workstation, software, and passwords that give access to these networks and their different sites. The system should be made flexible so that it can be adaptable in time and space, and can be customized: each physician can, when he/she wishes, consult one of the banks or receive specific information on the fields which he/she has chosen in advance. Access need not be limited to physicians alone, but can also be made available to health professionals and the public, and the latter could adapt behavior to help prevent the onset of illness. Of course, these data banks have to be organized, updated continuously and meet users’ expectations by allowing them to ask questions and to engage in discussions among themselves, so that it is always possible to evaluate the quality of the information consulted (Fitchett, 1998). The knowledge bank can make it possible to consult experts located elsewhere and to transmit images and other elements of a patient’s file to a colleague to obtain an opinion, a practice currently known as “tele-medicine” (Hansen & Nohria, 1999). Software can help to offer software diagnostic and prescription aids to extend this knowledge (Confessore, 1997; Wyatt, 2000; Timpson, 1998).

Table 1. Data banks, knowledge banks and KM software

conclusions

Until recently, most of the knowledge experience and learning about KM had been accessible to only a few practitioners. However, during the past three years an explosion of interest, research, and applications in KM has occurred. There is some concern among the practitioners that KM might suffer a fate similar to business reengi-neering, artificial intelligence, and total quality management. That is, interest in the discipline must last long enough to iron out the bugs while simultaneously delivering significant business value. The irony is that just when the discipline works well, potential users often have lost interest in the fad, point to the inevitable early failures, and thus miss out on the real benefits. Unless the very ambitious and interesting KM initiatives in healthcare evolve differently, even if they work in a technical sense, they will not work in the economic sense and the healthcare system will continue to be what it is today: an immense apparatus for reimbursing healthcare costs. However, there will still be a health/social services network and a medical profession that is familiar with the tools and power of the Internet. The experience will not be totally negative, even if it is likely to reach goals that are different from those set at the outset. Although considerable progress has been achieved in KM across a broad front, much work remains to fully deliver the business value that KM promises. Ultimately, in order to realize the enormous potential value from KM, organizations must motivate and enable creating, organizing and sharing knowledge.