Detecting diagnostic error in psychiatry

Diagnosis ◽  
2014 ◽  
Vol 1 (1) ◽  
pp. 75-78 ◽  
Author(s):  
James Phillips
Keyword(s):  
Error Detection ◽  
Gold Standard ◽  
Laboratory Tests ◽  
General Medicine ◽  
Diagnostic Error ◽  
Diagnostic Process ◽  
Psychiatric Diagnoses ◽  
Tissue Analysis ◽  
Laboratory Findings ◽  
Diagnostic Categories

AbstractThe question of diagnostic error in psychiatry involves two intertwined issues, diagnosis and error detection. You cannot detect diagnostic error unless you have a reliable, valid method of making diagnoses. Since the diagnostic process is less certain in psychiatry than in general medicine, that will make the detection of error less confidant. Psychiatric diagnostic categories are developed without laboratory tests and other biomarkers. These limitations dramatically weaken the validity of psychiatric diagnoses and render error detection an uncertain undertaking, with go gold standard such as laboratory findings and tissue analysis, as in most of general medicine. With these limitations in mind, I review the methods that are available for error detection in psychiatry.

Comparing Methods to Measure Error in Gynecologic Cytology and Surgical Pathology

2006 ◽  
Vol 130 (5) ◽  
pp. 626-629 ◽  
Author(s):  
Andrew A. Renshaw
Keyword(s):  
Clinical Practice ◽  
Error Detection ◽  
Gold Standard ◽  
Diagnostic Error ◽  
Error Rates ◽  
Surgical Pathology ◽  
Measuring Error ◽  
Review Of The Literature ◽  
Actual Clinical Practice ◽  
Measure Error

Abstract Context.—Both gynecologic cytology and surgical pathology use similar methods to measure diagnostic error, but differences exist between how these methods have been applied in the 2 fields. Objective.—To compare the application of methods of error detection in gynecologic cytology and surgical pathology. Data Sources.—Review of the literature. Conclusions.—There are several different approaches to measuring error, all of which have limitations. Measuring error using reproducibility as the gold standard is a common method to determine error. While error rates in gynecologic cytology are well characterized and methods for objectively assessing error in the legal setting have been developed, meaningful methods to measure error rates in clinical practice are not commonly used and little is known about the error rates in this setting. In contrast, in surgical pathology the error rates are not as well characterized and methods for assessing error in the legal setting are not as well defined, but methods to measure error in actual clinical practice have been characterized and preliminary data from these methods are now available concerning the error rates in this setting.

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.

scholarly journals SARS-CoV-2/DENV co-infection: a series of cases from the Federal District, Midwestern Brazil

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Heidi Luise Schulte ◽  
José Diego Brito-Sousa ◽  
Marcus Vinicius Guimarães Lacerda ◽  
Luciana Ansaneli Naves ◽  
Eliana Teles de Gois ◽  
...  
Keyword(s):  
Clinical Signs ◽  
Federal District ◽  
Therapeutic Interventions ◽  
Diagnostic Process ◽  
The Novel ◽  
Prevention Measures ◽  
Laboratory Findings ◽  
Novel Coronavirus ◽  
The Impact

Abstract Background Since the novel coronavirus disease outbreak, over 179.7 million people have been infected by SARS-CoV-2 worldwide, including the population living in dengue-endemic regions, particularly Latin America and Southeast Asia, raising concern about the impact of possible co-infections. Methods Thirteen SARS-CoV-2/DENV co-infection cases reported in Midwestern Brazil between April and September of 2020 are described. Information was gathered from hospital medical records regarding the most relevant clinical and laboratory findings, diagnostic process, therapeutic interventions, together with clinician-assessed outcomes and follow-up. Results Of the 13 cases, seven patients presented Acute Undifferentiated Febrile Syndrome and six had pre-existing co-morbidities, such as diabetes, hypertension and hypopituitarism. Two patients were pregnant. The most common symptoms and clinical signs reported at first evaluation were myalgia, fever and dyspnea. In six cases, the initial diagnosis was dengue fever, which delayed the diagnosis of concomitant infections. The most frequently applied therapeutic interventions were antibiotics and analgesics. In total, four patients were hospitalized. None of them were transferred to the intensive care unit or died. Clinical improvement was verified in all patients after a maximum of 21 days. Conclusions The cases reported here highlight the challenges in differential diagnosis and the importance of considering concomitant infections, especially to improve clinical management and possible prevention measures. Failure to consider a SARS-CoV-2/DENV co-infection may impact both individual and community levels, especially in endemic areas.

scholarly journals Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation

2021 ◽  
pp. bmjqs-2020-011593
Author(s):  
Traber D Giardina ◽  
Saritha Korukonda ◽  
Umber Shahid ◽  
Viralkumar Vaghani ◽  
Divvy K Upadhyay ◽  
...  
Keyword(s):  
Medical Record ◽  
Clinical Care ◽  
Diagnostic Testing ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Diagnostic Process ◽  
Healthcare Organisation ◽  
Safety Concerns ◽  
Patient Complaints ◽  
Malpractice Claims

BackgroundPatient complaints are associated with adverse events and malpractice claims but underused in patient safety improvement.ObjectiveTo systematically evaluate the use of patient complaint data to identify safety concerns related to diagnosis as an initial step to using this information to facilitate learning and improvement.MethodsWe reviewed patient complaints submitted to Geisinger, a large healthcare organisation in the USA, from August to December 2017 (cohort 1) and January to June 2018 (cohort 2). We selected complaints more likely to be associated with diagnostic concerns in Geisinger’s existing complaint taxonomy. Investigators reviewed all complaint summaries and identified cases as ‘concerning’ for diagnostic error using the National Academy of Medicine’s definition of diagnostic error. For all ‘concerning’ cases, a clinician-reviewer evaluated the associated investigation report and the patient’s medical record to identify any missed opportunities in making a correct or timely diagnosis. In cohort 2, we selected a 10% sample of ‘concerning’ cases to test this smaller pragmatic sample as a proof of concept for future organisational monitoring.ResultsIn cohort 1, we reviewed 1865 complaint summaries and identified 177 (9.5%) concerning reports. Review and analysis identified 39 diagnostic errors. Most were categorised as ‘Clinical Care issues’ (27, 69.2%), defined as concerns/questions related to the care that is provided by clinicians in any setting. In cohort 2, we reviewed 2423 patient complaint summaries and identified 310 (12.8%) concerning reports. The 10% sample (n=31 cases) contained five diagnostic errors. Qualitative analysis of cohort 1 cases identified concerns about return visits for persistent and/or worsening symptoms, interpersonal issues and diagnostic testing.ConclusionsAnalysis of patient complaint data and corresponding medical record review identifies patterns of failures in the diagnostic process reported by patients and families. Health systems could systematically analyse available data on patient complaints to monitor diagnostic safety concerns and identify opportunities for learning and improvement.

The impact of electronic health records on diagnosis

Diagnosis ◽  
2017 ◽  
Vol 4 (4) ◽  
pp. 211-223 ◽  
Author(s):  
Mark L. Graber ◽  
Colene Byrne ◽  
Doug Johnston
Keyword(s):  
Safety Concern ◽  
Diagnostic Error ◽  
The United States ◽  
Unintended Consequences ◽  
Diagnostic Process ◽  
Health It ◽  
Health Care Information ◽  
Health Care Information Technology ◽  
Electronic Health ◽  
The Impact

AbstractDiagnostic error may be the largest unaddressed patient safety concern in the United States, responsible for an estimated 40,000–80,000 deaths annually. With the electronic health record (EHR) now in near universal use, the goal of this narrative review is to synthesize evidence and opinion regarding the impact of the EHR and health care information technology (health IT) on the diagnostic process and its outcomes. We consider the many ways in which the EHR and health IT facilitate diagnosis and improve the diagnostic process, and conversely the major ways in which it is problematic, including the unintended consequences that contribute to diagnostic error and sometimes patient deaths. We conclude with a summary of suggestions for improving the safety and safe use of these resources for diagnosis in the future.

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.

Checklists to prevent diagnostic errors: a pilot randomized controlled trial

Diagnosis ◽  
2015 ◽  
Vol 2 (3) ◽  
pp. 163-169 ◽  
Author(s):  
John W. Ely ◽  
Mark A. Graber
Keyword(s):  
Primary Care ◽  
Usual Care ◽  
Error Rate ◽  
Primary Care Physicians ◽  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Diagnostic Process ◽  
Emergency Physicians ◽  
Mean Error ◽  
Premature Closure

AbstractMany diagnostic errors are caused by premature closure of the diagnostic process. To help prevent premature closure, we developed checklists that prompt physicians to consider all reasonable diagnoses for symptoms that commonly present in primary care.We enrolled 14 primary care physicians and 100 patients in a randomized clinical trial. The study took place in an emergency department (5 physicians) and a same-day access clinic (9 physicians). The physicians were randomized to usual care vs. diagnostic checklist. After completing the history and physical exam, checklist physicians read aloud a differential diagnosis checklist for the chief complaint. The primary outcome was diagnostic error, which was defined as a discrepancy between the diagnosis documented at the acute visit and the diagnosis based on a 1-month follow-up phone call and record review.There were 17 diagnostic errors. The mean error rate among the seven checklist physicians was not significantly different from the rate among the seven usual-care physicians (11.2% vs. 17.8%; p=0.46). In a post-hoc subgroup analysis, emergency physicians in the checklist group had a lower mean error rate than emergency physicians in the usual-care group (19.1% vs. 45.0%; p=0.04). Checklist physicians considered more diagnoses than usual-care physicians during the patient encounters (6.5 diagnoses [SD 4.2] vs. 3.4 diagnoses [SD 2.0], p<0.001).Checklists did not improve the diagnostic error rate in this study. However further development and testing of checklists in larger studies may be warranted.

scholarly journals Use of Heuristics during the clinical decision process in from family physicians in real conditions.

2021 ◽  
Author(s):  
Carmen Fernández Aguilar ◽  
José-Jesús Martín-Martín ◽  
Sergio Minué-Lorenzo ◽  
Alberto Fernández Ajuria
Keyword(s):  
Primary Care ◽  
Decision Process ◽  
Primary Care Physicians ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Operational Definition ◽  
Statistical Correlation ◽  
Diagnostic Process ◽  
Representativeness Heuristic ◽  
Definition Of

Rationale, aims and objectives: The available evidence on the existence and consequences of the use of heuristics in the clinical decision process is very scarce. The purpose of this study is to measure the use of the Representativeness, Availability and Overconfidence heuristics in real conditions with Primary Care physicians in cases of dyspnea and to study the possible correlation with diagnostic error. Methods: A prospective cohort study was carried out in 4 Primary Care centers in which 371 new cases or dyspnea were registered. The use of the three heuristics in the diagnostic process is measured through an operational definition of the same. Subsequently, the statistical correlation with the identified clinical errors is analyzed. Results: In 9.97% of the registered cases a diagnostic error was identified. In 49.59% of the cases, the physicians used the representativeness heuristic in the diagnostic decision process. The availability heuristic was used by 82.38% of the doctors and finally, in more than 50% of the cases the doctors showed excess confidence. None of the heuristics showed a statistically significant correlation with diagnostic error. Conclusion: The three heuristics have been used as mental shortcuts by Primary Care physicians in the clinical decision process in cases of dyspnea, but their influence on the diagnostic error is not significant. New studies based on the proposed methodology will allow confirming both its importance and its association with diagnostic error.

scholarly journals The psychology of diagnostic error

2015 ◽  
Vol 8 (3) ◽  
pp. 91-98
Author(s):  
L. Zwaan
Keyword(s):  
Diagnostic Errors ◽  
Diagnostic Error ◽  
Dual Process ◽  
Dual Process Theory ◽  
Process Theory ◽  
Diagnostic Process ◽  
Cognitive Errors ◽  
System 2 ◽  
System 1 ◽  
Analytic Reasoning

Diagnostic errors in medicine occur frequently and the consequences for the patient can be severe. Cognitive errors as well as system related errors contribute to the occurrence of diagnostic error, but it is generally accepted that cognitive errors are the main contributor. The diagnostic reasoning process in medicine, is an understudied area of research. One reason is because of the complexity of the diagnostic process and therefore the difficulty to measure diagnostic errors and the causes of diagnostic error. In this paper, I discuss some of the complexities of the diagnostic process. I describe the dual-process theory, which defines two reasoning modes, 1. a fast, automatic and unconscious reasoning mode called system 1, and a slow and analytic reasoning mode called system 2. Furthermore, the main cognitive causes of diagnostic error are described.

scholarly journals Mind the overlap: how system problems contribute to cognitive failure and diagnostic errors

Diagnosis ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 151-156 ◽  
Author(s):  
Ashwin Gupta ◽  
Molly Harrod ◽  
Martha Quinn ◽  
Milisa Manojlovich ◽  
Karen E. Fowler ◽  
...  
Keyword(s):  
Information Processing ◽  
Data Gathering ◽  
Diagnostic Errors ◽  
Organizational Structures ◽  
Diagnostic Error ◽  
Diagnostic Process ◽  
Cognitive Errors ◽  
Data Verification ◽  
Consulting Services ◽  
Cognitive Failure

Abstract Background Traditionally, research has examined systems- and cognitive-based sources of diagnostic error as individual entities. However, half of all errors have origins in both domains. Methods We conducted a focused ethnography of inpatient physicians at two academic institutions to understand how systems-based problems contribute to cognitive errors in diagnosis. Medicine teams were observed on rounds and during post-round work after which interviews were conducted. Field notes related to the diagnostic process and the work system were recorded, and findings were organized into themes. Using deductive content analysis, themes were categorized based on a published taxonomy to link systems-based contributions and cognitive errors such as faulty data gathering, information processing, data verification and errors associated with multiple domains. Results Observations, focus groups and interviews of 10 teams were conducted between January 2016 and April 2017. The following themes were identified: (1) challenges with interdisciplinary communication and communication within the electronic medical record (EMR) contributed to faulty data gathering; (2) organizational structures such as the operation of consulting services in silos promoted faulty information processing; (3) care handoffs led to faulty data verification and (4) interruptions, time constraints and a cluttered physical environment negatively influenced multiple cognitive domains. Conclusions Systems-based factors often facilitate and promote cognitive problems in diagnosis. Linking systems-based contributions to downstream cognitive impacts and intervening on both in tandem may help prevent diagnostic errors.

Sign in / Sign up

Export Citation Format

Share Document