scholarly journals Reasons of Diagnostic Errors and the Ways to Overcome among Medical Residents

2019 ◽  
Vol 09 (04) ◽  
pp. 324-325
Author(s):  
Shafaq Sultana ◽  
Farhat Fatima
Keyword(s):  
Patient Safety ◽  
Diagnostic Tests ◽  
Diagnostic Errors ◽  
Medical Practitioner ◽  
Accurate Diagnosis ◽  
Medical Residents ◽  
Initial Assessment ◽  
Diagnostic Process ◽  
Global Precedence

Arriving at an accurate diagnosis is one of the competencies prime of the medical practitioner. Errors may occur in the diagnostic process anywhere from the point of patient’s initial assessment and interpretation of diagnostic tests, and even during follow-up and patient referral. Patient safety is gaining global precedence and in this context diagnostic errors are speculate as an important cause of harm to the patients.1 An awareness of the possible underlying factors leading to diagnostic errors, along with a repertoire of strategies to improve can be of great help to both junior and senior medical residents

scholarly journals Application of electronic trigger tools to identify targets for improving diagnostic safety

2018 ◽  
Vol 28 (2) ◽  
pp. 151-159 ◽  
Author(s):  
Daniel R Murphy ◽  
Ashley ND Meyer ◽  
Dean F Sittig ◽  
Derek W Meeks ◽  
Eric J Thomas ◽  
...  
Keyword(s):  
Adverse Event ◽  
Patient Safety ◽  
High Risk ◽  
Health Systems ◽  
Language Processing ◽  
Diagnostic Errors ◽  
Diagnostic Process ◽  
Future Research ◽  
Implementation Challenges ◽  
Preventable Harm

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.

The 6C model for accurately capturing the patient’s medical history

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Taro Shimizu
Keyword(s):  
Artificial Intelligence ◽  
Differential Diagnosis ◽  
Patient Safety ◽  
Information Processing ◽  
Safety Concern ◽  
Data Gathering ◽  
Diagnostic Errors ◽  
Accurate Diagnosis ◽  
History Taking ◽  
Novel Approach

Abstract Diagnostic errors are an internationally recognized patient safety concern, and leading causes are faulty data gathering and faulty information processing. Obtaining a full and accurate history from the patient is the foundation for timely and accurate diagnosis. A key concept underlying ideal history acquisition is “history clarification,” meaning that the history is clarified to be depicted as clearly as a video, with the chronology being accurately reproduced. A novel approach is presented to improve history-taking, involving six dimensions: Courtesy, Control, Compassion, Curiosity, Clear mind, and Concentration, the ‘6 C’s’. We report a case that illustrates how the 6C approach can improve diagnosis, especially in relation to artificial intelligence tools that assist with differential diagnosis.

Lessons in clinical reasoning – pitfalls, myths, and pearls: the contribution of faulty data gathering and synthesis to diagnostic error

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Martin A. Schaller-Paule ◽  
Helmuth Steinmetz ◽  
Friederike S. Vollmer ◽  
Melissa Plesac ◽  
Felix Wicke ◽  
...  
Keyword(s):  
Patient Safety ◽  
Clinical Reasoning ◽  
Data Gathering ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Care Physician ◽  
Diagnostic Process ◽  
Myasthenic Crisis ◽  
Hospital Organization ◽  
Substantial Impact

Abstract Objectives Errors in clinical reasoning are a major factor for delayed or flawed diagnoses and put patient safety at risk. The diagnostic process is highly dependent on dynamic team factors, local hospital organization structure and culture, and cognitive factors. In everyday decision-making, physicians engage that challenge partly by relying on heuristics – subconscious mental short-cuts that are based on intuition and experience. Without structural corrective mechanisms, clinical judgement under time pressure creates space for harms resulting from systems and cognitive errors. Based on a case-example, we outline different pitfalls and provide strategies aimed at reducing diagnostic errors in health care. Case presentation A 67-year-old male patient was referred to the neurology department by his primary-care physician with the diagnosis of exacerbation of known myasthenia gravis. He reported shortness of breath and generalized weakness, but no other symptoms. Diagnosis of respiratory distress due to a myasthenic crisis was made and immunosuppressive therapy and pyridostigmine were given and plasmapheresis was performed without clinical improvement. Two weeks into the hospital stay, the patient’s dyspnea worsened. A CT scan revealed extensive segmental and subsegmental pulmonary emboli. Conclusions Faulty data gathering and flawed data synthesis are major drivers of diagnostic errors. While there is limited evidence for individual debiasing strategies, improving team factors and structural conditions can have substantial impact on the extent of diagnostic errors. Healthcare organizations should provide the structural supports to address errors and promote a constructive culture of patient safety.

Levamisole-Induced Leukoencephalopathy in Russia: Analysis of 30 Cases

2021 ◽  
Vol 17 ◽  
Author(s):  
Zakharova Maria Nikolaevna ◽  
Zakroyshchikova Inessa Vladimirovna ◽  
Kozlova Alexandra Olegovna ◽  
Zabirova Alfiia Hodzhaevna ◽  
Askarova Lola Shavkatovna ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Medication Management ◽  
Brain Mri ◽  
Diagnostic Errors ◽  
Acute Disseminated Encephalomyelitis ◽  
Initial Assessment ◽  
Mri Findings ◽  
Actual Prevalence

Aims: To raise medical specialists’ awareness regarding the severity of possible complications of levamisole administration and demonstrate the role of accurate medical history collection in differential diagnosis. Background: Levamisole, an anthelmintic drug with immunomodulatory effects, has long been used worldwide till early 2000s, when its association with demyelinating leukoencephalopathy was established. However, in the developing countries it is still widely used for prevention and treatment of helminthic invasion in humans. Actual prevalence of levamisole-induced multiple inflammatory leukoencephalopathy (LEV-induced MIL) in Russia remains unknown, and therefore, the study of its frequency and characteristics is indisputably important. Objectives: To determine the clinical features and MRI findings of levamisole-induced MIL in the Russian population and to analyse the frequency of diagnostic errors at the initial assessment. Methods: A single-center retrospective analysis of total 30 patients who were diagnosed with LEV-induced MIL and attended Research Center of Neurology was conducted. Inclusion criteria were 1) clinically: acute or subacute polysymptomatic onset of neurological disturbances, 2) MRI: multifocal demyelinating lesion with no evidence of dissemination in time, 3) anamnestic data: levamisole exposure from 2 to 8 weeks before symptoms onset as well as monophasic disease course (absence of relapses according to follow up assessments up to 3 years). Results: Clinically, presentation with constitutional symptoms, including headache, fever, fatigue and myalgia, focal motor disturbances and dysarthria prevailed in our cohort. On the brain MRI, multiple foci of demyelination with simultaneous gadolinium enhancement were observed. The link between neurological symptoms and levamisole intake has often been detected only during follow-up assessments. Patients were most often misdiagnosed with acute disseminated encephalomyelitis, stroke and multiple sclerosis. In most cases LEV-induced MIL was successfully treated with intravenous corticosteroids and/or plasma exchange (PLEX), however, residual neurologic symptoms preserved in some patients. Additionally, two detailed clinical cases of patients being initially misdiagnosed are presented in the article. Conclusion: The differential diagnosis remains difficult for suspected cases of LEV-induced MIL that could lead to delayed therapy initiation, and consequently incomplete recovery. Growing evidence suggests that a single administration of levamisole even in low doses might potentially lead to severe neurological deficit or death. Therefore, changes in medication management policies are required in order to prevent uncontrolled use of levamisole.

Analyzing diagnostic errors in the acute setting: a process-driven approach

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jacqueline A. Griffin ◽  
Kevin Carr ◽  
Kerrin Bersani ◽  
Nicholas Piniella ◽  
Daniel Motta-Calderon ◽  
...  
Keyword(s):  
Acute Care ◽  
Medical Error ◽  
Diagnostic Errors ◽  
General Medicine ◽  
Diagnostic Error ◽  
Assessment Process ◽  
Initial Assessment ◽  
Diagnostic Process ◽  
Case Review ◽  
Systematic Strategy

Abstract Objectives We describe an approach for analyzing failures in diagnostic processes in a small, enriched cohort of general medicine patients who expired during hospitalization and experienced medical error. Our objective was to delineate a systematic strategy for identifying frequent and significant failures in the diagnostic process to inform strategies for preventing adverse events due to diagnostic error. Methods Two clinicians independently reviewed detailed records of purposively sampled cases identified from established institutional case review forums and assessed the likelihood of diagnostic error using the Safer Dx instrument. Each reviewer used the modified Diagnostic Error Evaluation and Research (DEER) taxonomy, revised for acute care (41 possible failure points across six process dimensions), to characterize the frequency of failure points (FPs) and significant FPs in the diagnostic process. Results Of 166 cases with medical error, 16 were sampled: 13 (81.3%) had one or more diagnostic error(s), and a total of 113 FPs and 30 significant FPs were identified. A majority of significant FPs (63.3%) occurred in “Diagnostic Information and Patient Follow-up” and “Patient and Provider Encounter and Initial Assessment” process dimensions. Fourteen (87.5%) cases had a significant FP in at least one of these dimensions. Conclusions Failures in the diagnostic process occurred across multiple dimensions in our purposively sampled cohort. A systematic analytic approach incorporating the modified DEER taxonomy, revised for acute care, offered critical insights into key failures in the diagnostic process that could serve as potential targets for preventative interventions.

Profiles of Psychosocial and Clinical Functioning in Adolescence and Risk for Later Depression

2019 ◽  
Author(s):  
Thomas M Olino ◽  
Daniel Klein ◽  
John Seeley
Keyword(s):  
Psychosocial Functioning ◽  
Adolescent Depression ◽  
Depressive Disorders ◽  
Self Report ◽  
Initial Assessment ◽  
Predictive Utility ◽  
Regression Methods ◽  
History Of ◽  
History Of Depression

Background: Most studies examining predictors of onset of depression focus on variable centered regression methods that focus on effects of multiple predictors. In contrast, person-centered approaches develop profiles of factors and these profiles can be examined as predictors of onset. Here, we developed profiles of adolescent psychosocial and clinical functioning among adolescents without a history of major depression. Methods: Data come from a subsample of participants from the Oregon Adolescent Depression Project who completed self-report measures of functioning in adolescence and completed diagnostic and self-report measures at follow-up assessments up to approximately 15 years after baseline. Results: We identified four profiles of psychosocial and clinical functioning: Thriving; Average Functioning; Externalizing Vulnerability and Family Stress; and Internalizing Vulnerability at the baseline assessment of participants without a history of depression at the initial assessment in mid- adolescence. Classes differed in the likelihood of onset and course of depressive disorders, experience of later anxiety and substance use disorders, and psychosocial functioning in adulthood. Moreover, the predictive utility of these classes was maintained when controlling for multiple other established risk factors for depressive disorders. Conclusions: This work highlights the utility of examining multiple factors simultaneously to understand risk for depression.

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