Conceptual knowledge and decision strategies in relation to hypercholesterolemia and coronary heart disease

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Abstract

This paper reports on a study that examines physicians’ understanding of concepts and decision making in problems pertaining to hypercholesterolemia and coronary heart disease (CHD). The study was carried out in two phases: (1) a simulated clinical interview in which two clinical problems were presented and (2) a session in which subjects responded to a series of questions. The questions were related to the analysis of risk factors, diagnostic criteria (DC) for determining elevated lipid values, and differential diagnosis for lipid disorders. The subjects included 12 family practitioners who were randomly selected from a continuing medical education program at McGill University. The results indicate that all subjects exhibited gaps in their understanding of domain concepts. In particular, most physicians demonstrated a lack of knowledge concerning the primary genetic disorders that contribute to CHD, as well as deficiencies in understanding the secondary causes of hypercholesterolemia. The majority of subjects tended to overestimate the lipid value intervals for determining patients at high risk. Physicians had no difficulty diagnosing the first patient problem of familial hypercholesterolemia, but failed to identify the problem of elevated lipids secondary to hypothyroidism. We observed a dissociation between subjects’ conceptual understanding and their application of knowledge in solving patient problems. The implications of this work are discussed in terms of the cognitive dimensions of technologies for supporting learning and evidence-based decision making.

Introduction

It has been well documented that continuing medical education frequently fails to modify physician’s clinical behavior [1]. Innovative information technologies afford us the possibility of disseminating knowledge and enhancing the quality of physician’s decisions. However, decision making is an inherently complex cognitive process that critically depends on the availability of current information, a level of understanding and the use of appropriate decision strategies. The effectiveness of instructional aids and decision support tools is predicated on their usefulness in addressing the specific problems that lead to suboptimal decisions. In this paper, we present research pertaining to physician’s conceptual understanding and decision making related to hypercholesterolemia and coronary artery disease.

Significant advances have been made in both epidemiological research and in basic science research in understanding the risk factors involved, and the role of lipids in the genesis of atherosclerosis [2]. The etiology of coronary artery disease is multi-factorial, involving inherent or nonmodifiable risk factors, such as age and sex, and risk factors, such as cigarette smoking and cholesterol levels. Primary prevention, involving a reduction in these risk factors, can significantly lower cardiovascular mortality and may even reverse the process of coronary artery disease [2].

Although the association between cholesterol and cardiovascular disease has been recognized for many years, recent research has advanced our understanding of this relationship. In particular, the reference range of serum cholesterol levels for identifying individuals at risk have been determined with considerably greater precision. Despite the availability of newer guidelines [3], it has been observed that many laboratories and practicing physicians still refer to older reference ranges and generally, do not adhere to currently prescribed practices [4]. Evidence-based medicine is an emerging clinical discipline “that brings the best evidence from clinical and healthcare research to the bedside, to the surgery or clinic and to the community” [1]. This movement has made inroads into the evaluation, synthesis, and dissemination of high quality research findings. Although this is an essential component, it is our contention that the mere availability of information is insufficient to lead to applications of this knowledge in actual practice.

The integration of rapidly evolving biomedical research findings and clinical evidence into therapy and management of coronary heart disease (CHD) involves a number of complex cognitive issues. It has been found that physicians exhibit systematic biases regarding the assessment of cardiovascular risk [5], [6]. The root of this problem may be found in immediate access to available information, misconceptions, or faulty decision practices. This underscores the need for developing a better understanding of the cognitive processes and kinds of knowledge needed to engage in effective information gathering and decision making. In our view, the development of effective instructional and decision support tools for the practicing physician should be based on empirical research grounded in a sound theoretical and methodological framework [7].

The study of medical cognition focuses on diverse aspects of thinking in medical contexts, including investigations of clinical problem solving, diagnostic solution strategies, and decision-making in relation to therapeutics and patient management [8]. Decision making is one of the principle areas of concern in the study of medical cognition and informatics. The majority of studies in medical decision-making have involved the development of normative or prescriptive models, which are concerned with identifying courses of action, such as prescribing medication, in a manner that is consistent with expected outcomes given specific information [9]. This approach is largely based on assumptions that the decision maker is behaving rationally and is capable of choosing between alternatives in a way that maximizes decision outcomes. There have been many efforts to improve medical decision making using normative approaches. However, the use of these techniques in clinical medicine has often not resulted in sustained and generalizable improvements in physicians’ diagnostic decisions [10] or in their therapeutic intervention [11].

We have developed a cognitive framework for characterizing medical decision making [12], [13]. The objective of this framework is to describe different kinds of knowledge and reasoning strategies that support physicians' decision practices. It is useful to distinguish between three kinds of knowledge: factual, conceptual, and procedural knowledge. Factual knowledge merely reflects knowing a fact or set of facts (e.g. risk factors for coronary artery disease) without any in-depth understanding. Facts are routinely disseminated through a wide range of sources such as pamphlets, and pharmaceutical labels. The acquisition of factual knowledge alone would not necessarily lead to any increase in understanding or behavioral change. The acquisition of conceptual knowledge involves the integration of new information with prior knowledge and necessitates a deeper level of understanding. For example, risk factors may be associated in the physician’s mind with physiological and biochemical mechanisms and typical patient presentations. Conceptual understanding can support explanation and may result in appropriate actions. Procedural knowledge is a kind of knowing related to how to perform various activities. Decision rules, as represented in clinical guidelines, embody a kind of procedural knowledge. Heuristics and decision strategies are also forms of procedural knowledge.

Conceptual knowledge may not necessarily be tightly integrated with procedural knowledge. For example, a physician may demonstrate a certain understanding of specific concepts, but may use decision strategies that are inconsistent with this knowledge. Conversely, a physician may take the appropriate actions or decisions without conceptual understanding [14]. This dissociation may reflect correct performance without articulated knowledge or alternatively, accurate knowledge followed by inappropriate action. This decoupling of knowledge and action has been documented in several studies of medical decision making. Poses, Randall, and Wigton [11] found that teaching physicians how to improve their estimates of disease probabilities in regard to streptococcal pharyngitis did not affect their treatment decisions. Elstein et al. [15] found that physicians’ beliefs and understanding of hormonal replacement therapy was not predictive of the kinds of the decisions that they made when presented with related clinical cases.

Procedural and conceptual knowledge are fostered via different learning experiences. For example, continued adherence to a set of clinical guidelines would likely lead to a change in procedural knowledge. After a period of using these guidelines, a physician would be able to internalize the decision alternatives and follow appropriate decision strategies without explicit use of the guidelines. The acquisition of conceptual knowledge necessitates mindful engagement involving reflection and discourse with peers through various forums such as seminars, medical rounds, and continuing medical education. In addition, many computer-based learning environments are developed with the objective of fostering conceptual knowledge. Diverse forms of knowledge have specific effects on medical decision-making and their characterization is necessary for explaining variations in clinical practice. Furthermore, these considerations are important when developing decision support and instructional interventions to enhance decision making performance.

The principal thrust of evidence-based medicine is on the dissemination of cutting-edge clinical evidence in order to improve decision-making practices. In this context, evidence is seen as objective units of information that can be readily acted on. However, the availability of evidence does not guarantee that it will be applied in a given decision-making context. Evidence is invariably perceived evidence in the physician’s mind. There is a substantial body of research that indicates that when evidence is contrary to one’s prior beliefs or practices, it can be easily disregarded, discounted or re-interpreted to fit with one’s prior conceptions [16]. Evidence may be perceived as a set of facts added to the large arsenal of facts in the physician’s knowledge base. Ideally, evidence can be integrated into a physician’s knowledge base and result in genuine conceptual change (i.e. leading to a better understanding of the problem). Evidence may also have the effect of changing procedural knowledge. For example, if a physician was presented with findings indicating that change in diet was no longer sufficient to control cholesterol levels in the range of 4.5–5.2 mmol/l, he or she may prescribe medication with greater frequency for patients in that range. In our view, evidence that can be both understood (conceptual knowledge) and translated into action (procedural knowledge) is most likely to have a significant and sustained effect on behavior.

The work presented in this paper is part of a research program, which endeavors to combine studies of medical cognition with work in the design, development, and evaluation of medical technologies [7]. These systems include computerized patient records [17], decision support tools [13], and educational technologies [14]. The studies of medical cognition include investigations of diagnostic reasoning, therapeutic decision making and the effects of teaching on practice. The objectives of the program are to: (a) further our understanding of physician’s domain knowledge and information needs; (b) examine use of evidence in decision-making; and (c) to facilitate the development of information resources (including decision tools, educational systems, and guidelines) based on such understanding. In our research, there is an emphasis on both the individual subject and on group responses. The approach is typically to conduct in-depth investigations of each subject’s behavior.

The specific goals of this investigation were to characterize physicians’: (1) understanding of concepts, facts, and principles pertaining to coronary heart disease and hypercholesterolemia; (2) their information gathering, evaluation of evidence, and decision-making when dealing with various types of related clinical problems; and (3) the extent to which their understanding and beliefs correlate with their decision-making. The study was carried out in two phases: (1) a simulated clinical interview in which two clinical problems were presented; and (2) session in which subjects responded to a series of questions. The questions were related to the analysis of risk factors, diagnostic criteria (DC) for determining elevated lipid values, and differential diagnosis for lipid disorders. This research was carried out as part of an initiative to develop and assess a multi-media tutorial and decision support tool related to hypercholesterolemia and coronary artery disease for family physicians and general practitioners [18], [19].

Section snippets

Subjects

The first study included 12 general practitioners who participated in the Continuing Medical Education Program at McGill University. The physicians worked mostly in private practice. Each of the physicians had been practicing medicine for a minimum of 10 years, with a range of 10–27 years in practice. Two fourth-year students were included for the purposes of comparisons. The interviews took place at the physicians’ offices or at the Center for Medical Education at McGill University, according

Results

The first part of the results section presents findings pertaining to the patient problems for case 1 and case 2. The second part of this section is devoted to analysis of physicians’ responses to questions.

Conclusions

Biomedical research has continued to provide physicians with great advances in knowledge pertaining to etiology, diagnosis, treatment, and management of chronic diseases such as CHD and hypercholesterolemia. For example, we can determine the reference range for patients at risk with considerable greater precision. In addition, there are a host of treatment options that can significantly improve health care. Yet it is widely believed that many patients continue to receive suboptimal care [4].

Acknowledgements

The research was supported in part by a grant from Merck Frosst and an award from the Health Evidence and Application Linkages Network (HEALNET), Canadian Network of Centres of Excellence program to Vimla Patel. We would like thank James Cimino, and Richard and Sylvia Cruess for their comments on an earlier version of this paper. We also appreciate the comments offered by two anonymous reviewers.

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