Summary points
What was
Since the Institute of Medicine's release of “To Err is Human: Building a Safer Health System” in 1999 [1] and “Crossing the Quality Chasm: A New Health System for the 21st Century” in 2001 [2], there has been increasing pressure on everyone from healthcare providers working in solo practices to large nationwide, healthcare delivery networks to implement state of the art clinical information systems. Recent reports have reiterated the fact that, for these clinical information systems to deliver their expected improvements in quality, they must be equipped with state of the art, real-time, point-of-care, clinical decision support (CDS) features [3]. Unfortunately, the successful design, development, implementation, maintenance and evaluation of these advanced clinical decision support features is in itself a complex undertaking that is not well understood [4]. These advanced clinical decision support systems generally depend on large knowledge bases of clinical knowledge. For example, a drug–drug interaction checker requires a database of drug names and their interactions. This database must be kept up-to-date as new drugs become available, as new drug interactions become known and as our understanding of existing interactions evolves. Manual systems can be used for this task when the amount of clinical knowledge to manage is small (i.e., less than 100 interactions), but as the size of these databases grows, clinical knowledge management (CKM) tools become necessary to ensure that these clinical knowledge bases are correct, consistent, complete and current. In fact, the area of research and development referred to as “clinical knowledge management” will soon become vitally important as organizations struggle to develop, implement, maintain, and evaluate their clinical decision support efforts.
The need for high quality, collaborative, CKM practices is often overlooked even in the most advanced healthcare organizations [5]. The need to develop high quality, evidence-based CDS interventions, coupled with the need to obtain widespread, peer review of this work, makes the use of an Internet-based, collaborative, CKM tool almost mandatory. Moreover, this clinical content must be kept up to date as the existing knowledge changes, new clinical knowledge is gained, and underlying changes take place in the clinical information system [6]. This places enormous burdens on the informaticians responsible for maintaining all of the clinical applications that rely on this knowledge including: computer-based provider order entry (CPOE), clinical results review, clinical documentation, and medication administration systems, for example.
In a recent article, we identified “disseminate best practices in Clinical Decision Support (CDS) design, development, and implementation” as one of the “grand challenges” in CDS [7]. A key component of any CDS initiative is how the organization develops, disseminates, maintains, and evaluates its clinical knowledge content, or its clinical knowledge management practices [8].
In an attempt to explore the current state of the art in CKM, we developed an extensive survey of potential CKM tools and techniques (see Appendix A). This manuscript describes the content of the CKM survey and reports our initial findings from administering it to a convenience sample of six organizations with substantial experience in the development and use of advanced clinical information systems with state-of-the-art, real-time, clinical decision support systems.
We developed a survey of clinical knowledge management tools and techniques, which we call the clinical knowledge management inventory, based on our extensive review of the CPOE and CDS-related literature (see [9], [10] for links to an online bibliography of these two domains), interviews with experts and our own experiences in working in the field for several decades. Please see Table 2 for a list of questions.
We identified six geographically (2 Northwest, 2 Midwest, 1 Southwest, and 1
We have divided the results into three sections. In the first section, we present characterizations of the six organizations’ use of CPOE, various CDS intervention types, and their clinical knowledge management activities. The second section describes the content of the CKM site inventory including: (1) an overview of the CKM tools we identified as keys to success and (2) questions we asked at each site to help us better understand current practices in clinical knowledge. In the third section,
We identified a variety of tools and current practices for CKM. After reviewing all of the responses to our survey and discussing the summarization of the data, we have identified the following tools and practices as the most widely used in organizations with successful CPOE and CDS implementations:
A multidisciplinary team responsible for creating and maintaining the clinical content.
An external repository of clinical content with web-based viewer that allows anyone to review it.
An online,
Clearly this study represents only a small sample of all organizations involved in clinical decision support and hence clinical knowledge management activities. The next steps are to conduct a similar survey across a wider range of institutions. Then, if these currently identified practices are shown to be widespread and useful, it would be interesting to attempt to carry out a series of clinical trials to assess the impact of the use of these tools and techniques on the overall success of an
The field of CKM is in its infancy, yet holds great promise. Even within organizations that have been successfully using CPOE with advanced CDS features for well over 15 years, we did not find any site that was using all of the practices in CKM that we identified. If we are to speed progress in the area of clinical decision support, we must continue to develop and refine our understanding, implementation and use of advanced clinical knowledge management capabilities. Summary points What was
This work was funded in part by NLM Research Grant R56-LM006942 and AHRQ Contract HHHSA29020080010. The sponsors were not involved in the design, conduct or analysis of the study, or in the preparation of this manuscript.