Reducing Diagnostic Errors--Why Now?

Diagnostic Safety: Needs Assessment and Informed Curriculum at an Academic Children's Hospital

Background

Diagnostic excellence is central to healthcare quality and safety. Prior literature identified a lack of psychological safety and time as barriers to diagnostic reasoning education. We performed a needs assessment to inform the development of diagnostic safety education.

Methods

To evaluate existing educational programming and identify opportunities for content delivery, surveys were emailed to 155 interprofessional educational leaders and 627 clinicians at our hospital. Educational leaders and learners were invited to participate in focus groups to further explore beliefs, perceptions, and recommendations about diagnostic reasoning. The study team analyzed data using directed content analysis to identify themes.

Results

Of the 57 education leaders who responded to our survey, only 2 (5%) reported having formal training on diagnostic reasoning in their respective departments. The learner survey had a response rate of 47% (293/627). Learners expressed discomfort discussing diagnostic uncertainty and preferred case-based discussions and bedside learning as avenues for learning about the topic. Focus groups, including 7 educators and 16 learners, identified the following as necessary precursors to effective teaching about diagnostic safety: (1) faculty development, (2) institutional culture change, and (3) improved reporting of missed diagnoses. Participants preferred mandatory sessions integrated into existing educational programs.

Conclusions

Our needs assessment identified a broad interest in education regarding medical diagnosis and potential barriers to implementation. Respondents highlighted the need to develop communication skills regarding diagnostic errors and uncertainty across professions and care areas. Study findings informed a pilot diagnostic reasoning curriculum for faculty and trainees.

The burden of diagnostic error in dentistry: A study on periodontal disease misclassification

BACKGROUND

Periodontal disease constitutes a widely prevalent category of non-communicable diseases and ranks among the top 10 causes of disability worldwide. Little however is known about diagnostic errors in dentistry. In this work, by retrospectively deploying an electronic health record (EHR)-based trigger tool, followed by gold standard manual review, we provide epidemiological estimates on the rate of diagnostic misclassification in dentistry through a periodontal use case.

METHODS

An EHR-based trigger tool (a retrospective record review instrument that uses a list of triggers (or clues), i.e., data elements within the health record, to alert reviewers to the potential presence of a wrong diagnosis) was developed, tested and run against the EHR at the two participating sites to flag all cases having a potential misdiagnosis. All cases flagged as potentially misdiagnosed underwent extensive manual reviews by two calibrated domain experts. A subset of the non-flagged cases was also manually reviewed.

RESULTS

A total of 2,262 patient charts met the study's inclusion criteria. Of these, the algorithm flagged 1,124 cases as potentially misclassified and 1,138 cases as potentially correctly diagnosed. When the algorithm identified a case as potentially misclassified, compared to the diagnosis assigned by the gold standard, the kappa statistic was 0.01. However, for cases the algorithm marked as potentially correctly diagnosed, the review against the gold standard showed a kappa statistic of 0.9, indicating near perfect agreement. The observed proportion of diagnostic misclassification was 32 %. There was no significant difference by clinic or provider characteristics.

CONCLUSION

Our work revealed that about a third of periodontal cases are misclassified. Diagnostic errors have been reported to happen more frequently than other types of errors, and to be more preventable. Benchmarking diagnostic quality is a first step. Subsequent research endeavor will delve into comprehending the factors that contribute to diagnostic errors in dentistry and instituting measures to prevent them.

CLINICAL SIGNIFICANCE

This study sheds light on the significance of diagnostic excellence in the delivery of dental care, and highlights the potential role of technology in aiding diagnostic decision-making at the point of care.

Leveraging learning systems to improve quality and patient safety in allergen immunotherapy

Adverse events occur in all fields of medicine, including allergy-immunology, in which allergen immunotherapy medical errors can cause significant harm. Although difficult to experience, such errors constitute opportunities for improvement. Identifying system vulnerabilities can allow resolution of latent errors before they become active problems. We review key aspects and frameworks of the medical error response, acknowledging the fundamental responsibility of clinical teams to learn from harm. Adverse event response comprises 4 major phases: (1) event recognition and reporting, (2) investigation (for which root cause analysis can be helpful), (3) improvement (inclusive of the plan-do-study-act cycle), and (4) communication and resolution. Throughout the process, clinician wellness must be maintained. Adverse event prevention should be prioritized, and a human factors engineering approach can be useful. Quality improvement tools and approaches complement one another and together offer a meaningful avenue for error recovery and prevention.

The impact of transoesophageal echocardiography in elderly patients with infective endocarditis

BACKGROUND

Infective endocarditis (IE) increasingly involves older patients. Geriatric status may influence diagnostic and therapeutic decisions.

AIM

To describe transoesophageal echocardiography (TEE) use in elderly IE patients, and its impact on therapeutic management and mortality.

METHODS

A multicentre prospective observational study (ELDERL-IE) included 120 patients aged ≥75 years with definite or possible IE: mean age 83.1±5.0; range 75-101 years; 56 females (46.7%). Patients had an initial comprehensive geriatric assessment, and 3-month and 1-year follow-up. Comparisons were made between patients who did or did not undergo TEE.

RESULTS

Transthoracic echocardiography revealed IE-related abnormalities in 85 patients (70.8%). Only 77 patients (64.2%) had TEE. Patients without TEE were older (85.4±6.0 vs. 81.9±3.9 years; P=0.0011), had more comorbidities (Cumulative Illness Rating Scale-Geriatric score 17.9±7.8 vs. 12.8±6.7; P=0.0005), more often had no history of valvular disease (60.5% vs. 37.7%; P=0.0363), had a trend toward a higher Staphylococcus aureus infection rate (34.9% vs. 22.1%; P=0.13) and less often an abscess (4.7% vs. 22.1%; P=0.0122). Regarding the comprehensive geriatric assessment, patients without TEE had poorer functional, nutritional and cognitive statuses. Surgery was performed in 19 (15.8%) patients, all with TEE, was theoretically indicated but not performed in 15 (19.5%) patients with and 6 (14.0%) without TEE, and was not indicated in 43 (55.8%) patients with and 37 (86.0%) without TEE (P=0.0006). Mortality was significantly higher in patients without TEE.

CONCLUSIONS

Despite similar IE features, surgical indication was less frequently recognized in patients without TEE, who less often had surgery and had a poorer prognosis. Cardiac lesions might have been underdiagnosed in the absence of TEE, hampering optimal therapeutic management. Advice of geriatricians should help cardiologists to better use TEE in elderly patients with suspected IE.

Donor Safety, Discrepancies Between Practice and Theory: Analysis of the Polish Supreme Audit Office's Report

The introduction and development of genetic testing has caused the emergence of numerous dilemmas, which pertain to the performed tests, their results, and the influence they have on an individual person. To minimize potential doubts, it is crucial to ensure compliance with established procedures and to fulfill all test-associated formalities. In 2018, a report of the Polish Supreme Audit's Office (a governmental control agency) on the quality of genetic tests revealed that there is much to be done in the field of laboratory diagnostics in Poland. The inspection of six selected laboratories performing genetic tests identified shortcomings in terms of formalities accompanying the process of performing laboratory tests, keeping patient documentation and personal data protection. Although the observed shortcomings pertained to legal aspects of genetic tests, and not the quality of the tests themselves, the aforementioned may be detrimental to the individual person and the society (eg, lack of consent undermines the concept of biological material ownership), may cause legal liability to the laboratory personnel and even undermine public trust in genetic testing.

Psychiatric diagnostic dilemmas among people with intellectual and developmental disabilities

BACKGROUND

Research regarding the accuracy of co-morbid psychiatric diagnoses in individuals with intellectual and developmental disabilities (IDD) is sparse. Yet correct diagnostic assignment is vital so that effective and appropriate treatment can be implemented, especially for the large numbers of individuals requiring expensive and restrictive behavioural health crisis services.

METHOD

A retrospective review of de-identified data from multidisciplinary specialty team assessments completed for 50 individuals with ID (IntellectualDisability) with and without ASD and unresolved behavioural health challenges was conducted. The accuracy and reliability of the psychiatric diagnoses upon referral were compared with the diagnoses after the comprehensive team evaluation, and within-individual diagnostic agreement was calculated. The agreement between the Mood and Anxiety Semi-Structured interview tool (MASS) and the full team evaluation was also calculated. The influence of demographic and clinical characteristics on diagnostic agreement was explored.

RESULTS

The most common chief complaints upon referral were aggression to others and self-injurious behaviour. Individuals were taking a median of six medications (interquartile range: 5 to 7); 80% were taking an antipsychotic medication. The most common medical conditions were constipation (70%) and gastroesophageal reflux disease (52%). Measures of interrater reliability of the referral diagnoses with the team assessment were below 0.5 (kappa range: -0.04 to 0.39), with the exception of ruling out dementia (kappa = 0.85). The interrater reliability estimates for the MASS evaluations for depression and anxiety were higher (kappa = 0.69 and 0.64) and reflected higher sensitivity and PPV. The odds of any referral diagnosis being confirmed by team evaluation were low: 0.25 (range: 0 to 0.67). The level of diagnostic agreement for each patient was not significantly attributable to demographic or clinical characteristics, although effect sizes indicate a possible positive relationship to age and the number of prescribed psychotropic medications at referral.

CONCLUSION

Individuals in the current study had serious psychiatric and behavioural problems despite psychiatric care in their communities. The majority of psychiatric diagnoses provided upon referral were not supported by the multidisciplinary specialty team's assessment. In addition to possible diagnostic inaccuracy, the group in the study suffered from multiple medical co-morbidities and were exposed to polypharmacy. Results emphasise the importance of multidisciplinary evaluation by clinicians with expertise in neurodevelopmental disabilities when people with ID with and without ASD have complex behavioural health needs that are unresponsive to usual care. In addition, based on agreement with the full team evaluation, the MASS shows promise as an assessment tool, especially with regards to identifying anxiety and depression.

Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders

Diagnostic error or delay (DEOD) is common in the acute care setting and results in poor patient outcomes. Many factors contribute to DEOD, but little is known about how contributors may differ across acute care areas and professional roles. As part of a sequential exploratory mixed methods research study, we surveyed acute care clinical stakeholders about the frequency with which different factors contribute to DEOD. Survey respondents could also propose solutions in open text fields. N = 220 clinical stakeholders completed the survey. Care Team Interactions, Systems and Process, Patient, Provider, and Cognitive factors were perceived to contribute to DEOD with similar frequency. Organization and Infrastructure factors were perceived to contribute to DEOD significantly less often. Responses did not vary across acute care setting. Physicians perceived Cognitive factors to contribute to DEOD more frequently compared to those in other roles. Commonly proposed solutions included: technological solutions, organization level fixes, ensuring staff know and are encouraged to work to the full scope of their role, and cultivating a culture of collaboration and respect. Multiple factors contribute to DEOD with similar frequency across acute care areas, suggesting the need for a multi-pronged approach that can be applied across acute care areas.

Behavioral Economics Interventions to Improve Medical Decision-Making

BACKGROUND

In medicine, a wide gap exists between the medical care that ought to be possible in the light of the current state of medical research and the care that is actually provided. Behavioral biases and noise are two major reasons for this.

METHODS

We present the findings of a selective literature review and illustrate how interventions based on behavioral economics can help physicians make better decisions and thereby improve treatment outcomes.

RESULTS

A number of behavioral economics interventions, making use of, for example, default settings, active decision rules, social norms, and self-commitments, may improve physicians' clinical decision-making. Evidence on long-term effects is, however, mostly lacking.

CONCLUSION

Despite their apparent potential, the application of behavioral economic interventions to improve medical decisionmaking is still in its infancy, particularly in Germany.

Deep learning from multiple experts improves identification of amyloid neuropathologies

Pathologists can label pathologies differently, making it challenging to yield consistent assessments in the absence of one ground truth. To address this problem, we present a deep learning (DL) approach that draws on a cohort of experts, weighs each contribution, and is robust to noisy labels. We collected 100,495 annotations on 20,099 candidate amyloid beta neuropathologies (cerebral amyloid angiopathy (CAA), and cored and diffuse plaques) from three institutions, independently annotated by five experts. DL methods trained on a consensus-of-two strategy yielded 12.6-26% improvements by area under the precision recall curve (AUPRC) when compared to those that learned individualized annotations. This strategy surpassed individual-expert models, even when unfairly assessed on benchmarks favoring them. Moreover, ensembling over individual models was robust to hidden random annotators. In blind prospective tests of 52,555 subsequent expert-annotated images, the models labeled pathologies like their human counterparts (consensus model AUPRC = 0.74 cored; 0.69 CAA). This study demonstrates a means to combine multiple ground truths into a common-ground DL model that yields consistent diagnoses informed by multiple and potentially variable expert opinions.

Bedside Clinicians' Perceptions on the Contributing Role of Diagnostic Errors in Acutely Ill Patient Presentation: A Survey of Academic and Community Practice

OBJECTIVES

This study aimed to explore clinicians' perceptions of the occurrence of and factors associated with diagnostic errors in patients evaluated during a rapid response team (RRT) activation or unplanned admission to the intensive care unit (ICU).

METHODS

A multicenter prospective survey study was conducted among multiprofessional clinicians involved in the care of patients with RRT activations and/or unplanned ICU admissions (UIAs) at 2 academic hospitals and 1 community-based hospital between April 2019 and March 2020. A study investigator screened eligible patients every day. Within 24 hours of the event, a research coordinator administered the survey to clinicians, who were asked the following: whether diagnostic errors contributed to the reason for RRT/UIA, whether any new diagnosis was made after RRT/UIA, if there were any failures to communicate the diagnosis, and if involvement of specialists earlier would have benefited that patient. Patient clinical data were extracted from the electronic health record.

RESULTS

A total of 1815 patients experienced RRT activations, and 1024 patients experienced UIA. Clinicians reported that 18.2% (95/522) of patients experienced diagnostic errors, 8.0% (42/522) experienced a failure of communication, and 16.7% (87/522) may have benefitted from earlier involvement of specialists. Compared with academic settings, clinicians in the community hospital were less likely to report diagnostic errors (7.0% versus 22.8%, P = 0.002).

CONCLUSIONS

Clinicians report a high rate of diagnostic errors in patients they evaluate during RRT or UIAs.

Predicting Common Audiological Functional Parameters (CAFPAs) as Interpretable Intermediate Representation in a Clinical Decision-Support System for Audiology

The application of machine learning for the development of clinical decision-support systems in audiology provides the potential to improve the objectivity and precision of clinical experts' diagnostic decisions. However, for successful clinical application, such a tool needs to be accurate, as well as accepted and trusted by physicians. In the field of audiology, large amounts of patients' data are being measured, but these are distributed over local clinical databases and are heterogeneous with respect to the applied assessment tools. For the purpose of integrating across different databases, the Common Audiological Functional Parameters (CAFPAs) were recently established as abstract representations of the contained audiological information describing relevant functional aspects of the human auditory system. As an intermediate layer in a clinical decision-support system for audiology, the CAFPAs aim at maintaining interpretability to the potential users. Thus far, the CAFPAs were derived by experts from audiological measures. For designing a clinical decision-support system, in a next step the CAFPAs need to be automatically derived from available data of individual patients. Therefore, the present study aims at predicting the expert generated CAFPA labels using three different machine learning models, namely the lasso regression, elastic nets, and random forests. Furthermore, the importance of different audiological measures for the prediction of specific CAFPAs is examined and interpreted. The trained models are then used to predict CAFPAs for unlabeled data not seen by experts. Prediction of unlabeled cases is evaluated by means of model-based clustering methods. Results indicate an adequate prediction of the ten distinct CAFPAs. All models perform comparably and turn out to be suitable choices for the prediction of CAFPAs. They also generalize well to unlabeled data. Additionally, the extracted relevant features are plausible for the respective CAFPAs, facilitating interpretability of the predictions. Based on the trained models, a prototype of a clinical decision-support system in audiology can be implemented and extended towards clinical databases in the future.

Discrepancies between clinical diagnosis and hospital autopsy: A comparative retrospective analysis of 1,112 cases

Aims

The aim of this study was to compare discrepancies between diagnosed and autopsied causes of death in 1,112 hospital autopsies and to determine the factors causing this discrepancies.

Methods

1,112 hospital autopsies between 2010 and 2013 were retrospectively studied. Ante-mortem diagnoses were compared to causes of death as determined by autopsy. Clinical diagnoses were extracted from the autopsy request form, and post-mortem diagnoses were assessed from respective autopsy reports. Variables, such as sex, age, Body Mass Index, category of disease, duration of hospital stay and new-borns were studied in comparison to discrepancy. P-values were derived from the Mann-Whitney U test for the constant features and chi-2 test, p-values < 0,05 were considered significant.

Results

73.9% (n = 822) patients showed no discrepancy between autopsy and clinical diagnosis. The duration of hospitalisation (6 vs. 9 days) and diseases of the cardiovascular system (61.7%) had a significant impact on discrepancies.

Conclusion

Age, cardiovascular diseases and duration of hospital stay significantly affect discrepancies in ante- and post-mortem diagnoses.

Cognitive Errors in Pediatric Emergency Medicine

ABSTRACT

Fundamental to the practice of pediatric emergency medicine is making timely and accurate diagnoses. However, studies have shown errors in this process are common. A number of factors in the emergency department environment as well as identifiable errant patterns of thinking can contribute to such challenges. Cognitive psychologists have described 2 types of thinking: system 1 (fast) relies primarily on intuition and pattern recognition, whereas system 2 (slow) is more deliberative and analytical. Reviewing how these 2 styles of thinking are applied in clinical practice provides a framework for understanding specific cognitive errors. This article uses illustrative examples to introduce many of these common errors, providing context for how and why they occur. In addition, a practical approach to reducing the risk of such errors is offered.

Serious Diagnoses for Headaches After ED Discharge

BACKGROUND

Headache is a common complaint among children presenting to the emergency department (ED) and can be due to serious neurologic and nonneurologic diagnoses (SNNDs). We sought to characterize the children discharged from the ED with headache found to have SNNDs at revisits.

METHODS

We performed a multicenter retrospective cohort study using data from 45 pediatric hospitals from October 1, 2015, to March 31, 2019. We included pediatric patients (≤18 years) discharged from the ED with a principal diagnosis of headache, excluding patients with concurrent or previous SNNDs or neurosurgeries. We identified rates and types of SNNDs diagnosed within 30 days of initial visit and compared these rates with those of control groups defined as patients with discharge diagnoses of cough, chest pain, abdominal pain, and soft tissue complaints.

RESULTS

Of 121 621 included patients (57% female, median age 12.4 years, interquartile range: 8.8-15.4), 608 (0.5%, 95% confidence interval: 0.5%-0.5%) were diagnosed with SNNDs within 30 days. Most were diagnosed at the first revisit (80.8%); 37.5% were diagnosed within 7 days. The most common SNNDs were benign intracranial hypertension, cerebral edema and compression, and seizures. A greater proportion of patients with SNNDs underwent neuroimaging, blood, and cerebrospinal fluid testing compared with those without SNNDs (P < .001 for each). The proportion of SNNDs among patients diagnosed with headache (0.5%) was higher than for control cohorts (0.0%-0.1%) (P < .001 for each).

CONCLUSIONS

A total 0.5% of pediatric patients discharged from the ED with headache were diagnosed with an SNND within 30 days. Further efforts to identify at-risk patients remain a challenge.

Something's Lost and Something's Gained: Seeing Reference Laboratory Quality from Both Sides, Now

Growing regulatory burdens, payment model changes, and increased complexity in laboratory medicine have contributed to an increased reliance on reference laboratories. Although reference laboratories often offer rapid, low cost, high quality testing, outsourcing laboratory tests can create quality and patient safety vulnerabilities particularly in the pre-analytic and post-analytic phases of the test cycle. Disconnects in governance, policy, and information technology between the reference laboratory and the referring provider conspire to increase risk. Laboratory leaders seeking to reduce risk and improve quality must ensure clear and collaborative oversight, monitor meaningful quality metrics, and integrate feedback from ordering providers.

Diagnostic error, quality assurance, and medical malpractice/risk management education in emergency medicine residency training programs

Background

Diagnostic errors in emergency medicine (EM) can lead to patient harm as well as potential malpractice claims and quality assurance (QA) reviews. It is therefore essential that these topics are part of the core education of trainees. The methods training programs use to educate residents on these topics are unknown. The goal of this study was to identify the current methods used to teach EM residents about diagnostic errors, QA, and malpractice/risk management and determine the amount of educational teaching time EM programs dedicate to these topics.

Methods

An 11-item questionnaire pertaining to resident education on diagnostic errors, QA, and malpractice was sent through the Council of Emergency Medicine Residency Directors (CORD) listserv. Differences in the proportions of responses by duration of training program were analyzed using chi-squared or Fisher’s exact tests.

Results

Fifty-four percent (91/168) of the EM programs responded. There was no difference in prevalence of formal education on these topics among 3- and 4-year programs. The majority of programs (59.5%) offer fewer than 4 h per year of additional QA education beyond morbidity and mortality rounds; a minority of the programs (18.8%) offer more than 4 h per year of medical malpractice/risk management education.

Conclusions

This needs assessment demonstrated that there is a lack of dedicated educational time devoted to these topics. A more formalized and standard curricular approach with increased time allotment may enhance EM resident education about diagnostic errors, QA, and malpractice/risk management.

From second to hundredth opinion in medicine: A global consultation platform for physicians

Serious medical diagnostic errors lead to adverse patient outcomes and increased healthcare costs. The use of virtual online consultation platforms may lead to better-informed physicians and reduce the incidence of diagnostic errors. Our aim was to assess the usage characteristics of an online, physician-to-physician, no-cost, medical consultation platform, Medscape Consult, from November 2015 through October 2017. Physicians creating original content were noted as “presenters” and those following up as “responders”. During the study period, 37,706 physician users generated a combined 117,346 presentations and responses. The physicians had an average age of 56 years and were from 171 countries on every continent. Over 90% of all presentations received responses with the median time to first response of 1.5 h. Overall, computer- and device-based medical consultation has the capacity to rapidly reach a global medical community and may play a role in the reduction of diagnostic errors.

A Fatal Case of Undiagnosed Candida Meningitis: Role of Computer-assisted Diagnosis

Diagnostic error is an increasing health care concern. An intravenous drug abuser with chronic meningitis died after a prolonged hospitalization from fungal meningitis diagnosed at autopsy. We examine the diagnostic pitfalls and consider how a computer-assisted diagnostic system may influence the outcome of an otherwise fatal condition.

Health Information Technology in Healthcare Quality and Patient Safety: Literature Review

Background

The area of healthcare quality and patient safety is starting to use health information technology to prevent reportable events, identify them before they become issues, and act on events that are thought to be unavoidable. As healthcare organizations begin to explore the use of health information technology in this realm, it is often unclear where fiscal and human efforts should be focused.

Objective

The purpose of this study was to provide a foundation for understanding where to focus health information technology fiscal and human resources as well as expectations for the use of health information technology in healthcare quality and patient safety.

Methods

A literature review was conducted to identify peer-reviewed publications reporting on the actual use of health information technology in healthcare quality and patient safety. Inductive thematic analysis with open coding was used to categorize a total of 41 studies. Three pre-set categories were used: prevention, identification, and action. Three additional categories were formed through coding: challenges, outcomes, and location.

Results

This study identifies five main categories across seven study settings. A majority of the studies used health IT for identification and prevention of healthcare quality and patient safety issues. In this realm, alerts, clinical decision support, and customized health IT solutions were most often implemented. Implementation, interface design, and culture were most often noted as challenges.

Conclusions

This study provides valuable information as organizations determine where they stand to get the most “bang for their buck” relative to health IT for quality and patient safety. Knowing what implementations are being effectivity used by other organizations helps with fiscal and human resource planning as well as managing expectations relative to cost, scope, and outcomes. The findings from this scan of the literature suggest that having organizational champion leaders that can shepherd implementation, impact culture, and bridge knowledge with developers would be a valuable resource allocation to consider.

Transitioning to a High-Value Health Care Model: Academic Accountability

Health care spending in the United States has increased to unprecedented levels, and these costs have broken medical providers' promise to do no harm. Medical debt is the leading contributor to U.S. personal bankruptcy, more than 50% of household foreclosures are secondary to medical debt and illness, and patients are choosing to avoid necessary care because of its cost. Evidence that the health care delivery model is contributing to patient hardship is a call to action for the profession to transition to a high-value model, one that delivers the highest health care quality and safety at the lowest personal and financial cost to patients. As such, value improvement work is being done at academic medical centers across the country. To promote measurable improvements in practice on a national scale, academic institutions need to align efforts and create a new model for collaboration, one that transcends cross-institutional competition, specialty divisions, and geographical constraints. Academic institutions are particularly accountable because of the importance of research and education in driving this transition. Investigations that elucidate effective implementation methodologies and evaluate safety outcomes data can facilitate transformation. Engaging trainees in quality improvement initiatives will instill high-value care into their practice. This article charges academic institutions to go beyond dissemination of best practice guidelines and demonstrate accountability for high-value quality improvement implementation. By effectively transitioning to a high-value health care system, medical providers will convincingly demonstrate that patients are their most important priority.

Diagnostic Error in Pediatric Cancer

The purpose of this study was to ( a) determine the frequency of diagnostic errors in pediatric cancer, ( b) categorize errors, and ( c) underscore themes associated with misdiagnosis. This is a retrospective cohort study at a tertiary children's hospital of 265 patients with new oncologic diagnoses. The diagnostic error rate was 28%. Compared with those with no diagnostic error, those in whom there was an error were more likely to have ( a) more visits before diagnosis ( P < .001), ( b) not been seen in an acute care setting ( P = .03), ( c) inappropriate treatment ( P < .001), and ( d) misinterpreted laboratory studies or imaging ( P < .001). Themes in diagnostic errors were lack of appropriate evaluation for persistent symptoms (47%), failure to recognize signs and symptoms suggestive of malignancy (45%), and misinterpretation of tests (8%). Clinicians should consider diagnostic evaluation for multiple visits for the same complaint or a constellation of signs and symptoms suggestive of malignancy.

To err is human, to correct is public health: a systematic review examining poor quality testing and misdiagnosis of HIV status

INTRODUCTION

In accordance with global testing and treatment targets, many countries are seeking ways to reach the "90-90-90" goals, starting with diagnosing 90% of all people with HIV. Quality HIV testing services are needed to enable people with HIV to be diagnosed and linked to treatment as early as possible. It is essential that opportunities to reach people with undiagnosed HIV are not missed, diagnoses are correct and HIV-negative individuals are not inadvertently initiated on life-long treatment. We conducted this systematic review to assess the magnitude of misdiagnosis and to describe poor HIV testing practices using rapid diagnostic tests.

METHODS

We systematically searched peer-reviewed articles, abstracts and grey literature published from 1 January 1990 to 19 April 2017. Studies were included if they used at least two rapid diagnostic tests and reported on HIV misdiagnosis, factors related to potential misdiagnosis or described quality issues and errors related to HIV testing.

RESULTS

Sixty-four studies were included in this review. A small proportion of false positive (median 3.1%, interquartile range (IQR): 0.4-5.2%) and false negative (median: 0.4%, IQR: 0-3.9%) diagnoses were identified. Suboptimal testing strategies were the most common factor in studies reporting misdiagnoses, particularly false positive diagnoses due to using a "tiebreaker" test to resolve discrepant test results. A substantial proportion of false negative diagnoses were related to retesting among people on antiretroviral therapy. Conclusions HIV testing errors and poor practices, particularly those resulting in false positive or false negative diagnoses, do occur but are preventable. Efforts to accelerate HIV diagnosis and linkage to treatment should be complemented by efforts to improve the quality of HIV testing services and strengthen the quality management systems, particularly the use of validated testing algorithms and strategies, retesting people diagnosed with HIV before initiating treatment and providing clear messages to people with HIV on treatment on the risk of a "false negative" test result.

[Cognitive errors in diagnostic decision making]

Approximately 10-15% of our diagnostic decisions are faulty and may lead to unfavorable and dangerous outcomes, which could be avoided. These diagnostic errors are mainly caused by cognitive biases in the diagnostic reasoning process.Our medical diagnostic decision-making is based on intuitive "System 1" and analytical "System 2" diagnostic decision-making and can be deviated by unconscious cognitive biases.These deviations can be positively influenced on a systemic and an individual level. For the individual, metacognition (internal withdrawal from the decision-making process) and debiasing strategies, such as verification, falsification and rule out worst-case scenarios, can lead to improved diagnostic decisions making.

Teaching for Reducing Diagnostic Errors

Diagnostic errors, constituted by a missed, wrong, or delayed diagnosis detected later by additional tests or findings, are one of the most vexing issues in medicine. They are one of the commonest causes of patient- harm and also medical negligence claims. Although a variety of constructs have been proposed to explain diagnostic errors, the complex interplay of cognitive- and system-factors that underlie these errors is rarely clear to the clinicians. In this write-up, we discuss the reasons for diagnostic errors and how medical students can be trained to avoid such errors. The errors have been classified as Cognitive errors, System errors, and No-fault errors, and cognitive interventions to address each of these are detailed.

How Doctors Think: Common Diagnostic Errors in Clinical Judgment-Lessons from an Undiagnosed and Rare Disease Program

The scientific process of analysis and deduction is frequently, often subconsciously, used by physicians to develop a differential diagnosis based on patients' symptoms. Common disorders are most frequently diagnosed in general practice. Rare diseases are uncommon and frequently remain undiagnosed for many years. Cognitive errors in clinical judgment delay definitive diagnosis. Whole-exome sequencing has helped identify the cause of undiagnosed or rare diseases in up to 40% of children. This article provides experiences with an undiagnosed or rare disease program, where detailed data accumulation and a multifaceted analytical approach assisted in diagnosing atypical presentations of common disorders.

Estimate of false-positive breast cancer diagnoses from accuracy studies: a systematic review

Background

False-positive histological diagnoses have the same consequences of overdiagnosis in terms of unnecessary treatment. The aim of this systematic review is to assess their frequency at needle core biopsy (CB) and/or surgical excision of the breast.

Methods

PubMed, Embase, Cochrane Library were systematically searched up to 30 October 2015. Eligibility criteria: cross-sectional studies assessing diagnostic accuracy of CB compared with surgical excision; studies assessing reproducibility of pathologists reading the same slides. Outcomes: false-positive rates; Misclassification of Benign as Malignant (MBM) histological diagnosis; K statistic. Independent reviewers extracted data and assessed quality using an adapted QUADAS-2 tool.

Results

Sixteen studies assessed CB false-positive rates. In 10 studies (41 989 screen-detected lesions), the range of false-positive rates was 0%–7.1%. Twenty-seven studies assessed pathologists' reproducibility. Studies with consecutive, random or stratified samples of all the specimens: at CB the MBM range was 0.25%–2.4% (K values 0.83–0.98); at surgical excision, it was 0.67%–1.2% (K values 0.86–0.94). Studies with enriched samples: the MBM range was 1.4%–6.2% (K values 0.57–0.86). Studies of cases selected for second opinion: the MBM range was 0.29%–12.2% (K values 0.48 and 0.50).

Conclusions

High heterogeneity of the included studies precluded formal pooling estimates. When considering studies of higher sample size or methodological quality, false-positive rates and MBM are around 1%. The impact of false-positive histological diagnoses of breast cancer on unnecessary treatment, as well as that of overdiagnosis, is not negligible and is of importance in clinical practice.

Reliability and Validity of the Checklist for Early Recognition and Treatment of Acute Illness and Injury as a Charting Tool in the Medical Intensive Care Unit

Background:

Resuscitation of critically ill patients is complex and potentially prone to diagnostic errors and therapeutic harm. The Checklist for early recognition and treatment of acute illness and injury (CERTAIN) is an electronic tool that aims to provide decision-support, charting, and prompting for standardization. This study sought to evaluate the validity and reliability of CERTAIN in a real-time Intensive Care Unit (ICU).

Materials and Methods:

This was a prospective pilot study in the medical ICU of a tertiary care medical center. A total of thirty patient encounters over 2 months period were charted independently by two CERTAIN investigators. The inter-observer recordings and comparison to the electronic medical records (EMR) were used to evaluate reliability and validity, respectively. The primary outcome was reliability and validity measured using Cohen's Kappa statistic. Secondary outcomes included time to completion, user satisfaction, and learning curve.

Results:

A total of 30 patients with a median age of 59 (42–78) years and median acute physiology and chronic health evaluation III score of 38 (23–50) were included in this study. Inter-observer agreement was very good (κ = 0.79) in this study and agreement between CERTAIN and the EMR was good (κ = 0.5). CERTAIN charting was completed in real-time that was 121 (92–150) min before completion of EMR charting. The subjective learning curve was 3.5 patients without differences in providers with different levels of training.

Conclusions:

CERTAIN provides a reliable and valid method to evaluate resuscitation events in real time. CERTAIN provided the ability to complete data in real-time.

Diagnostic discrepancies in clinical practice: An autopsy study in patients with heart failure

Autopsies are the gold standard for diagnostic accuracy; however, no recent study has analyzed autopsies in heart failure (HF).We reviewed 1241 autopsies (January 2000-May 2005) and selected 232 patients with HF. Clinical and autopsy diagnoses were analyzed and discrepancies categorized according to their importance regarding therapy and prognosis.Mean age was 63.3 ± 15.9 years; 154 (66.4%) patients were male. The causes of death at autopsy were end-stage HF (40.9%), acute myocardial infarction (17.2%), infection (15.9), and pulmonary embolism 36 (15.5). Diagnostic discrepancies occurred in 191 (82.3%) cases; in 56 (24.1%), discrepancies were related to major diagnoses with potential influence on survival or treatment; pulmonary embolism was the cause of death for 24 (42.9%) of these patients. In 35 (15.1%), discrepancies were related to a major diagnosis with equivocal influence on survival or treatment; in 100 (43.1%), discrepancies did not influence survival or treatment. In multivariate analysis, age (OR: 1.03, 95% CI: 1.008-1.052, P = 0.007) and presence of diabetes mellitus (OR: 0.359, 95% CI: 0.168-0.767, P = 0.008) influenced the occurrence discrepancies.Diagnostic discrepancies with a potential impact on prognosis are frequent in HF. These findings warrant reconsideration in diagnostic and therapeutic practices with HF patients.

Claims-Based Diagnostic Patterns of Patients Evaluated for Lyme Disease and Given Extended Antibiotic Therapy

BACKGROUND

A Lyme disease (LD) diagnosis can be far from straightforward, particularly if erythema migrans does not develop or is not noticed. Extended courses of antibiotics for LD are not recommended, but their use is increasing. We sought to elucidate the patient patterns toward a diagnosis of LD, hypothesizing that a subset of patients ultimately receiving extended courses antibiotics may be symptomatic for an extended period before the first LD diagnosis.

METHODS

Claims submitted to a nationwide U.S. health insurance plan in 14 high-prevalence states were grouped into standardized diagnostic categories. The patterns of diagnostic categories over time were compared between patients evaluated for LD and given standard antibiotic therapy (PLDSA) and patients evaluated for LD and given extended antibiotic therapy (PLDEA) in 2011-2012.

RESULTS

The incidence of PLDSA was 40.45 (N = 3207) and that of PLDEA was 7.57 (N = 600) per 100,000 insured over 2011-2012. 50.3% of PLDEA were diagnosed in the nonsummer months. Seven diagnostic categories were associated with PLDEA. From 180 days before the first LD diagnosis, the risks of having claims associated with back problems (odds ratio [OR], 2.1; confidence interval [95% CI], 1.4-2.9; p < 0.001) and connective tissue disease (OR, 1.6; 95% CI, 1.1-2.3; p < 0.01) complaints were higher among PLDEA. From 90 days before the diagnosis, malaise and fatigue (OR, 1.7; 95% CI, 1.1-2.6; p < 0.05), other nervous system disorders (OR, 2.0; 95% CI, 1.3-3.1; p < 0.01), and nontraumatic joint disorder (OR, 1.4; 95% CI, 1.0-2.0; p < 0.05) were more likely found among PLDEA than PLDSA. From 30 days before the diagnosis, the risk for mental health (OR 1.6; 95% CI, 1.1-2.0; p < 0.01) and headache (OR 1.5; 95% CI, 1.1-2.0; p < 0.05) among PLDEA was elevated.

CONCLUSIONS

Among patients evaluated for LD and ultimately receiving an extended course of antibiotics for LD, 15.8% of them were symptomatic and seeking care for several months before their first LD diagnosis.

The incorporation of focused history in checklist for early recognition and treatment of acute illness and injury

BACKGROUND

Diagnostic error and delay are critical impediments to the safety of critically ill patients. Checklist for early recognition and treatment of acute illness and injury (CERTAIN) has been developed as a tool that facilitates timely and error-free evaluation of critically ill patients. While the focused history is an essential part of the CERTAIN framework, it is not clear how best to choreograph this step in the process of evaluation and treatment of the acutely decompensating patient.

METHODS

An un-blinded crossover clinical simulation study was designed in which volunteer critical care clinicians (fellows and attendings) were randomly assigned to start with either obtaining a focused history choreographed in series (after) or in parallel to the primary survey. A focused history was obtained using the standardized SAMPLE model that is incorporated into American College of Trauma Life Support (ATLS) and Pediatric Advanced Life Support (PALS). Clinicians were asked to assess six acutely decompensating patients using pre - determined clinical scenarios (three in series choreography, three in parallel). Once the initial choreography was completed the clinician would crossover to the alternative choreography. The primary outcome was the cognitive burden assessed through the NASA task load index. Secondary outcome was time to completion of a focused history.

RESULTS

A total of 84 simulated cases (42 in parallel, 42 in series) were tested on 14 clinicians. Both the overall cognitive load and time to completion improved with each successive practice scenario, however no difference was observed between the series versus parallel choreographies. The median (IQR) overall NASA TLX task load index for series was 39 (17 - 58) and for parallel 43 (27 - 52), p = 0.57. The median (IQR) time to completion of the tasks in series was 125 (112 - 158) seconds and in parallel 122 (108 - 158) seconds, p = 0.92.

CONCLUSION

In this clinical simulation study assessing the incorporation of a focused history into the primary survey of a non-trauma critically ill patient, there was no difference in cognitive burden or time to task completion when using series choreography (after the exam) compared to parallel choreography (concurrent with the primary survey physical exam). However, with repetition of the task both overall task load and time to completion improved in each of the choreographies.

Online public reactions to frequency of diagnostic errors in US outpatient care

BACKGROUND

Diagnostic errors pose a significant threat to patient safety but little is known about public perceptions of diagnostic errors. A study published in BMJ Quality & Safety in 2014 estimated that diagnostic errors affect at least 5% of US adults (or 12 million) per year. We sought to explore online public reactions to media reports on the reported frequency of diagnostic errors in the US adult population.

METHODS

We searched the World Wide Web for any news article reporting findings from the study. We then gathered all the online comments made in response to the news articles to evaluate public reaction to the newly reported diagnostic error frequency (n=241). Two coders conducted content analyses of the comments and an experienced qualitative researcher resolved differences.

RESULTS

Overall, there were few comments made regarding the frequency of diagnostic errors. However, in response to the media coverage, 44 commenters shared personal experiences of diagnostic errors. Additionally, commentary centered on diagnosis-related quality of care as affected by two emergent categories: (1) US health care providers (n=79; 63 commenters) and (2) US health care reform-related policies, most commonly the Affordable Care Act (ACA) and insurance/reimbursement issues (n=62; 47 commenters).

CONCLUSION

The public appears to have substantial concerns about the impact of the ACA and other reform initiatives on the diagnosis-related quality of care. However, policy discussions on diagnostic errors are largely absent from the current national conversation on improving quality and safety. Because outpatient diagnostic errors have emerged as a major safety concern, researchers and policymakers should consider evaluating the effects of policy and practice changes on diagnostic accuracy.