Approximately 328.24 million people live in the U.S., most of whom require health care services.1,2 Health care is a knowledge-driven industry, and delivery of quality services is heavily dependent on evidence-based medicine and the ability of clinicians to access timely, relevant data and information. But as medical science evolves daily through research, innovation, and new treatments, effectively caring for individual patients in a specific health care setting is becoming exponentially more complex.
Part of this complexity is attributable to the voluminous amount of health care data that now can be collected through information and communication technologies. New knowledge is generated from these data faster than most clinicians can translate, disseminate, and apply it in practice. Clinicians must be able to access not only clinical knowledge, but also information about organizational processes, workflow, evidence-based guidelines, and best practices to provide the best possible patient care.
Explicitly and formally representing these data and processes digitally as knowledge is known as knowledge management.
Explicitly and formally representing these data and processes digitally as knowledge is known as knowledge management. The goal of knowledge management is to provide the decision-maker with appropriate tools, technologies, strategies, and processes to turn data and information into valuable structured, computable, and sharable representation of clinical knowledge, otherwise known as knowledge assets.3 Clinicians are perhaps the most advanced knowledge workers, and their information tools must align with their mental models, cognitive processes, and actual work processes. Knowledge management systems not only can improve the flow of information between all providers and staff, but also provide cognitive support and orient information management activities to real-world clinical workflows. This support can lead to increased efficiency, fewer preventable errors, lower costs, reduced cognitive burden, greater innovation, more informed decision-making, and, ultimately, improved patient care.
Knowledge management and its applications in health care
The discussion of knowledge can be traced back to ancient civilizations, but modern-day knowledge management evolved in the late 1980s.4 This evolution was spurred by the emergence of the Internet and the broadened use of information technology in businesses, coupled with the acknowledgment of the value of a company’s information and knowledge assets.5 As the discipline grew, the need for these methods in corporate settings shed light on the goals and challenges of knowledge management. Applied effectively, knowledge management can be used to increase a company’s performance, evaluate risk, assist in the development of partnerships, align management, enhance economic value, and aid in the development of quality and performance measurement tools.6 So, although the principles and theories of knowledge management originated in the business sector, it has proven to be widely applicable and beneficial in the health care setting as well.
Knowledge management concepts applied in health care
Health care knowledge management can be described as the systematic creation, modeling, sharing, operationalization, and translation of health care knowledge to improve the quality of patient care.7 The goal of health care knowledge management is to provide the most relevant health care information (gathered both internally and externally) to the right people, at the right time, in the right way to enable them to make the most well-informed and cost-effective patient care decisions.
Another goal of health care knowledge management is to transform a health care facility into a learning environment in which new knowledge is continually generated, shared, used, and improved.
Classification and types of knowledge in health care
Explicit knowledge is information that can be codified in paper or electronic form through identifying, capturing, indexing, and disseminating for use.7 Examples of explicit health care knowledge include disease processes, risk and severity scores, predictive models, clinical practice guidelines and care pathways, quality measures, clinical workflows, and drug knowledge bases (drug-drug and drug-allergy interactions, drug classes, physiologic effects, mechanisms of action, indications, and contradictions).7
Explicit and evolvable definitions of diseases, procedures, therapeutics, diagnostics, evidence-based practices, workflows, along with clinician knowledge lie at the core of the practice of medicine. But it is not always possible to derive the full maturity and breadth of knowledge assets, such as clinical decision support (CDS), quality measures, and user interfaces, from available health care knowledge. Well-established best practices in health care knowledge management and clinical informatics can be used to leverage explicit knowledge in powerful ways.
The role of health information technology and digital health tools
Development of health information technology and the broader digital transformation of health care have played a major role in the advancement of health care knowledge management. To a large extent, health care data collected today are in a digital format, and health care knowledge is updated and expanded constantly. Therefore, digital health tools are essential for gathering multisource health care data from electronic health records (EHRs), registries, health information exchanges, biosensors and wearables, smart devices and hospitals, data warehouses, cloud storage technology, other repositories, and any other interoperable software or tools.
Digital health care tools also are necessary to support data interoperability to exchange, assess, synthesize, and articulate multisource and multiformat health care information into a coherent knowledge base that can be leveraged in day-to-day patient engagement and point-of-care decision-making.8 Such digital health tools and new technologies play a role in driving an evolution in health care through the power of clinical decision support software, artificial intelligence and machine learning, blockchain, and cloud computing. Using health information technology to apply knowledge management concepts requires a well-coordinated and systemic approach that goes far beyond buying and installing software.
Advantages of applying knowledge management concepts
Some of the main advantages of applying knowledge management concepts to health care are as follows.
- Foster collaboration and knowledge sharing: Health care delivery can involve many team members. In surgery alone, the surgeon, anesthesiologist, nurses, physician assistants, pathologist, radiologist, primary care physician, hospitalists, and any number of other specialists may be involved in a patient’s care. Knowledge management processes and tools can foster collaborative problem solving, discussion, and sharing of data and knowledge throughout the patient’s surgical care journey.9 One such example is an interoperable shared care plan including knowledge-enriched data, explicit links to source knowledge, as well as clinical assessments and rationale. Optimal clinical workflow models then can leverage this best practice care knowledge to enable best practice care delivery.
- Manage system complexity: Beyond clinicians, health care delivery also involves third parties, such as hospital and clinical administrators, financial professionals, human resources, drug companies, insurance companies, and more.4 Health care knowledge management techniques can tie together the knowledge from these different partners working in different domains.4 Furthermore, knowledge management enables distinct types of knowledge to evolve by allowing focus on specific areas of health care (for example, distinct disease models, pharmacologic knowledge bases, best practice guidelines and pathways, and clinical workflows), while also explicitly managing the relationships between these distinct assets to realize high-value, clinically-oriented information tools.
- Reduce cognitive burden: Knowledge management systems can reduce cognitive burden by identifying, representing, and aligning clinical knowledge with clinicians’ mental models (for example, knowledge about diseases, procedures, organ systems, and so on) as well as clinicians’ cognitive processes (for example, differential diagnoses and treatment planning). Also known as cognitive support, this benefit of knowledge management systems allows for explicit and valuable inferences to be precomputed and stored for use in cases such as practice, operations, and research. Cognitive support allows clinicians to leverage medical knowledge and digital health software to take appropriate actions quickly and easily.
- Leverage knowledge, build a learning organization, and spur innovation: Clinicians cannot expect to acquire all necessary skills and knowledge in medical school because the science of medicine is constantly evolving and expanding exponentially. Knowledge management systems can facilitate lifelong learning. Another aim of knowledge management is to transform a health care institution into a learning organization that can generate new knowledge, create knowledge systems, and base individual and organizational actions and tools on evidence-based medicine, which, in turn, can inspire innovation.10 Knowledge management can further serve as a catalyst for a continuously learning health system by greatly accelerating knowledge discovery, translation, and dissemination.
- Reduce preventable medical errors and liability: A 2016 study revealed that medical errors cause approximately 250,000 deaths per year.11 Knowledge management systems could decrease medical errors, including those caused by adverse drug effects, limited access to relevant data or knowledge, human oversight, poor clinical decision-making, and more.4 Fewer medical errors also would result in fewer liability lawsuits.
- Reduce inefficiencies and wait times: Like other complex systems, health care institutions have interrelated players and components. Inefficiencies can create delays in care and increased costs. Knowledge management techniques allow health care institutions to study and structure organizational processes, standardize procedures, and share knowledge from successful experiences to reduce inefficiencies in the system.
- Lower health care costs: Many of the advantages of health care knowledge management would have the added advantage of lowering health care costs. Smoother collaboration, effective knowledge sharing, reduced medical errors and adverse drug events, less liability risk, and reduced inefficiencies and wait times all contribute to lower health care costs.10 Use of digital health tools and new technologies, which often are the foundation of health care knowledge management, is another way to reduce health care spending.
- Improve quality of care: The ultimate goal of a health care knowledge management system is to drive optimal outcomes in the effectiveness, efficiency, and safety of patient care. Each of the advantages discussed in this article contributes to, and is relevant only because it furthers, this goal.
How knowledge management is operationalized
Knowledge management can be operationalized in health care by using knowledge management services and knowledge creation, and using knowledge at the point of care.
Knowledge management can be operationalized in health care by using knowledge management services and knowledge creation and using knowledge at the point of care.
Knowledge management services
Knowledge is a resource, but health care knowledge also should be viewed as a service that supplies the necessary functionalities to address knowledge gaps in health care delivery. Knowledge management services can be aligned and applied to each step of the modern care delivery model. They can be broken down into three foundational categories—enabling services, care services, and transformational services—that are adaptable to most health care services. Knowledge management processes are cyclical, which means all information and knowledge gathered through each phase of patient care (or knowledge management service category) informs the progression of the next phase, working together to create a system that continues to learn, adapt, and improve.6
Enabling services are the foundational building blocks of a knowledge management service. They allow for the identification, collection, organization, and modeling of knowledge, while also working alongside tools that support access to knowledge assets. In other words, this is the platform where knowledge is created or acquired, accessed, and shared.
Care services are informed by the knowledge platform supplied by the enabling services. At this stage, health care knowledge is operationalized and used to support patients’ specific needs, driving a diagnostic-therapeutic cycle that is evidence-based and informed by data.
Transformational services drive changes informed by the data collected and care decisions made during the enabling and care phases. In the transformational phase, health care practices and hospitals can use what they have learned through the care process to define and promote cultures of knowledge-centric care delivery. Outcomes and quality metrics, research, and other patient-centric evidence collected through the cycle of health care delivery can affect clinical process, standards, and policies that allow the health care system to learn from itself, identify gaps, and improve in real-time. Transformational services evolve and improve the enabling services.
Figure 1 demonstrates how knowledge management services are linked and applied at the point of care and how the evidence gathered during each phase can be used to inform the future of health care delivery. The figure shows one example of how knowledge is gathered and applied in the health care setting, but it is important to remember that many sources beyond evidence-based sources and patient records can be used to gather knowledge. This same principle applies as you move through the care cycle, in which there are multiple ways to inform care processes beyond the assessment of quality and performance metrics, such as research, teaching, innovation, and learning health care systems.
FIGURE 1. USING KNOWLEDGE MANAGEMENT IN HEALTH CARE
Knowledge management services also can promote knowledge creation. For example, knowledge creation can begin by gathering and assembling the necessary health care knowledge from research, evidence-based resources, and so on, and applying clinical practice guidelines (CPGs), pathways, and standards of care for a given condition. Combining knowledge assets with CPGs allows the knowledge management system to disseminate the most relevant resources and/or guidelines to physicians at the points of care where they are most needed to inform decision-making and the care delivery process. Knowledge may be created (or acquired) through authoring by experts, elicitation, and translation, and knowledge synthesis such as evidence-based medicine methodologies, and/or discovery by machine learning. The emerging paradigm is a hybrid model that best leverages the advantages of each.
Explicit, detailed knowledge created for individual patients can be pooled to learn, discover, and create new higher value knowledge resulting in a true learning health care system.
In addition to providing guidance and resources, knowledge can be individualized for each patient. Knowledge is created each time information is added to the patient’s medical record. Understanding that patient information is stored in many different locations over a lifetime and shared through exchanges across all sites, maintaining the patient’s medical records will allow the full scope of a patient’s data to be collected from all possible sources. Access to the full patient record is essential to informed clinical decision-making at the point of care. To achieve this level of information capture, semantic interoperability—the ability to seamlessly exchange data that is properly interpreted by the receiver—is required to allow patient information to flow easily between health care providers, which is central to today’s team-based care models. Explicit, detailed knowledge created for individual patients can be pooled to learn, discover, and create new higher-value knowledge, resulting in a true learning health care system.
Using knowledge at the point of care
An important aspect of operationalizing knowledge management is the ability to use knowledge at the point of care. With access to a full set of patient data, the knowledge can be applied, organized, and displayed in the physician’s EHR or other interface for use at the bedside. The combined knowledge assets allow for the application of customized clinical decision support, care planning, alerts, and patient education based on the most up-to-date and relevant patient data and medical evidence all in one place.
Having all necessary data and knowledge in hand at the point of care assists in making treatment decisions and managing care without requiring the physician to access multiple systems. Knowledge management systems can catalyze the evolution to clinician user interfaces designed to align with clinician mental models and cognitive processes that enable clinical workflows. The standard mechanisms instituted by knowledge management services also allow for reliable and valid measurement of the efficiency and efficacy of patient care, furthering high-quality care.6 In addition, gathering reliable data on the quality of care allows health systems and physicians to track quality metrics to inform future guidelines, establish clinical pathways, establish standards of care, and flag undesirable outcomes.
Although health care knowledge management services provide many benefits, implementation can be a challenge. Despite its success in the business sector, knowledge management is not yet widely used in health care settings. The lack of uptake, which is in part because of a lack of awareness of the promise of knowledge management services in health care, is a foundational challenge. Establishing an appreciation of and trust in health care knowledge management systems will require commitment from health care professionals and health care administrators. One step toward this goal is the sharing of evidence of successful use of knowledge management and measured improvements in efficiency and clinical outcomes.
Implementing knowledge management services not only requires a commitment from users, but also will require a significant financial commitment from the institutions where they practice.
Implementing knowledge management services not only requires a commitment from users, but also will require a significant financial commitment from the institutions where they practice. Although health care systems may not be developing the technologies in-house, the advancement of these technologies is costly for vendors, and these expenses likely will trickle down to the users and patients. Knowledge management tools must be technically sound, and they require design and management by highly trained experts (that is, physician informaticians and specialized computer scientists) and oversight from clinical experts to ensure they provide information that is reliable and clinically valid. Once implemented in a health system, hospitals and practices must allot resources to ensure the systems are consistent with up-to-date clinical standards and customized to align with the standards instituted within their systems.
Once the knowledge management system is in place, user education is necessary and will need to continue with new iterations of the system. Without being able to demonstrate the value these systems provide, administrators may be unable to justify the financial burden, thereby slowing the uptake and general acceptance of innovative technologies.
Technical challenges, such as a lack of integration in clinical workflows and other health information technology systems, including EHRs, telemedicine, CDS, and lack of semantic standards for the exchange of patient health information, also detract from the industry’s willingness to adopt knowledge management systems. Semantic standards are agreed-upon methods for connecting systems together. Standards may pertain to security, data transport, data format or structure, or the meanings of codes or terms, and the lack of semantic standards for the exchange of patient health information is a challenge that plagues the health care industry.
Without a standard language for data sharing, digital health technologies cannot be fully realized. Integration with other health information technology also is not commonplace. As noted previously, knowledge management services are best used when data are accessed and shared across all systems that store patient information; without this integration, health care providers will be burdened with trying to coordinate care across multiple systems. Instead of siloed systems, a fully integrated platform that physicians can access with the ability to share data with knowledge management services layered throughout will be more valuable.
In addition to technology barriers, many other constraints stand in the way of increased uptake of knowledge management tools. As with any system that accesses and shares patient health information, there are concerns about how the privacy of patient data is maintained and the best safeguards for protecting patient information. Until a system can prove that patient data are safe, physicians may feel uncomfortable sharing patient data and other information.9
Knowledge management is a powerful tool to improve communication, reduce cognitive burden, increase efficiency, leverage data, and more, all with the purpose of better patient care. Frank Gilbreth—a pioneer in workflow and close friend of Ernest A. Codman, MD, FACS (who originated what today is known as outcomes reporting and transparency)—summarized the importance of management science, later known as knowledge management, by saying, “When your management becomes a science, there will result greater efficiency in you as individuals and in the great work of the hospitals to which you devote your lives.”12
The authors would like to recognize Matthew Burton, MD, vice-president of clinical informatics, Apervita, Inc. for his contribution to this article.
- U.S. Census Bureau. Quick facts. Available at: www.census.gov/quickfacts/fact/table/US/PST045219. Accessed January 15, 2021.
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- Handspicker B. The role of knowledge management in health care IT program delivery. IRIS Health Solutions. November 27, 2018. Available at: www.irishealthsolutions.com/index.php/blog/25-the-role-of-knowledge-management-in-health-care-it-program-delivery. Accessed January 19, 2021.
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- Johns Hopkins Medicine. News release. May 3, 2016. Study suggests medical errors now third leading cause of death in the U.S. Available at: www.hopkinsmedicine.org/news/media/releases/study_suggests_medical_errors_now_third_leading_cause_of_death_in_the_us. Accessed January 19, 2021.
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