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      Improving diagnosis by improving education: a policy brief on education in healthcare professions

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          Abstract

          Diagnostic error is increasingly recognized as a major patient safety concern. Efforts to improve diagnosis have largely focused on safety and quality improvement initiatives that patients, providers, and health care organizations can take to improve the diagnostic process and its outcomes. This educational policy brief presents an alternative strategy for improving diagnosis, centered on future healthcare providers, to improve the education and training of clinicians in every health care profession. The hypothesis is that we can improve diagnosis by improving education. A literature search was first conducted to understand the relationship of education and training to diagnosis and diagnostic error in different health care professions. Based on the findings from this search we present the justification for focusing on education and training, recommendations for specific content that should be incorporated to improve diagnosis, and recommendations on educational approaches that should be used. Using an iterative, consensus-based process, we then developed a driver diagram that categorizes the key content into five areas. Learners should: 1) Acquire and effectively use a relevant knowledge base, 2) Optimize clinical reasoning to reduce cognitive error, 3) Understand system-related aspects of care, 4) Effectively engage patients and the diagnostic team, and 5) Acquire appropriate perspectives and attitudes about diagnosis. These domains echo recommendations in the National Academy of Medicine’s report Improving Diagnosis in Health Care. The National Academy report suggests that true interprofessional education and training, incorporating recent advances in understanding diagnostic error, and improving clinical reasoning and other aspects of education, can ultimately improve diagnosis by improving the knowledge, skills, and attitudes of all health care professionals.

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          Most cited references44

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          Entrustability of professional activities and competency-based training.

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            Research in clinical reasoning: past history and current trends.

            Research in clinical reasoning has been conducted for over 30 years. Throughout this time there have been a number of identifiable trends in methodology and theory. This paper identifies three broad research traditions, ordered chronologically, are: (a) attempts to understand reasoning as a general skill--the "clinical reasoning" process; (b) research based on probes of memory--reasoning related to the amount of knowledge and memory; and (c) research related to different kinds of mental representations--semantic qualifiers, scripts, schemas and exemplars. Several broad themes emerge from this review. First, there is little evidence that reasoning can be characterised in terms of general process variables. Secondly, it is evident that expertise is associated, not with a single basic representation but with multiple coordinated representations in memory, from causal mechanisms to prior examples. Different representations may be utilised in different circumstances, but little is known about the characteristics of a particular situation that led to a change in strategy. It becomes evident that expertise lies in the availability of multiple representations of knowledge. Perhaps the most critical aspect of learning is not the acquisition of a particular strategy or skill, nor is it the availability of a particular kind of knowledge. Rather, the critical element may be deliberate practice with multiple examples which, on the hand, facilitates the availability of concepts and conceptual knowledge (i.e. transfer) and, on the other hand, adds to a storehouse of already solved problems.
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              Is Open Access

              The frequency of diagnostic errors in outpatient care: estimations from three large observational studies involving US adult populations

              Background The frequency of outpatient diagnostic errors is challenging to determine due to varying error definitions and the need to review data across multiple providers and care settings over time. We estimated the frequency of diagnostic errors in the US adult population by synthesising data from three previous studies of clinic-based populations that used conceptually similar definitions of diagnostic error. Methods Data sources included two previous studies that used electronic triggers, or algorithms, to detect unusual patterns of return visits after an initial primary care visit or lack of follow-up of abnormal clinical findings related to colorectal cancer, both suggestive of diagnostic errors. A third study examined consecutive cases of lung cancer. In all three studies, diagnostic errors were confirmed through chart review and defined as missed opportunities to make a timely or correct diagnosis based on available evidence. We extrapolated the frequency of diagnostic error obtained from our studies to the US adult population, using the primary care study to estimate rates of diagnostic error for acute conditions (and exacerbations of existing conditions) and the two cancer studies to conservatively estimate rates of missed diagnosis of colorectal and lung cancer (as proxies for other serious chronic conditions). Results Combining estimates from the three studies yielded a rate of outpatient diagnostic errors of 5.08%, or approximately 12 million US adults every year. Based upon previous work, we estimate that about half of these errors could potentially be harmful. Conclusions Our population-based estimate suggests that diagnostic errors affect at least 1 in 20 US adults. This foundational evidence should encourage policymakers, healthcare organisations and researchers to start measuring and reducing diagnostic errors.
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                Author and article information

                Journal
                Diagnosis
                Walter de Gruyter GmbH
                2194-802X
                2194-8011
                September 25 2018
                September 25 2018
                : 5
                : 3
                : 107-118
                Article
                10.1515/dx-2018-0033
                30145580
                cce0ddcd-b5c1-4183-92e4-0690c6505c93
                © 2018
                History

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