Use of Reflective Practice to Increase Diagnostic Accuracy

2016 ◽  
Vol 5 (1) ◽  
pp. 134-139
Author(s):  
Martin Caliendo ◽  
Joanna Abraham
Keyword(s):  
Diagnostic Accuracy ◽  
Reflective Practice ◽  
Patient Outcomes ◽  
Evaluation Studies ◽  
Diagnostic Errors ◽  
Empirical Support ◽  
Diagnostic Error ◽  
Future Research ◽  
Information Synthesis ◽  
Methodological Foundation

Diagnostic error accounts for up to 17 percent of all adverse patient outcomes. Cognitive errors, in particular faulty information synthesis, accounts for the majority of these diagnostic errors. Reflective practice is reported as a strategy to improve diagnostic accuracy. The theoretic foundation to use reflective practice to decrease diagnostic error is well developed; however, empirical support is lacking and inconsistent. To address this gap, the author conducted an integrative review to critically evaluate the evidence in support of intervention for training in reflective practice to improve the diagnostic accuracy of clinicians’ decision making. We discuss our findings on the analytical, theoretical and methodological foundation of current evaluation studies on training in reflective practice patterns, in addition to identifying gaps in knowledge that will guide potential areas for future research.

scholarly journals ED misdiagnosis of cerebrovascular events in the era of modern neuroimaging

Neurology ◽  
2017 ◽  
Vol 88 (15) ◽  
pp. 1468-1477 ◽  
Author(s):  
Alexander Andrea Tarnutzer ◽  
Seung-Han Lee ◽  
Karen A. Robinson ◽  
Zheyu Wang ◽  
Jonathan A. Edlow ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Diagnostic Accuracy ◽  
Clinical Presentation ◽  
False Negative ◽  
False Negative Rate ◽  
Diagnostic Errors ◽  
Risk Of Bias ◽  
Future Research ◽  
Negative Rate ◽  
Cerebrovascular Events

Objective:With the emergency department (ED) being a high-risk site for diagnostic errors, we sought to estimate ED diagnostic accuracy for identifying acute cerebrovascular events.Methods:MEDLINE and Embase were searched for studies (1995–2016) reporting ED diagnostic accuracy for ischemic stroke, TIA, or subarachnoid hemorrhage (SAH). Two independent reviewers determined inclusion. We identified 1,693 unique citations, examined 214 full articles, and analyzed 23 studies. Studies were rated on risk of bias (QUADAS-2). Diagnostic data were extracted. We prospectively defined clinical presentation subgroups to compare odds of misdiagnosis.Results:Included studies reported on 15,721 patients. Studies were at low risk of bias. Overall sensitivity (91.3% [95% confidence interval (CI) 90.7–92.0]) and specificity (92.7% [91.7–93.7]) for a cerebrovascular etiology was high, but there was significant variation based on clinical presentation. Misdiagnosis was more frequent among subgroups with milder (SAH with normal vs abnormal mental state; false-negative rate 23.8% vs 4.2%, odds ratio [OR] 7.03 [4.80–10.31]), nonspecific (dizziness vs motor findings; false-negative rate 39.4% vs 4.4%, OR 14.22 [9.76–20.74]), or transient (TIA vs ischemic stroke; false discovery rate 59.7% vs 11.7%, OR 11.21 [6.66–18.89]) symptoms.Conclusions:Roughly 9% of cerebrovascular events are missed at initial ED presentation. Risk of misdiagnosis is much greater when presenting neurologic complaints are mild, nonspecific, or transient (range 24%–60%). This difference suggests that many misdiagnoses relate to symptom-specific factors. Future research should emphasize studying causes and designing error-reduction strategies in symptom-specific subgroups at greatest risk of misdiagnosis.

Methodologies for evaluating strategies to reduce diagnostic error: report from the research summit at the 7th International Diagnostic Error in Medicine Conference

Diagnosis ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Beau B. Bruce ◽  
Robert El-Kareh ◽  
John W. Ely ◽  
Michael H. Kanter ◽  
Goutham Rao ◽  
...  
Keyword(s):  
Randomized Clinical Trials ◽  
Diagnostic Errors ◽  
Interrupted Time Series ◽  
Diagnostic Error ◽  
Current Evidence ◽  
Future Research ◽  
Error Mitigation ◽  
Safety Research ◽  
Diagnostic Research ◽  
Cluster Randomized

AbstractIn this article we review current evidence on strategies to evaluate diagnostic error solutions, discuss the methodological challenges that exist in investigating the value of these strategies in patient care, and provide recommendations for methods that can be applied in investigating potential solutions to diagnostic errors. These recommendations were developed iteratively by the authors based upon initial discussions held during the Research Summit of the 7th Annual Diagnostic Error in Medicine Conference in September 2014. The recommendations include the following elements for designing studies of diagnostic research solutions: (1) Select direct and indirect outcomes measures of importance to patients, while also practical for the particular solution; (2) Develop a clearly-stated logic model for the solution to be tested; (3) Use rapid, iterative prototyping in the early phases of solution testing; (4) Use cluster-randomized clinical trials where feasible; (5) Avoid simple pre-post designs, in favor of stepped wedge and interrupted time series; (6) Leverage best practices for patient safety research and engage experts from relevant domains; and (7) Consider sources of bias and design studies and their analyses to minimize selection and information bias and control for confounding. Areas of diagnostic error mitigation research identified for further attention include: role of competing diagnoses, understanding the impacts of organizational culture, timing of diagnosis, and sequencing of research studies. Future research will likely require novel clinical, health services, and qualitative research methods to address the age-old problem of arriving at an accurate diagnosis.

Feasibility of patient-reported diagnostic errors following emergency department discharge: a pilot study

Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Kelly T. Gleason ◽  
Susan Peterson ◽  
Cheryl R. Dennison Himmelfarb ◽  
Mariel Villanueva ◽  
Taylor Wynn ◽  
...  
Keyword(s):  
Emergency Department ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Health Concern ◽  
Future Research ◽  
Clinical Predictors ◽  
Patient Reported ◽  
Patient’S Experience ◽  
Emergency Department Discharge ◽  
Measured Response

AbstractObjectivesThe National Academy of Medicine identified diagnostic error as a pressing public health concern and defined failure to effectively communicate the diagnosis to patients as a diagnostic error. Leveraging Patient’s Experience to improve Diagnosis (LEAPED) is a new program for measuring patient-reported diagnostic error. As a first step, we sought to assess the feasibility of using LEAPED after emergency department (ED) discharge.MethodsWe deployed LEAPED using a cohort design at three EDs within one academic health system. We enrolled 59 patients after ED discharge and queried them about their health status and understanding of the explanation for their health problems at 2-weeks, 1-month, and 3-months. We measured response rates and demographic/clinical predictors of patient uptake of LEAPED.ResultsOf those enrolled (n=59), 90% (n=53) responded to the 2-week post-ED discharge questionnaire (1 and 3-month ongoing). Of the six non-responders, one died and three were hospitalized at two weeks. The average age was 50 years (SD 16) and 64% were female; 53% were white and 41% were black. Over a fifth (23%) reported they were not given an explanation of their health problem on leaving the ED, and of those, a fourth (25%) did not have an understanding of what next steps to take after leaving the ED.ConclusionsPatient uptake of LEAPED was high, suggesting that patient-report may be a feasible method of evaluating the effectiveness of diagnostic communication to patients though further testing in a broader patient population is essential. Future research should determine if LEAPED yields important insights into the quality and safety of diagnostic care.

SAFER PRACTICES: reducing the risk of diagnostic errors

2020 ◽  
Vol 31 (2) ◽  
pp. 80-86 ◽  
Author(s):  
Paul Silverston
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Critical Thinking ◽  
Reflective Practice ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Practice Nurses

Diagnostic errors are relatively common in general practice. Paul Silverston describes a mnemonic-based system to prevent and detect these errors Diagnostic errors in primary care are relatively common and they have the potential to cause serious harm to patients. Up to 80% of these errors are believed to be preventable. This article describes a mnemonic-based system that practice nurses can use to prevent diagnostic errors from arising, as well as to detect these errors when they occur. The mnemonic is designed to be used pre-consultation to reduce the risk of errors arising through better preparation; during the consultation, as a diagnostic error checklist; and after the consultation to encourage reflective practice and critical thinking.

scholarly journals ‘Immunising’ physicians against availability bias in diagnostic reasoning: a randomised controlled experiment

2020 ◽  
Vol 29 (7) ◽  
pp. 550-559 ◽  
Author(s):  
Sílvia Mamede ◽  
Marco Antonio de Carvalho-Filho ◽  
Rosa Malena Delbone de Faria ◽  
Daniel Franci ◽  
Maria do Patrocinio Tenorio Nunes ◽  
...  
Keyword(s):  
Inflammatory Bowel Disease ◽  
Diagnostic Accuracy ◽  
Bowel Disease ◽  
Performance Test ◽  
Phase 1 ◽  
Diagnostic Errors ◽  
Future Research ◽  
Chronic Diarrhoea ◽  
Availability Bias ◽  
Inflammatory Bowel

BackgroundDiagnostic errors have often been attributed to biases in physicians’ reasoning. Interventions to ‘immunise’ physicians against bias have focused on improving reasoning processes and have largely failed.ObjectiveTo investigate the effect of increasing physicians’ relevant knowledge on their susceptibility to availability bias.Design, settings and participantsThree-phase multicentre randomised experiment with second-year internal medicine residents from eight teaching hospitals in Brazil.InterventionsImmunisation: Physicians diagnosed one of two sets of vignettes (either diseases associated with chronic diarrhoea or with jaundice) and compared/contrasted alternative diagnoses with feedback. Biasing phase (1 week later): Physicians were biased towards either inflammatory bowel disease or viral hepatitis. Diagnostic performance test: All physicians diagnosed three vignettes resembling inflammatory bowel disease, three resembling hepatitis (however, all with different diagnoses). Physicians who increased their knowledge of either chronic diarrhoea or jaundice 1 week earlier were expected to resist the bias attempt.Main outcome measurementsDiagnostic accuracy, measured by test score (range 0–1), computed for subjected-to-bias and not-subjected-to-bias vignettes diagnosed by immunised and not-immunised physicians.ResultsNinety-one residents participated in the experiment. Diagnostic accuracy differed on subjected-to-bias vignettes, with immunised physicians performing better than non-immunised physicians (0.40 vs 0.24; difference in accuracy 0.16 (95% CI 0.05 to 0.27); p=0.004), but not on not-subjected-to-bias vignettes (0.36 vs 0.41; difference −0.05 (95% CI −0.17 to 0.08); p=0.45). Bias only hampered non-immunised physicians, who performed worse on subjected-to-bias than not-subjected-to-bias vignettes (difference −0.17 (95% CI −0.28 to −0.05); p=0.005); immunised physicians’ accuracy did not differ (p=0.56).ConclusionsAn intervention directed at increasing knowledge of clinical findings that discriminate between similar-looking diseases decreased physicians’ susceptibility to availability bias, reducing diagnostic errors, in a simulated setting. Future research needs to examine the degree to which the intervention benefits other disease clusters and performance in clinical practice.Trial registration number68745917.1.1001.0068.

Diagnostic Accuracy & Pathology Revised Reports: Evidence-Based Guideline Development

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S124-S124
Author(s):  
A Spiczka ◽  
L Waibel ◽  
E Garcia ◽  
I Kundu ◽  
R Garris ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Patient Care ◽  
Patient Outcomes ◽  
Guideline Development ◽  
Treatment Plan ◽  
Clinical Care ◽  
Diagnostic Errors ◽  
Care Providers ◽  
Snowball Sampling ◽  
Diagnostic Discrepancies

Abstract Introduction/Objective Diagnostic errors in pathology may have adverse impact on patient outcomes and are often rectified through revised reports (RR). Improving patient outcomes with accurate RR is a tangible yet challenging benefit to assuring continuous quality improvement (CQI). Assessment and elevation of RR optimization requires counterbalance of workflow complexity in the diagnostic reporting domain. Implications inform best-practice guidelines for pathology RR and exemplify improved patient outcomes by driving down negative impacts from diagnostic errors. Methods A “Survey for RR in Pathology: Reality & Best Practices” was sent via email to relevant stakeholders. The 8-item survey was designed by the National Pathology Quality Registry team & ASCP’s Institute for Science, Technology & Policy. The model included quantitative and qualitative feedback to probe current experiences with RR. The survey was open April 1-30, 2019, via Key Survey and used snowball sampling. Results Key results illuminate necessity for RR standardization. Survey findings represent 172 respondents. Ninety- two percent of respondents indicated report accuracy as a major indication for optimizing RR practices & positively impacting patient care. Pathology practices assure appropriate RR by notifying a care provider when a change in diagnosis necessitates RR (89%) & 86% of respondents indicate delineation of RR types (e.g. addenda, amendment). Still 54% of respondents see inappropriate RR use with lack of notification to care providers and 48% indicate no delineation of RR types. This balance-counterbalance highlights deviations from optimized RR and a need for guidelines. Effects on patient care or impact to a patient’s treatment plan was indicated by 43% who affirmed stratification of diagnostic discrepancies as major vs. minor. Solely focusing on changes in diagnosis (benign vs. malignant) was heralded by 19% of respondents as a reason to categorize diagnostic discrepancies. Forty-two percent of respondents indicate data-driven CQI in the RR domain. Conclusion Identified RR practice gaps decrease diagnostic accuracy, confirming the need for optimal RR guidelines. RR guidelines should focus on standardized nomenclature; active dialogue between laboratory team & clinical care partners; streamlined workflows to assure accuracy; & valuing transparency to derive improved patient outcomes based on high-quality diagnostic pathology RR.

scholarly journals A human factor event-based learning assessment tool for assessment of errors and diagnostic accuracy in histopathology and cytopathology

2020 ◽  
Vol 73 (10) ◽  
pp. 681-685
Author(s):  
David Nigel Poller ◽  
Massimo Bongiovanni ◽  
Beatrix Cochand-Priollet ◽  
Sarah J Johnson ◽  
Miguel Perez-Machado
Keyword(s):  
Diagnostic Accuracy ◽  
Human Factor ◽  
Assessment Tool ◽  
Aerospace Industry ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Review Article ◽  
Learning Assessment ◽  
Dirty Dozen ◽  
Event Based

This review article summarises systems for categorisation of diagnostic errors in pathology and cytology with regard to diagnostic accuracy and the published information on human factors (HFs) in pathology to date. A 12-point event-based checklist for errors of diagnostic accuracy in histopathology and cytopathology is proposed derived from Dupont’s ‘Dirty Dozen’ HF checklist, as used in the aerospace industry for aircraft maintenance. This HF checklist comprises 12 HFs; (1) Failure of communication. (2) Complacency. (3) Lack of knowledge. (4) Distractions. (5) Lack of teamwork. (6) Fatigue. (7) Lack of resources. (8) Pressure. (9) Lack of assertiveness. (10) Stress. (11) Norms. (12) Lack of awareness. The accompanying article explains practical examples of how each of these 12 HFs may cause errors in diagnostic accuracy in pathology. This checklist could be used as a template for analysis of accuracy and risk of diagnostic error in pathology either retrospectively ‘after the event’ or prospectively at the time of diagnosis. There is a need for further evaluation and validation of this proposed 12-point HF checklist and similar systems for categorisation of diagnostic errors and diagnostic accuracy in pathology based on HF principles.

Identifying trigger concepts to screen emergency department visits for diagnostic errors

Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Prashant Mahajan ◽  
Chih-Wen Pai ◽  
Karen S. Cosby ◽  
Cynthia J. Mollen ◽  
Kathy N. Shaw ◽  
...  
Keyword(s):  
Emergency Department ◽  
Expert Panel ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Emergency Department Visits ◽  
Therapeutic Interventions ◽  
Diagnostic Process ◽  
Future Research ◽  
Office Referrals ◽  
Vital Component

AbstractObjectivesThe diagnostic process is a vital component of safe and effective emergency department (ED) care. There are no standardized methods for identifying or reliably monitoring diagnostic errors in the ED, impeding efforts to enhance diagnostic safety. We sought to identify trigger concepts to screen ED records for diagnostic errors and describe how they can be used as a measurement strategy to identify and reduce preventable diagnostic harm.MethodsWe conducted a literature review and surveyed ED directors to compile a list of potential electronic health record (EHR) trigger (e-triggers) and non-EHR based concepts. We convened a multidisciplinary expert panel to build consensus on trigger concepts to identify and reduce preventable diagnostic harm in the ED.ResultsSix e-trigger and five non-EHR based concepts were selected by the expert panel. E-trigger concepts included: unscheduled ED return to ED resulting in hospital admission, death following ED visit, care escalation, high-risk conditions based on symptom-disease dyads, return visits with new diagnostic/therapeutic interventions, and change of treating service after admission. Non-EHR based signals included: cases from mortality/morbidity conferences, risk management/safety office referrals, ED medical director case referrals, patient complaints, and radiology/laboratory misreads and callbacks. The panel suggested further refinements to aid future research in defining diagnostic error epidemiology in ED settings.ConclusionsWe identified a set of e-trigger concepts and non-EHR based signals that could be developed further to screen ED visits for diagnostic safety events. With additional evaluation, trigger-based methods can be used as tools to monitor and improve ED diagnostic performance.

Ways that nurse practitioner students self-explain during diagnostic reasoning

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Leah Burt ◽  
Susan Corbridge ◽  
Colleen Corte ◽  
Laurie Quinn ◽  
Lorna Finnegan ◽  
...  
Keyword(s):  
Problem Solving ◽  
Health Care Providers ◽  
Nurse Practitioner ◽  
Descriptive Analysis ◽  
Diagnostic Errors ◽  
Diagnostic Reasoning ◽  
Knowledge Structures ◽  
Future Research ◽  
Biological Knowledge ◽  
Care Providers

Abstract Objectives An important step in mitigating the burden of diagnostic errors is strengthening diagnostic reasoning among health care providers. A promising way forward is through self-explanation, the purposeful technique of generating self-directed explanations to process novel information while problem-solving. Self-explanation actively improves knowledge structures within learners’ memories, facilitating problem-solving accuracy and acquisition of knowledge. When students self-explain, they make sense of information in a variety of unique ways, ranging from simple restatements to multidimensional thoughts. Successful problem-solvers frequently use specific, high-quality self-explanation types. The unique types of self-explanation present among nurse practitioner (NP) student diagnosticians have yet to be explored. This study explores the question: How do NP students self-explain during diagnostic reasoning? Methods Thirty-seven Family NP students enrolled in the Doctor of Nursing Practice program at a large, Midwestern U.S. university diagnosed three written case studies while self-explaining. Dual methodology content analyses facilitated both deductive and qualitative descriptive analysis. Results Categories emerged describing the unique ways that NP student diagnosticians self-explain. Nine categories of inference self-explanations included clinical and biological foci. Eight categories of non-inference self-explanations monitored students’ understanding of clinical data and reflect shallow information processing. Conclusions Findings extend the understanding of self-explanation use during diagnostic reasoning by affording a glimpse into fine-grained knowledge structures of NP students. NP students apply both clinical and biological knowledge, actively improving immature knowledge structures. Future research should examine relationships between categories of self-explanation and markers of diagnostic success, a step in developing prompted self-explanation learning interventions.

scholarly journals Defining indocyanine green fluorescence to assess anastomotic perfusion during gastrointestinal surgery: systematic review

BJS Open ◽  
2021 ◽  
Vol 5 (2) ◽  
Author(s):  
M D Slooter ◽  
M S E Mansvelders ◽  
P R Bloemen ◽  
S S Gisbertz ◽  
W A Bemelman ◽  
...  
Keyword(s):  
Systematic Review ◽  
Indocyanine Green ◽  
Patient Outcomes ◽  
Gastrointestinal Surgery ◽  
Fluorescence Angiography ◽  
Future Research ◽  
Fluorescence Signal ◽  
Pixel Intensity ◽  
Indocyanine Green Fluorescence ◽  
Quantitative Parameters

Abstract Background The aim of this systematic review was to identify all methods to quantify intraoperative fluorescence angiography (FA) of the gastrointestinal anastomosis, and to find potential thresholds to predict patient outcomes, including anastomotic leakage and necrosis. Methods This systematic review adhered to the PRISMA guidelines. A PubMed and Embase literature search was performed. Articles were included when FA with indocyanine green was performed to assess gastrointestinal perfusion in human or animals, and the fluorescence signal was analysed using quantitative parameters. A parameter was defined as quantitative when a diagnostic numeral threshold for patient outcomes could potentially be produced. Results Some 1317 articles were identified, of which 23 were included. Fourteen studies were done in patients and nine in animals. Eight studies applied FA during upper and 15 during lower gastrointestinal surgery. The quantitative parameters were divided into four categories: time to fluorescence (20 studies); contrast-to-background ratio (3); pixel intensity (2); and numeric classification score (2). The first category was subdivided into manually assessed time (7 studies) and software-derived fluorescence–time curves (13). Cut-off values were derived for manually assessed time (speed in gastric conduit wall) and derivatives of the fluorescence–time curves (Fmax, T1/2, TR and slope) to predict patient outcomes. Conclusion Time to fluorescence seems the most promising category for quantitation of FA. Future research might focus on fluorescence–time curves, as many different parameters can be derived and the fluorescence intensity can be bypassed. However, consensus on study set-up, calibration of fluorescence imaging systems, and validation of software programs is mandatory to allow future data comparison.

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