Patient safety strategies targeted at diagnostic errors: A systematic review
ABSTRACT Missed, delayed, or incorrect diagnosis can lead to inappropriate patient care, poor patient outcomes, and increased cost. This systematic review analyzed evaluations of interventions to prevent diagnostic errors. Searches used MEDLINE (1966 to October 2012), the Agency for Healthcare Research and Quality's Patient Safety Network, bibliographies, and prior systematic reviews. Studies that evaluated any intervention to decrease diagnostic errors in any clinical setting and with any study design were eligible, provided that they addressed a patient-related outcome. Two independent reviewers extracted study data and rated study quality.There were 109 studies that addressed 1 or more intervention categories: personnel changes (n = 6), educational interventions (n = 11), technique (n = 23), structured process changes (n = 27), technology-based systems interventions (n = 32), and review methods (n = 38). Of 14 randomized trials, which were rated as having mostly low to moderate risk of bias, 11 reported interventions that reduced diagnostic errors. Evidence seemed strongest for technology-based systems (for example, text message alerting) and specific techniques (for example, testing equipment adaptations). Studies provided no information on harms, cost, or contextual application of interventions. Overall, the review showed a growing field of diagnostic error research and categorized and identified promising interventions that warrant evaluation in large studies across diverse settings.
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- "Delayed cancer diagnosis is one of the most common, harmful and costly types of diagnostic error in ambulatory care settings (Gandhi et al, 2006; Singh et al, 2009, 2010). A recent systematic review of patient safety strategies targeted at reducing diagnostic errors by primary care clinicians found the strongest evidence for technology-based interventions such as computer-assisted diagnostic aids, decision support algorithms, text messages and pager alerts and adaptations to testing equipment (McDonald et al, 2013). In this study, we explore the feasibility of implementing a risk assessment tool that applies the 'QCancer' cancer risk prediction model in general practice (Hippisley-Cox and Coupland, 2013a,c). "
ABSTRACT: Background:Reducing diagnostic delays in primary care by improving the assessment of symptoms associated with cancer could have significant impacts on cancer outcomes. Symptom risk assessment tools could improve the diagnostic assessment of patients with symptoms suggestive of cancer in primary care. We aimed to explore the use of a cancer risk tool, which implements the QCancer model, in consultations and its potential impact on clinical decision making.Methods:We implemented an exploratory 'action design' method with 15 general practitioners (GPs) from Victoria, Australia. General practitioners applied the risk tool in simulated consultations, conducted semi-structured interviews based on the normalisation process theory and explored issues relating to implementation of the tool.Results:The risk tool was perceived as being potentially useful for patients with complex histories. More experienced GPs were distrustful of the risk output, especially when it conflicted with their clinical judgement. Variable interpretation of symptoms meant that there was significant variation in risk assessment. When a risk output was high, GPs were confronted with numerical risk outputs creating challenges in consultation.Conclusions:Significant barriers to implementing electronic cancer risk assessment tools in consultation could limit their uptake. These relate not only to the design and integration of the tool but also to variation in interpretation of clinical histories, and therefore variable risk outputs and strong beliefs in personal clinical intuition.British Journal of Cancer advance online publication, 3 March 2015; doi:10.1038/bjc.2015.46 www.bjcancer.com.British Journal of Cancer 03/2015; 112. DOI:10.1038/bjc.2015.46 · 4.82 Impact Factor
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- "Missed, delayed or incorrect diagnoses are considered to be diagnostic errors . Although the incidence of diagnostic error is difficult to establish , it is estimated to be between 5% and 20% , depending on the medical speciality analysed. "
ABSTRACT: Background Missed, delayed or incorrect diagnoses are considered to be diagnostic errors. The aim of this paper is to describe the methodology of a study to analyse cognitive aspects of the process by which primary care (PC) physicians diagnose dyspnoea. It examines the possible links between the use of heuristics, suboptimal cognitive acts and diagnostic errors, using Reason’s taxonomy of human error (slips, lapses, mistakes and violations). The influence of situational factors (professional experience, perceived overwork and fatigue) is also analysed. Methods Cohort study of new episodes of dyspnoea in patients receiving care from family physicians and residents at PC centres in Granada (Spain). With an initial expected diagnostic error rate of 20%, and a sampling error of 3%, 384 episodes of dyspnoea are calculated to be required. In addition to filling out the electronic medical record of the patients attended, each physician fills out 2 specially designed questionnaires about the diagnostic process performed in each case of dyspnoea. The first questionnaire includes questions on the physician’s initial diagnostic impression, the 3 most likely diagnoses (in order of likelihood), and the diagnosis reached after the initial medical history and physical examination. It also includes items on the physicians’ perceived overwork and fatigue during patient care. The second questionnaire records the confirmed diagnosis once it is reached. The complete diagnostic process is peer-reviewed to identify and classify the diagnostic errors. The possible use of heuristics of representativeness, availability, and anchoring and adjustment in each diagnostic process is also analysed. Each audit is reviewed with the physician responsible for the diagnostic process. Finally, logistic regression models are used to determine if there are differences in the diagnostic error variables based on the heuristics identified. Discussion This work sets out a new approach to studying the diagnostic decision-making process in PC, taking advantage of new technologies which allow immediate recording of the decision-making process.BMC Family Practice 05/2014; 15(1):92. DOI:10.1186/1471-2296-15-92 · 1.74 Impact Factor
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- "A recent systematic review evaluated the effects of patient safety strategies that focused on diagnostic error and found that only few strategies had an effect in terms of diagnostic error reduction or reduction of patient harm.34 While this review identified over 100 studies that tested the effects of interventions on the diagnostic process, two other recent narrative reviews showed that there are a large number of interventions that have been developed to reduce diagnostic errors, but have not been yet tested for their effectiveness. "
ABSTRACT: Diagnostic errors remain an underemphasised and understudied area of patient safety research. We briefly summarise the methods that have been used to conduct research on epidemiology, contributing factors and interventions related to diagnostic error and outline directions for future research. Research methods that have studied epidemiology of diagnostic error provide some estimate on diagnostic error rates. However, there appears to be a large variability in the reported rates due to the heterogeneity of definitions and study methods used. Thus, future methods should focus on obtaining more precise estimates in different settings of care. This would lay the foundation for measuring error rates over time to evaluate improvements. Research methods have studied contributing factors for diagnostic error in both naturalistic and experimental settings. Both approaches have revealed important and complementary information. Newer conceptual models from outside healthcare are needed to advance the depth and rigour of analysis of systems and cognitive insights of causes of error. While the literature has suggested many potentially fruitful interventions for reducing diagnostic errors, most have not been systematically evaluated and/or widely implemented in practice. Research is needed to study promising intervention areas such as enhanced patient involvement in diagnosis, improving diagnosis through the use of electronic tools and identification and reduction of specific diagnostic process 'pitfalls' (eg, failure to conduct appropriate diagnostic evaluation of a breast lump after a 'normal' mammogram). The last decade of research on diagnostic error has made promising steps and laid a foundation for more rigorous methods to advance the field.BMJ quality & safety 08/2013; 22(Suppl 2). DOI:10.1136/bmjqs-2012-001624 · 3.28 Impact Factor