A unified conceptual model for diagnostic errors: underdiagnosis, overdiagnosis, and misdiagnosis

Harbingers of sepsis misdiagnosis among pediatric emergency department patients

OBJECTIVES

To identify clinical presentations that acted as harbingers for future sepsis hospitalizations in pediatric patients evaluated in the emergency department (ED) using the Symptom Disease Pair Analysis of Diagnostic Error (SPADE) methodology.

METHODS

We identified patients in the Pediatric Health Information Systems (PHIS) database admitted for sepsis between January 1, 2004 and December 31, 2023 and limited the study cohort to those patients who had an ED treat-and-release visit in the 30 days prior to admission. Using the look-back approach of the SPADE methodology, we identified the most common clinical presentations at the initial ED visit and used an observed to expected (O:E) analysis to determine which presentations were overrepresented. We then employed a graphical, temporal analysis with a comparison group to identify which overrepresented presentations most likely represented harbingers for future sepsis hospitalization.

RESULTS

We identified 184,157 inpatient admissions for sepsis, of which 15,331 hospitalizations (8.3 %) were preceded by a treat-and-release ED visit in the prior 30 days. Based on the O:E and temporal analyses, the presentations of fever and dehydration were both overrepresented in the study cohort and temporally clustered close to sepsis hospitalization. ED treat-and-release visits for fever or dehydration preceded 1.2 % of all sepsis admissions.

CONCLUSIONS

In pediatric patients presenting to the ED, fever and dehydration may represent harbingers for future sepsis hospitalization. The SPADE methodology could be applied to the PHIS database to develop diagnostic performance measures across a wide range of pediatric hospitals.

Framing diagnostic error: an epidemiological perspective

Diagnostic errors burden the United States healthcare system. Depending on how they are defined, between 40,000 and 4 million cases occur annually. Despite this striking statistic, and the potential benefits epidemiological approaches offer in identifying risk factors for sub-optimal diagnoses, diagnostic error remains an underprioritized epidemiolocal research topic. Magnifying the challenge are the array of forms and definitions of diagnostic errors, and limited sources of data documenting their occurrence. In this narrative review, we outline a framework for improving epidemiological applications in understanding risk factors for diagnostic error. This includes explicitly defining diagnostic error, specifying the hypothesis and research questions, consideration of systemic including social and economic factors, as well as the time-dependency of diagnosis relative to disease progression. Additional considerations for future epidemiological research on diagnostic errors include establishing standardized research databases, as well as identifying potential important sources of study bias.

Diagnostic Discrepancies in the Emergency Department: A Retrospective Study

OBJECTIVES

Diagnostic errors contribute substantially to preventable medical errors. Especially, the emergency department (ED) is a high-risk environment. Previous research showed that in 15%-30% of the ED patients, there is a difference between the primary diagnosis assigned by the emergency physician and the discharge diagnosis. This study aimed to determine the number and types of diagnostic discrepancies and to explore factors predicting discrepancies.

METHODS

A retrospective record review was conducted in an academic medical center. The primary diagnosis assigned in the ED was compared with the discharge diagnosis after hospital admission. For each patient, we gathered additional information about the diagnostic process to identify possible predictors of diagnostic discrepancies.

RESULTS

The electronic health records of 200 patients were reviewed. The primary diagnosis assigned in the ED was substantially different from the discharge diagnosis in 16.0%. These diagnostic discrepancies were associated with a higher number of additional diagnostics applied for (2.4 versus 2.0 diagnostics; P = 0.002) and longer stay in the ED (5.9 versus 4.7 hours; P = 0.008).

CONCLUSIONS

A difference between the diagnosis assigned by the emergency physician and the discharge diagnosis was found in almost 1 in 6 patients. The increased number of additional diagnostics and the longer stay at the ED in the group of patients with a diagnostic discrepancy suggests that these cases reflect the more difficult cases. More research should be done on predictive factors of diagnostic discrepancies.

ETHICS IN RADIOLOGICAL PROTECTION FOR MEDICAL DIAGNOSIS AND TREATMENT

Publication 138 defines the ethical foundations of the ICRP System of Radiological Protection based on core values (beneficence and non-maleficence, dignity, justice, and prudence) and procedural values (accountability, transparency, and inclusiveness). The purpose of the present publication is to propose a practical application of values for medical radiological protection professions. As medicine has a long history and strong culture of ethics, this publication starts by identifying the shared values, and defines a common language between biomedical ethics and radiological protection. The core values are very similar, with the autonomy of biomedical ethics, which can be seen as a corollary of dignity, and the precautionary principle, which can be understood as the implementation of prudence. In recent years, medical education and training has emphasised the values of solidarity, honesty, and, above all, empathy. All these values are defined and interpreted in the specific context of the use of ionising radiation in medicine. For those more familiar with radiological protection, the ethical implications of their actions are described. Conversely, for those who already have a good background in ethics, this publication highlights the specificities of ionising radiation that also deserve consideration.In order to emphasise the coherence between the values involved in biomedical ethics and those involved in radiological protection, this publication proposes to combine them: dignity and autonomy; beneficence and non-maleficence; prudence and precaution; justice and solidarity; transparency, accountability, and honesty; and inclusiveness and empathy. This allows a structured review of practical situations from an ethical perspective. For the sake of both example and education, this publication proposes 21 realistic scenarios (11 in imaging procedures and 10 in radiation therapies). Sensitising questions are provided to stimulate reflection and discussion. The ultimate goal is to be able to use ethical values in clinical imaging and therapy situations. Required education and training in ethics is essential for medical radiological workers throughout their career span. An example of a framework of knowledge, skills, and competencies is proposed. In order to assist the reader in a theoretically complex subject, key messages are distributed throughout the text as fixed points that can be easily understood. Although primarily aimed at medical radiological protection professionals, this publication is also intended for authorities, patients, and the public.© 2024 ICRP. Published by SAGE.

The TeamSTEPPS for Improving Diagnosis Team Assessment Tool: Scale Development and Psychometric Evaluation

INTRODUCTION

One in three patients is affected by diagnosis-related communication failures. Only a few valid and reliable instruments that measure teamwork and communication exist, and none of those focus on improving diagnosis. The authors developed, refined, and psychometrically evaluated the TeamSTEPPSⓇ for Improving Diagnosis Team Assessment Tool (TAT), which assesses diagnostic teamwork and communication in five critical teamwork domains and can be used to identify strengths and opportunities for improvement and monitor performance.

METHODS

The TAT was administered as a cross-sectional survey to 360 health professionals across nine diverse US health systems. Content and construct validity were evaluated through pilot implementation and subject matter expert review. Reliability and internal consistency were assessed with Cronbach's alpha. To understand sources of variation in TAT scores and assess the tool's consistency across diverse health care organizations, generalizability theory (G-theory) was used. Best practices in screening for careless responding identified participants with random or nonvarying responses.

RESULTS

Analyses indicated strong support for the tool. Content validity findings indicated that the TAT encompassed relevant diagnostic improvement teamwork and communication content. Construct validity, evaluated through pilot implementations, demonstrated the tool's effectiveness in assessing teamwork categories. Reliability analyses confirmed the TAT's internal consistency, with an overall Cronbach's alpha of 0.97. Each dimension of the TAT exhibited good reliability coefficients, ranging from 0.83 to 0.95. G-theory analysis showed that variations in TAT scores were primarily attributed to respondents (28.0%) and scale dimensions (59.6%); both are desirable facets of variation. Further, examination of careless respondents ensured the accuracy and quality of the results, enhancing the TAT's credibility as a valuable diagnostic improvement tool.

CONCLUSION

Psychometric evaluation demonstrated that the TAT is a reliable and valid instrument for assessing teamwork and communication among and across diagnostic teams. The TAT adds a novel, evidence-based, psychometrically sound measurement tool to help advance diagnostic teamwork and communication to improve patient care and outcomes.

Burden of serious harms from diagnostic error in the USA

BACKGROUND

Diagnostic errors cause substantial preventable harms worldwide, but rigorous estimates for total burden are lacking. We previously estimated diagnostic error and serious harm rates for key dangerous diseases in major disease categories and validated plausible ranges using clinical experts.

OBJECTIVE

We sought to estimate the annual US burden of serious misdiagnosis-related harms (permanent morbidity, mortality) by combining prior results with rigorous estimates of disease incidence.

METHODS

Cross-sectional analysis of US-based nationally representative observational data. We estimated annual incident vascular events and infections from 21.5 million (M) sampled US hospital discharges (2012-2014). Annual new cancers were taken from US-based registries (2014). Years were selected for coding consistency with prior literature. Disease-specific incidences for 15 major vascular events, infections and cancers ('Big Three' categories) were multiplied by literature-based rates to derive diagnostic errors and serious harms. We calculated uncertainty estimates using Monte Carlo simulations. Validity checks included sensitivity analyses and comparison with prior published estimates.

RESULTS

Annual US incidence was 6.0 M vascular events, 6.2 M infections and 1.5 M cancers. Per 'Big Three' dangerous disease case, weighted mean error and serious harm rates were 11.1% and 4.4%, respectively. Extrapolating to all diseases (including non-'Big Three' dangerous disease categories), we estimated total serious harms annually in the USA to be 795 000 (plausible range 598 000-1 023 000). Sensitivity analyses using more conservative assumptions estimated 549 000 serious harms. Results were compatible with setting-specific serious harm estimates from inpatient, emergency department and ambulatory care. The 15 dangerous diseases accounted for 50.7% of total serious harms and the top 5 (stroke, sepsis, pneumonia, venous thromboembolism and lung cancer) accounted for 38.7%.

CONCLUSION

An estimated 795 000 Americans become permanently disabled or die annually across care settings because dangerous diseases are misdiagnosed. Just 15 diseases account for about half of all serious harms, so the problem may be more tractable than previously imagined.

Addressing the ethical problem of underdiagnosis in the post-pandemic Canadian healthcare system

Proper diagnosis is essential for effective treatment, yet in Canada health conditions are commonly underdiagnosed at all levels of the health system, meaning that they go undiagnosed or are diagnosed only after a delay. Underdiagnosis leads to inadequate treatment and potentially insufficient recovery and rehabilitation, as well as costly inefficiencies, such as repeat medical visits. Moreover, disparities in underdiagnosis in which vulnerable groups, such as women and Indigenous persons, are properly diagnosed at lower rates worsen existing inequities, which threatens the overall health of the general population. As health leaders and policy-makers seek to strengthen Canada's strained healthcare system, it will be important to address underdiagnosis and its causes, including systematic bias. Providing timely and accurate diagnoses for all patients is an essential component of delivering high quality, efficient, ethical, and cost-effective healthcare. The Canadian College of Health Leaders' Code of Ethics offers a framework for addressing underdiagnosis equitably. Utilizing the framework, suggestions are made for actions that can be taken at all levels of the health system to reduce underdiagnosis.

Misdiagnosis of Posterior Reversible Encephalopathy Syndrome and Reversible Cerebral Vasoconstriction Syndrome in the Emergency Department

Background Cerebrovascular dysregulation syndromes, posterior reversible encephalopathy syndrome (PRES) and reversible cerebral vasoconstriction syndrome (RCVS), are challenging to diagnose because they are rare and require advanced neuroimaging for confirmation. We sought to estimate PRES/RCVS misdiagnosis in the emergency department and its associated factors. Methods and Results We conducted a retrospective cohort study of PRES/RCVS patients using administrative claims data from 11 states (2016-2018). We defined patients with a probable PRES/RCVS misdiagnosis as those with an emergency department visit for a neurological symptom resulting in discharge to home that occurred ≤14 days before PRES/RCVS hospitalization. Proportions of patients with probable misdiagnosis were calculated, characteristics of patients with and without probable misdiagnosis were compared, and regression analyses adjusted for demographics and comorbidities were performed to identify factors affecting probable misdiagnosis. We identified 4633 patients with PRES/RCVS. A total of 210 patients (4.53% [95% CI, 3.97-5.17]) had a probable preceding emergency department misdiagnosis; these patients were younger (mean age, 48 versus 54 years; P<0.001) and more often female (80.4% versus 69.3%; P<0.001). Misdiagnosed patients had fewer vascular risk factors except prior stroke (36.3% versus 24.2%; P<0.001) and more often had comorbid headache (84% versus 21.4%; P<0.001) and substance use disorder (48.8% versus 37.9%; P<0.001). Facility-level factors associated with probable misdiagnosis included smaller facility, lacking a residency program (62.2% versus 73.7%; P<0.001), and not having on-site neurological services (75.7% versus 84.3%; P<0.001). Probable misdiagnosis was not associated with higher likelihood of stroke or subarachnoid hemorrhage during PRES/RCVS hospitalization. Conclusions Probable emergency department misdiagnosis occurred in ≈1 of every 20 patients with PRES/RCVS in a large, multistate cohort.

Optimizing measurement of misdiagnosis-related harms using symptom-disease pair analysis of diagnostic error (SPADE): comparison groups to maximize SPADE validity

Diagnostic errors in medicine represent a significant public health problem but continue to be challenging to measure accurately, reliably, and efficiently. The recently developed Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach measures misdiagnosis related harms using electronic health records or administrative claims data. The approach is clinically valid, methodologically sound, statistically robust, and operationally viable without the requirement for manual chart review. This paper clarifies aspects of the SPADE analysis to assure that researchers apply this method to yield valid results with a particular emphasis on defining appropriate comparator groups and analytical strategies for balancing differences between these groups. We discuss four distinct types of comparators (intra-group and inter-group for both look-back and look-forward analyses), detailing the rationale for choosing one over the other and inferences that can be drawn from these comparative analyses. Our aim is that these additional analytical practices will improve the validity of SPADE and related approaches to quantify diagnostic error in medicine.

Vestibular syndromes, diagnosis and diagnostic errors in patients with dizziness presenting to the emergency department: a cross-sectional study

OBJECTIVES

We aimed to determine the frequency of vestibular syndromes, diagnoses, diagnostic errors and resources used in patients with dizziness in the emergency department (ED).

DESIGN

Retrospective cross-sectional study.

SETTING

Tertiary referral hospital.

PARTICIPANTS

Adult patients presenting with dizziness.

PRIMARY AND SECONDARY OUTCOME MEASURES

We collected clinical data from the initial ED report from July 2015 to August 2020 and compared them with the follow-up report if available. We calculated the prevalence of vestibular syndromes and stroke prevalence in patients with dizziness. Vestibular syndromes are differentiated in acute (AVS) (eg, stroke, vestibular neuritis), episodic (EVS) (eg, benign paroxysmal positional vertigo, transient ischaemic attack) and chronic (CVS) (eg, persistent postural-perceptual dizziness) vestibular syndrome. We reported the rate of diagnostic errors using the follow-up diagnosis as the reference standard.

RESULTS

We included 1535 patients with dizziness. 19.7% (303) of the patients presented with AVS, 34.7% (533) with EVS, 4.6% (71) with CVS and 40.9% (628) with no or unclassifiable vestibular syndrome. The three most frequent diagnoses were stroke/minor stroke (10.1%, 155), benign paroxysmal positional vertigo (9.8%, 150) and vestibular neuritis (9.6%, 148). Among patients with AVS, 25.4% (77) had stroke. The cause of the dizziness remained unknown in 45.0% (692) and 18.0% received a false diagnosis. There was a follow-up in 662 cases (43.1%) and 58.2% with an initially unknown diagnoses received a final diagnosis. Overall, 69.9% of all 1535 patients with dizziness received neuroimaging (MRI 58.2%, CT 11.6%) in the ED.

CONCLUSIONS

One-fourth of patients with dizziness in the ED presented with AVS with a high prevalence (10%) of vestibular strokes. EVS was more frequent; however, the rate of undiagnosed patients with dizziness and the number of patients receiving neuroimaging were high. Almost half of them still remained without diagnosis and among those diagnosed were often misclassified. Many unclear cases of vertigo could be diagnostically clarified after a follow-up visit.

Risk assessment of the acute stroke diagnostic process using failure modes, effects, and criticality analysis

INTRODUCTION

To date, many emergency department (ED)-based quality improvement studies and interventions for acute stroke patients have focused on expediting time-sensitive treatments, particularly reducing door-to-needle time. However, prior to treatment, a diagnosis of stroke must be reached. The ED-based stroke diagnostic process has been understudied despite its importance in assuring high-quality and safe care.

METHODS

We used a learning collaborative to conduct a failure modes, effects, and criticality analysis (FMECA) of the acute stroke diagnostic process at three health systems in Chicago, IL. Our FMECA was designed to prospectively identify, characterize, and rank order failures in the systems and processes of care that offer opportunities for redesign to improve stroke diagnostic accuracy. Multidisciplinary teams involved in stroke care at five different sites participated in moderated sessions to create an acute stroke diagnostic process map as well as identify failures and existing safeguards. For each failure, a risk priority number and criticality score were calculated. Failures were then ranked, with the highest scores representing the most critical failures to be targeted for redesign.

RESULTS

A total of 28 steps were identified in the acute stroke diagnostic process. Iterative steps in the process include information gathering, clinical examination, interpretation of diagnostic test results, and reassessment. We found that failure to use existing screening scales to identify patients with large-vessel occlusions early on in their ED course ranked highest. Failure to obtain an accurate history of the index event, failure to suspect acute stroke in triage, and failure to use established stroke screening tools at ED arrival to identify potential stroke patients were also highly ranked.

CONCLUSIONS

Our study results highlight the critical importance of upstream steps in the acute stroke diagnostic process, particularly the use of existing tools to identify stroke patients who may be eligible for time-sensitive treatments.

Developing a Framework and Electronic Tool for Communicating Diagnostic Uncertainty in Primary Care: A Qualitative Study

IMPORTANCE

Communication of information has emerged as a critical component of diagnostic quality. Communication of diagnostic uncertainty represents a key but inadequately examined element of diagnosis.

OBJECTIVE

To identify key elements facilitating understanding and managing diagnostic uncertainty, examine optimal ways to convey uncertainty to patients, and develop and test a novel tool to communicate diagnostic uncertainty in actual clinical encounters.

DESIGN, SETTING, AND PARTICIPANTS

A 5-stage qualitative study was performed between July 2018 and April 2020, at an academic primary care clinic in Boston, Massachusetts, with a convenience sample of 24 primary care physicians (PCPs), 40 patients, and 5 informatics and quality/safety experts. First, a literature review and panel discussion with PCPs were conducted and 4 clinical vignettes of typical diagnostic uncertainty scenarios were developed. Second, these scenarios were tested during think-aloud simulated encounters with expert PCPs to iteratively draft a patient leaflet and a clinician guide. Third, the leaflet content was evaluated with 3 patient focus groups. Fourth, additional feedback was obtained from PCPs and informatics experts to iteratively redesign the leaflet content and workflow. Fifth, the refined leaflet was integrated into an electronic health record voice-enabled dictation template that was tested by 2 PCPs during 15 patient encounters for new diagnostic problems. Data were thematically analyzed using qualitative analysis software.

MAIN OUTCOMES AND MEASURES

Perceptions and testing of content, feasibility, usability, and satisfaction with a prototype tool for communicating diagnostic uncertainty to patients.

RESULTS

Overall, 69 participants were interviewed. A clinician guide and a diagnostic uncertainty communication tool were developed based on the PCP interviews and patient feedback. The optimal tool requirements included 6 key domains: most likely diagnosis, follow-up plan, test limitations, expected improvement, contact information, and space for patient input. Patient feedback on the leaflet was iteratively incorporated into 4 successive versions, culminating in a successfully piloted prototype tool as an end-of-visit voice recognition dictation template with high levels of patient satisfaction for 15 patients with whom the tool was tested.

CONCLUSIONS AND RELEVANCE

In this qualitative study, a diagnostic uncertainty communication tool was successfully designed and implemented during clinical encounters. The tool demonstrated good workflow integration and patient satisfaction.

Diagnostic error, uncertainty, and overdiagnosis in melanoma

Diagnostic error can be defined as deviation from a gold standard diagnosis, typically defined in terms of expert opinion, although sometimes in terms of unexpected events that might occur in follow-up (such as progression and death from disease). Although diagnostic error does exist for melanoma, deviations from gold standard diagnosis, certainly among appropriately trained and experienced practitioners, are likely to be the result of uncertainty and lack of specific criteria, and differences of opinion, rather than lack of diagnostic skills. In this review, the concept of diagnostic error will be considered in relation to diagnostic uncertainty, and the concept of overdiagnosis in melanoma will be presented and discussed.

Providers' and Patients' Perspectives on Diagnostic Errors in the Acute Care Setting

BACKGROUND

Diagnostic errors (DEs) have been studied extensively in ambulatory care, but less work has been done in the acute care setting. In this study, the authors examined health care providers' and patients' perspectives about the classification of DEs, the main causes and scope of DEs in acute care, the main gaps in current systems, and the need for innovative solutions.

METHODS

A qualitative mixed methods study was conducted, including semistructured interviews with health care providers and focus groups with patient advisors. Using grounded theory approach, thematic categories were derived from the interviews and focus groups.

RESULTS

The research team conducted interviews with 17 providers and two focus groups with seven patient advisors. Both providers and patient advisors struggled to define and describe DEs in acute care settings. Although participants agreed that DEs pose a significant risk to patient safety, their perception of the frequency of DEs was mixed. Most participants identified communication failures, lack of comfort with diagnostic uncertainty, incorrect clinical evaluation, and cognitive load as key causes of DEs. Most respondents believed that non-information technology (IT) tools and processes (for example, communication improvement strategies) could significantly reduce DEs.

CONCLUSION

The study findings represent an important supplement to our understanding of DEs in acute care settings and the advancement of a culture of patient safety in the context of patient-centered care and patient engagement. Health care organizations should consider the key factors identified in this study when trying to create a culture that engages clinicians and patients in reducing DEs.

Defining Diagnostic Error: A Scoping Review to Assess the Impact of the National Academies' Report Improving Diagnosis in Health Care

BACKGROUND

Standards for accurate and timely diagnosis are ill-defined. In 2015, the National Academies of Science, Engineering, and Medicine (NASEM) committee published a landmark report, Improving Diagnosis in Health Care , and proposed a new definition of diagnostic error, "the failure to ( a ) establish an accurate and timely explanation of the patient's health problem(s) or ( b ) communicate that explanation to the patient."

OBJECTIVE

This study aimed to explore how researchers operationalize the NASEM's definition of diagnostic error with relevance to accuracy, timeliness, and/or communication in peer-reviewed published literature.

METHODS

Using the Arskey and O'Malley's framework framework, we identified published literature from October 2015 to February 2021 using Medline and Google Scholar. We also conducted subject matter expert interviews with researchers.

RESULTS

Of 34 studies identified, 16 were analyzed and abstracted to determine how diagnostic error was operationalized and measured. Studies were grouped by theme: epidemiology, patient focus, measurement/surveillance, and clinician focus. Nine studies indicated using the NASEM definition. Of those, 5 studies also operationalized with existing definitions proposed before the NASEM report. Four studies operationalized the components of the NASEM definition and did not cite existing definitions. Three studies operationalized error using existing definitions only. Subject matter experts indicated that the NASEM definition functions as foundation for researchers to conceptualize diagnostic error.

CONCLUSIONS

The NASEM report produced a common understanding of diagnostic error that includes accuracy, timeliness, and communication. In recent peer-reviewed literature, most researchers continue to use pre-NASEM report definitions to operationalize accuracy and timeliness. The report catalyzed the use of patient-centered concepts in the definition, resulting in emerging studies focused on examining errors related to communicating diagnosis to patients.

Analysis of Variation Between Diagnosis at Admission vs Discharge and Clinical Outcomes Among Adults With Possible Bacteremia

Importance

Misdiagnosis of infection is among the most commonly made diagnostic errors and is associated with increased morbidity and mortality. Little is known about how often misdiagnosed site of infection occurs and its association with clinical outcomes.

Objectives

To evaluate the discrepancy between admission and discharge site of infection diagnoses among patients with suspected bacteremia, to explore factors associated with discrepant diagnoses, and to evaluate the association with clinical outcomes.

Design, Setting, and Participants

This cohort study used electronic records of 1477 adult patients who were admitted to the hospital for suspected bacteremia from April 1, 2019, to May 31, 2020, and who had blood cultures taken at the emergency department at Haga Teaching Hospital, The Hague, the Netherlands. Suspected infection sites were classified into 8 categories at admission and discharge. Misdiagnosed site was defined as a discrepancy between the suspected site of infection at admission and at discharge.

Main Outcomes and Measures

Clinical outcomes were 30-day mortality, intensive care unit admission, length of hospital stay, and antibiotic use, analyzed with logistic and linear regression. Risk factors for misdiagnosed site were determined using regression analysis.

Results

A total of 1477 patients (820 [55.5%] male; median [IQR] age, 68 [56-78] years) were analyzed. The rate of misdiagnosed site of infection was 11.6% (171 of 1477); 3.1% of all patients (46 of 1477) ultimately had no infection. No association was found between misdiagnosis and 30-day mortality (adjusted odds ratio [aOR], 0.8; 95% CI, 0.3-1.9; P = .60), intensive care unit admission (aOR, 1.3; 95% CI, 0.6-3.0; P = .54), and hospital length of stay (adjusted increase of stay, 15.5%; 95% CI, -3.1% to 37.7%; P = .11). Misdiagnosed site was associated with receiving broad-spectrum antibiotics (aOR, 4.0; 95% CI, 1.8-8.8; P < .001). Older age, dementia, a positive urine sediment test result without urinary symptoms, and suspicion of an intravascular, central nervous system, or bone and joint infection were risk factors for misdiagnosed site of infection.

Conclusions and Relevance

In this cohort study, misdiagnosed site of infection occurred in 1 of 9 patients and was not associated with worse short-term clinical outcomes. Clinicians should be aware of risk factors associated with misdiagnosed site of infection and potential inappropriate antibiotic use.

Diagnostic Error in Neuro-ophthalmology: Avenues to Improve

Purpose of Review

To highlight potential avenues to reduce preventable diagnostic error of neuro-ophthalmic conditions and avoid patient harm.

Recent Findings

Recent prospective studies and studies of patient harm have advanced our understanding. Additionally, recent studies of fundus photography, telemedicine, and artificial intelligence highlight potential avenues for diagnostic improvement.

Summary

Diagnostic error of neuro-ophthalmic conditions can often be traced to failure to gather an adequate history, perform a complete physical exam, obtain adequate/appropriate neuroimaging, and generate a complete, appropriate differential diagnosis. Improving triage and identification of neuro-ophthalmic conditions by other providers and increasing access to subspecialty neuro-ophthalmology evaluation are essential avenues to reduce diagnostic error. Further research should evaluate the relationship between misdiagnosis and patient harm, and help identify the most impactful potential targets for improvement.

Diagnostic Error in Pediatrics: A Narrative Review

A priority topic for patient safety research is diagnostic errors. However, despite the significant growth in awareness of their unacceptably high incidence and associated harm, a relative paucity of large, high-quality studies of diagnostic error in pediatrics exists. In this narrative review, we present what is known about the incidence and epidemiology of diagnostic error in pediatrics as well as the established research methods for identifying, evaluating, and reducing diagnostic errors, including their strengths and weaknesses. Additionally, we highlight that pediatric diagnostic error remains an area in need of both innovative research and quality improvement efforts to apply learnings from a rapidly growing evidence base. We propose several key research questions aimed at addressing persistent gaps in the pediatric diagnostic error literature that focus on the foundational knowledge needed to inform effective interventions to reduce the incidence of diagnostic errors and their associated harm. Additional research is needed to better establish the epidemiology of diagnostic error in pediatrics, including identifying high-risk clinical scenarios, patient populations, and groups of diagnoses. A critical need exists for validated measures of both diagnostic errors and diagnostic processes that can be adapted for different clinical settings and standardized for use across varying institutions. Pediatric researchers will need to work collaboratively on large-scale, high-quality studies to accomplish the ultimate goal of reducing diagnostic errors and their associated harm in children by addressing these fundamental gaps in knowledge.

Diagnostic Policies Optimization for Chronic Diseases Based on POMDP Model

During the process of disease diagnosis, overdiagnosis can lead to potential health loss and unnecessary anxiety for patients as well as increased medical costs, while underdiagnosis can result in patients not being treated on time. To deal with these problems, we construct a partially observable Markov decision process (POMDP) model of chronic diseases to study optimal diagnostic policies, which takes into account individual characteristics of patients. The objective of our model is to maximize a patient’s total expected quality-adjusted life years (QALYs). We also derive some structural properties, including the existence of the diagnostic threshold and the optimal diagnosis age for chronic diseases. The resulting optimization is applied to the management of coronary heart disease (CHD). Based on clinical data, we validate our model, demonstrate how the quantitative tool can provide actionable insights for physicians and decision makers in health-related fields, and compare optimal policies with actual clinical decisions. The results indicate that the diagnostic threshold first decreases and then increases as the patient’s age increases, which contradicts the intuitive non-decreasing thresholds. Moreover, diagnostic thresholds were higher for women than for men, especially at younger ages.

Crossing Academic Boundaries for Diagnostic Safety: 10 Complex Challenges and Potential Solutions From Clinical Perspectives and High-Reliability Organizing Principles

OBJECTIVE

We apply the high-reliability organization (HRO) paradigm to the diagnostic process, outlining challenges to enacting HRO principles in diagnosis and offering solutions for how diagnostic process stakeholders can overcome these barriers.

BACKGROUND

Evidence shows that healthcare is starting to organize for higher reliability by employing various principles and practices of HRO. These hold promise for enhancing safer care, but there has been little consideration of the challenges that clinicians and healthcare systems face while enacting HRO principles in the diagnostic process. To effectively deploy the HRO perspective, these barriers must be seriously considered.

METHOD

We review key principles of the HRO paradigm, the diagnostic errors and harms that potentially can be prevented by its enactment, the challenges that clinicians and healthcare systems face in executing various principles and practices, and possible solutions that clinicians and organizational leaders can take to overcome these challenges and barriers.

RESULTS

Our analyses reveal multiple challenges including the inherent diagnostic uncertainty; the lack of diagnosis-focused performance feedback; the fact that diagnosis is often a solo, rather than team, activity; the tendency to simplify the diagnostic process; and professional and institutional status hierarchies. But these challenges are not insurmountable-there are strategies and solutions available to overcome them.

CONCLUSION

The HRO lens offers some important ideas for how the safety of the diagnostic process can be improved.

APPLICATION

The ideas proposed here can be enacted by both individual clinicians and healthcare leaders; both are necessary for making systematic progress in enhancing diagnostic performance.

A Research Agenda for Diagnostic Excellence in Critical Care Medicine

Diagnosing critically ill patients in the intensive care unit is difficult. As a result, diagnostic errors in the intensive care unit are common and have been shown to cause harm. Research to improve diagnosis in critical care medicine has accelerated in past years. However, much work remains to fully elucidate the diagnostic process in critical care. To achieve diagnostic excellence, interdisciplinary research is needed, adopting a balanced strategy of continued biomedical discovery while addressing the complex care delivery systems underpinning the diagnosis of critical illness.

Emergency medicine physicians' perspectives on diagnostic accuracy in neurology: a qualitative study

OBJECTIVES

We sought to understand the knowledge, attitudes, and beliefs of emergency medicine (EM) physicians towards non-specific neurological conditions and the use of clinical decision support (CDS) to improve diagnostic accuracy.

METHODS

We conducted semi-structured interviews of EM physicians at four emergency departments (EDs) affiliated with a single US healthcare system. Interviews were conducted until thematic saturation was achieved. Conventional content analysis was used to identify themes related to EM physicians' perspectives on acute diagnostic neurology; directed content analysis was used to explore views regarding CDS. Each interview transcript was independently coded by two researchers using an iteratively refined codebook with consensus-based resolution of coding differences.

RESULTS

We identified two domains regarding diagnostic safety: (1) challenges unique to neurological complaints and (2) challenges in EM more broadly. Themes relevant to neurology included: (1) knowledge gaps and uncertainty, (2) skepticism about neurology, (3) comfort with basic as opposed to detailed neurological examination, and (4) comfort with non-neurological diseases. Themes relevant to diagnostic decision making in the ED included: (1) cognitive biases, (2) ED system/environmental issues, (3) patient barriers, (4) comfort with diagnostic uncertainty, and (5) concerns regarding diagnostic error identification and measurement. Most participating EM physicians were enthusiastic about the potential for well-designed CDS to improve diagnostic accuracy for non-specific neurological complaints.

CONCLUSIONS

Physicians identified diagnostic challenges unique to neurological diseases as well as issues related more generally to diagnostic accuracy in EM. These physician-reported issues should be accounted for when designing interventions to improve ED diagnostic accuracy.

Failure to Obtain Urgent Arterial Imaging in Acute Third Nerve Palsies

BACKGROUND

Isolated third nerve palsy may indicate an expanding posterior communicating artery aneurysm, thus necessitating urgent arterial imaging. This study aims to assess the rate and duration of delays in arterial imaging for new isolated third nerve palsies, identify potential causes of delay, and evaluate instances of delay-related patient harm.

METHODS

In this cross-sectional study, we retrospectively reviewed 110 patient charts (aged 18 years and older) seen between November 2012 and June 2020 at the neuro-ophthalmology clinic and by the inpatient ophthalmology consultation service at a tertiary institution. All patients were referred for suspicion of or had a final diagnosis of third nerve palsy. Demographics, referral encounter details, physical examination findings, final diagnoses, timing of arterial imaging, etiologies of third nerve palsy, and details of patient harm were collected.

RESULTS

Of the 110 included patients, 62 (56.4%) were women, 88 (80%) were white, and the mean age was 61.8 ± 14.6 years. Forty (36.4%) patients received arterial imaging urgently. Patients suspected of third nerve palsy were not more likely to be sent for urgent evaluation (P = 0.29) or arterial imaging (P = 0.082) than patients in whom the referring doctor did not suspect palsy. Seventy-eight of 95 (82%) patients with a final diagnosis of third nerve palsy were correctly identified by referring providers. Of the 20 patients without any arterial imaging before neuro-ophthalmology consultation, there was a median delay of 24 days from symptom onset to imaging, and a median delay of 12.5 days between first medical contact for their symptoms and imaging. One patient was harmed as a result of delayed imaging.

CONCLUSIONS

Third nerve palsies were typically identified correctly, but referring providers failed to recognize the urgency of arterial imaging to rule out an aneurysmal etiology. Raising awareness of the urgency of arterial imaging may improve patient safety.

Diagnostic Error: Why Now?

Diagnostic errors remain relatively understudied and underappreciated. They are particularly concerning in the intensive care unit, where they are more likely to result in harm to patients. There is a lack of consensus on the definition of diagnostic error, and current methods to quantify diagnostic error have numerous limitations as noted in the sentinel report by the National Academy of Medicine. Although definitive definition and measurement remain elusive goals, increasing our understanding of diagnostic error is crucial if we are to make progress in reducing the incidence and harm caused by errors in diagnosis.

Learning from Missed Opportunities Through Reflective Practice

Identification of diagnostic errors is difficult but is not alone sufficient for performance improvement. Instead, cases must be reflected on to identify ways to improve decision-making in the future. There are many tools and modalities to retrospectively reflect on action to study medical decisions and outcomes and improve future performance. Reflection in action-in which diagnostic decisions are considered in real-time-may also improve medical decision-making especially through strategies such as structured reflection. Ongoing regular feedback can normalize the discussion about improving decision-making, enable reflective practice, and improve decision making.

Automated identification of diagnostic labelling errors in medicine

Objectives

Identification of diagnostic error is complex and mostly relies on expert ratings, a severely limited procedure. We developed a system that allows to automatically identify diagnostic labelling error from diagnoses coded according to the international classification of diseases (ICD), often available as routine health care data.

Methods

The system developed (index test) was validated against rater based classifications taken from three previous studies of diagnostic labeling error (reference standard). The system compares pairs of diagnoses through calculation of their distance within the ICD taxonomy. Calculation is based on four different algorithms. To assess the concordance between index test and reference standard, we calculated the area under the receiver operating characteristics curve (AUROC) and corresponding confidence intervals. Analysis were conducted overall and separately per algorithm and type of available dataset.

Results

Diagnoses of 1,127 cases were analyzed. Raters previously classified 24.58% of cases as diagnostic labelling errors (ranging from 12.3 to 87.2% in the three datasets). AUROC ranged between 0.821 and 0.837 overall, depending on the algorithm used to calculate the index test (95% CIs ranging from 0.8 to 0.86). Analyzed per type of dataset separately, the highest AUROC was 0.924 (95% CI 0.887–0.962).

Conclusions

The trigger system to automatically identify diagnostic labeling error from routine health care data performs excellent, and is unaffected by the reference standards’ limitations. It is however only applicable to cases with pairs of diagnoses, of which one must be more accurate or otherwise superior than the other, reflecting a prevalent definition of a diagnostic labeling error.

Health-seeking behaviour, views and preferences of adults with suspected increased intestinal permeability: A cross-sectional survey of Australian adults

Background

The public health consequence of increased intestinal permeability (IP) is currently limited by the lack of patient-centred research. This study aims to describe the health-seeking behaviour of Australian adults with suspected IP.

Methods

A cross-sectional survey of 589 Australian adults who have been diagnosed with IP or have suspected (undiagnosed) IP.

Results

The majority (56.2%) of participants with suspected IP reported self-diagnosing their condition, with the majority (56.7%) of these participants preferring to be assessed using an accurate method by a general practitioner or naturopath. On average, Australian adults with suspected IP spent 11.1 (95% CI: 9.5, 12.8) years between first suspecting IP and receiving a formal diagnosis. Over the previous 12 months, participants spent an average of $699 on consultation fees, $2176 on dietary supplements for the treatment of IP, and an average of $287 on the assessment of IP. Furthermore, participants who find it difficult to live on their available household income spent significantly more (mean=$2963) on dietary supplements compared to participants who find it easy to live on their available household income ($1918) (p=0.015).

Conclusion

The investigation of Australian adults with suspected IP found the majority of participants experienced a considerable length of time between first suspecting IP and receiving a diagnosis of IP. The out-of-pocket expenditure associated with the management of IP suggests a financial burden for people with suspected IP. The results of this study provide novel patient-centred considerations that can be used to inform a clinical practice guideline for the management of IP.

Comparison of Diagnostic Recommendations from Individual Physicians versus the Collective Intelligence of Multiple Physicians in Ambulatory Cases Referred for Specialist Consultation

BACKGROUND

Studies report higher diagnostic accuracy using the collective intelligence (CI) of multiple clinicians compared with individual clinicians. However, the diagnostic process is iterative, and unexplored is the value of CI in improving clinical recommendations leading to a final diagnosis.

METHODS

To compare the appropriateness of diagnostic recommendations advised by individual physicians versus the CI of physicians, we entered actual consultation requests sent by primary care physicians to specialists onto a web-based CI platform capable of collecting diagnostic recommendations (next steps for care) from multiple physicians. We solicited responses to 35 cases (12 endocrinology, 13 gynecology, 10 neurology) from ≥3 physicians of any specialty through the CI platform, which aggregated responses into a CI output. The primary outcome was the appropriateness of individual physician recommendations versus the CI output recommendations, using recommendations agreed upon by 2 specialists in the same specialty as a gold standard. The secondary outcome was the recommendations' potential for harm.

RESULTS

A total of 177 physicians responded. Cases had a median of 7 respondents (interquartile range: 5-10). Diagnostic recommendations in the CI output achieved higher levels of appropriateness (69%) than recommendations from individual physicians (45%; χ² = 5.95, P = 0.015). Of the CI recommendations, 54% were potentially harmful, as compared with 41% of individuals' recommendations (χ² = 2.49, P = 0.11).

LIMITATIONS

Cases were from a single institution. CI was solicited using a single algorithm/platform.

CONCLUSIONS

When seeking specialist guidance, diagnostic recommendations from the CI of multiple physicians are more appropriate than recommendations from most individual physicians, measured against specialist recommendations. Although CI provides useful recommendations, some have potential for harm. Future research should explore how to use CI to improve diagnosis while limiting harm from inappropriate tests/therapies.

Safer Stroke-Dx Instrument: Identifying Stroke Misdiagnosis in the Emergency Department

BACKGROUND

Missed or delayed diagnosis of acute stroke, or false-negative stroke (FNS), at initial emergency department (ED) presentation occurs in ≈9% of confirmed stroke patients. Failure to rapidly diagnose stroke can preclude time-sensitive treatments, resulting in higher risks of severe sequelae and disability. In this study, we developed and tested a modified version of a structured medical record review tool, the Safer Dx Instrument, to identify FNS in a subgroup of hospitalized patients with stroke to gain insight into sources of ED stroke misdiagnosis.

METHODS

We conducted a retrospective cohort study at 2 unaffiliated comprehensive stroke centers. In the development and confirmatory cohorts, we applied the Safer Stroke-Dx Instrument to report the prevalence and documented sources of ED diagnostic error in FNS cases among confirmed stroke patients upon whom an acute stroke was suspected by the inpatient team, as evidenced by stroke code activation or urgent neurological consultation, but not by the ED team. Inter-rater reliability and agreement were assessed using interclass coefficient and kappa values (κ).

RESULTS

Among 183 cases in the development cohort, the prevalence of FNS was 20.2% (95% CI, 15.0-26.7). Too narrow a differential diagnosis and limited neurological examination were common potential sources of error. The interclass coefficient for the Safer Stroke-Dx Instrument items ranged from 0.42 to 0.91, and items were highly correlated with each other. The κ for diagnostic error identification was 0.90 (95% CI, 0.821-0.978) using the Safer Stroke-Dx Instrument. In the confirmatory cohort of 99 cases, the prevalence of FNS was 21.2% (95% CI, 14.2-30.3) with similar sources of diagnostic error identified.

CONCLUSIONS

Hospitalized patients identified by stroke codes and requests for urgent neurological consultation represent an enriched population for the study of diagnostic error in the ED. The Safer Stroke-Dx Instrument is a reliable tool for identifying FNS and sources of diagnostic error.

Stroke hospitalization after misdiagnosis of "benign dizziness" is lower in specialty care than general practice: a population-based cohort analysis of missed stroke using SPADE methods

OBJECTIVES

Isolated dizziness is a challenging stroke presentation in the emergency department, but little is known about this problem in other clinical settings. We sought to compare stroke hospitalizations after treat-and-release clinic visits for purportedly "benign dizziness" between general and specialty care settings.

METHODS

This was a population-based retrospective cohort study from a national database. We included clinic patients with a first incident treat-and-release visit diagnosis of non-specific dizziness/vertigo or a peripheral vestibular disorder (ICD-9-CM 780.4 or 386.x [not 386.2]). We compared general care (internal medicine, family medicine) vs. specialty care (neurology, otolaryngology) providers. We used propensity scores to control for baseline stroke risk differences unrelated to dizziness diagnosis. We measured excess (observed>expected) stroke hospitalizations in the first 30 d (i.e., missed strokes associated with an adverse event).

RESULTS

We analyzed 144,355 patients discharged with "benign dizziness" (n=117,117 diagnosed in general care; n=27,238 in specialty care). After propensity score matching, patients in both groups were at higher risk of stroke in the first 30 d (rate difference per 10,000 treat-and-release visits for "benign dizziness" 24.9 [95% CI 18.6-31.2] in general care and 10.6 [95% CI 6.3-14.9] in specialty care). Short-term stroke risk was higher in general care than specialty care (relative risk, RR 2.2, 95% CI 1.5-3.2) while the long-term risk was not significantly different (RR 1.3, 95% CI 0.9-1.9), indicating higher misdiagnosis-related harms among dizzy patients who initially presented to generalists after adequate propensity matching.

CONCLUSIONS

Missed stroke-related harms in general care were roughly twice that in specialty care. Solutions are needed to address this care gap.

Monitoring Diagnostic Safety Risks in Emergency Departments: Protocol for a Machine Learning Study

BACKGROUND

Diagnostic decision making, especially in emergency departments, is a highly complex cognitive process that involves uncertainty and susceptibility to errors. A combination of factors, including patient factors (eg, history, behaviors, complexity, and comorbidity), provider-care team factors (eg, cognitive load and information gathering and synthesis), and system factors (eg, health information technology, crowding, shift-based work, and interruptions) may contribute to diagnostic errors. Using electronic triggers to identify records of patients with certain patterns of care, such as escalation of care, has been useful to screen for diagnostic errors. Once errors are identified, sophisticated data analytics and machine learning techniques can be applied to existing electronic health record (EHR) data sets to shed light on potential risk factors influencing diagnostic decision making.

OBJECTIVE

This study aims to identify variables associated with diagnostic errors in emergency departments using large-scale EHR data and machine learning techniques.

METHODS

This study plans to use trigger algorithms within EHR data repositories to generate a large data set of records that are labeled trigger-positive or trigger-negative, depending on whether they meet certain criteria. Samples from both data sets will be validated using medical record reviews, upon which we expect to find a higher number of diagnostic safety events in the trigger-positive subset. Machine learning will be used to evaluate relationships between certain patient factors, provider-care team factors, and system-level risk factors and diagnostic safety signals in the statistically matched groups of trigger-positive and trigger-negative charts.

RESULTS

This federally funded study was approved by the institutional review board of 2 academic medical centers with affiliated community hospitals. Trigger queries are being developed at both organizations, and sample cohorts will be labeled using the triggers. Machine learning techniques such as association rule mining, chi-square automated interaction detection, and classification and regression trees will be used to discover important variables that could be incorporated within future clinical decision support systems to help identify and reduce risks that contribute to diagnostic errors.

CONCLUSIONS

The use of large EHR data sets and machine learning to investigate risk factors (related to the patient, provider-care team, and system-level) in the diagnostic process may help create future mechanisms for monitoring diagnostic safety.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/24642.

Head Computed tomography during emergency department treat-and-release visit for headache is associated with increased risk of subsequent cerebrovascular disease hospitalization

OBJECTIVES

The occurrence of head computed tomography (HCT) at emergency department (ED) visit for non-specific neurological symptoms has been associated with increased subsequent stroke risk and may be a marker of diagnostic error. We evaluate whether HCT occurrence among ED headache patients is associated with increased subsequent cerebrovascular disease risk.

METHODS

We conducted a retrospective cohort study of consecutive adult patients with headache who were discharged home from the ED (ED treat-and-release visit) at one multicenter institution. Patients with headache were defined as those with primary ICD-9/10-CM discharge diagnoses codes for benign headache from 9/1/2013-9/1/2018. The primary outcome of cerebrovascular disease hospitalization was identified using ICD-9/10-CM codes and confirmed via chart review. We matched headache patients who had a HCT (exposed) to those who did not have a HCT (unexposed) in the ED in a one-to-one fashion using propensity score methods.

RESULTS

Among the 28,121 adult patients with ED treat-and-release headache visit, 45.6% (n=12,811) underwent HCT. A total of 0.4% (n=111) had a cerebrovascular hospitalization within 365 days of index visit. Using propensity score matching, 80.4% (n=10,296) of exposed patients were matched to unexposed. Exposed patients had increased risk of cerebrovascular hospitalization at 365 days (RR: 1.65: 95% CI: 1.18-2.31) and 180 days (RR: 1.62; 95% CI: 1.06-2.49); risk of cerebrovascular hospitalization was not increased at 90 or 30 days.

CONCLUSIONS

Having a HCT performed at ED treat-and-release headache visit is associated with increased risk of subsequent cerebrovascular disease. Future work to improve cerebrovascular disease prevention strategies in this subset of headache patients is warranted.

Missed acute myocardial infarction in the emergency department-standardizing measurement of misdiagnosis-related harms using the SPADE method

OBJECTIVES

Diagnostic error is a serious public health problem. Measuring diagnostic performance remains elusive. We sought to measure misdiagnosis-related harms following missed acute myocardial infarctions (AMI) in the emergency department (ED) using the symptom-disease pair analysis of diagnostic error (SPADE) method.

METHODS

Retrospective administrative data analysis (2009-2017) from a single, integrated health system using International Classification of Diseases (ICD) coded discharge diagnoses. We looked back 30 days from AMI hospitalizations for antecedent ED treat-and-release visits to identify symptoms linked to probable missed AMI (observed > expected). We then looked forward from these ED discharge diagnoses to identify symptom-disease pair misdiagnosis-related harms (AMI hospitalizations within 30-days, representing diagnostic adverse events).

RESULTS

A total of 44,473 AMI hospitalizations were associated with 2,874 treat-and-release ED visits in the prior 30 days. The top plausibly-related ED discharge diagnoses were "chest pain" and "dyspnea" with excess treat-and-release visit rates of 9.8% (95% CI 8.5-11.2%) and 3.4% (95% CI 2.7-4.2%), respectively. These represented 574 probable missed AMIs resulting in hospitalization (adverse event rate per AMI 1.3%, 95% CI 1.2-1.4%). Looking forward, 325,088 chest pain or dyspnea ED discharges were followed by 508 AMI hospitalizations (adverse event rate per symptom discharge 0.2%, 95% CI 0.1-0.2%).

CONCLUSIONS

The SPADE method precisely quantifies misdiagnosis-related harms from missed AMIs using administrative data. This approach could facilitate future assessment of diagnostic performance across health systems. These results correspond to ∼10,000 potentially-preventable harms annually in the US. However, relatively low error and adverse event rates may pose challenges to reducing harms for this ED symptom-disease pair.

Rate of sepsis hospitalizations after misdiagnosis in adult emergency department patients: a look-forward analysis with administrative claims data using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) methodology in an integrated health system

OBJECTIVES

Delays in sepsis diagnosis can increase morbidity and mortality. Previously, we performed a Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) "look-back" analysis to identify symptoms at risk for delayed sepsis diagnosis. We found treat-and-release emergency department (ED) encounters for fluid and electrolyte disorders (FED) and altered mental status (AMS) were associated with downstream sepsis hospitalizations. In this "look-forward" analysis, we measure the potential misdiagnosis-related harm rate for sepsis among patients with these symptoms.

METHODS

Retrospective cohort study using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (2013-2018). Patients ≥18 years with ≥1 treat-and-release ED encounter for FED or AMS were included. Observed greater than expected sepsis hospitalizations within 30 days of ED treat-and-release encounters were considered potential misdiagnosis-related harms. Temporal analyses were employed to differentiate case and comparison (superficial injury/contusion ED encounters) cohorts.

RESULTS

There were 4,549 treat-and-release ED encounters for FED or AMS, 26 associated with a sepsis hospitalization in the next 30 days. The observed (0.57%) minus expected (0.13%) harm rate was 0.44% (absolute) and 4.5-fold increased over expected (relative). There was a spike in sepsis hospitalizations in the week following FED/AMS ED visits. There were fewer sepsis hospitalizations and no spike in admissions in the week following superficial injury/contusion ED visits. Potentially misdiagnosed patients were older and more medically complex.

CONCLUSIONS

Potential misdiagnosis-related harms from sepsis are infrequent but measurable using SPADE. This look-forward analysis validated our previous look-back study, demonstrating the SPADE approach can be used to study infectious disease syndromes.

Diagnostic Error of Neuro-ophthalmologic Conditions: State of the Science

BACKGROUND

Diagnostic error is prevalent and costly, occurring in up to 15% of US medical encounters and affecting up to 5% of the US population. One-third of malpractice payments are related to diagnostic error. A complex and specialized diagnostic process makes neuro-ophthalmologic conditions particularly vulnerable to diagnostic error.

EVIDENCE ACQUISITION

English-language literature on diagnostic errors in neuro-ophthalmology and neurology was identified through electronic search of PubMed and Google Scholar and hand search.

RESULTS

Studies investigating diagnostic error of neuro-ophthalmologic conditions have revealed misdiagnosis rates as high as 60%-70% before evaluation by a neuro-ophthalmology specialist, resulting in unnecessary tests and treatments. Correct performance and interpretation of the physical examination, appropriate ordering and interpretation of neuroimaging tests, and generation of a differential diagnosis were identified as pitfalls in the diagnostic process. Most studies did not directly assess patient harms or financial costs of diagnostic error.

CONCLUSIONS

As an emerging field, diagnostic error in neuro-ophthalmology offers rich opportunities for further research and improvement of quality of care.

Antecedent treat-and-release diagnoses prior to sepsis hospitalization among adult emergency department patients: a look-back analysis employing insurance claims data using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) methodology

OBJECTIVES

The aim of this study was to identify delays in early pre-sepsis diagnosis in emergency departments (ED) using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach.

METHODS

SPADE methodology was employed using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (KPMAS). Study cohort included KPMAS members ≥18 years with ≥1 sepsis hospitalization 1/1/2013-12/31/2018. A look-back analysis identified treat-and-release ED visits in the month prior to sepsis hospitalizations. Top 20 diagnoses associated with these ED visits were identified; two diagnosis categories were distinguished as being linked to downstream sepsis hospitalizations. Observed-to-expected (O:E) and temporal analyses were performed to validate the symptom selection; results were contrasted to a comparison group. Demographics of patients that did and did not experience sepsis misdiagnosis were compared.

RESULTS

There were 3,468 sepsis hospitalizations during the study period and 766 treat-and-release ED visits in the month prior to hospitalization. Patients discharged from the ED with fluid and electrolyte disorders (FED) and altered mental status (AMS) were most likely to have downstream sepsis hospitalizations (O:E ratios of 2.66 and 2.82, respectively). Temporal analyses revealed that these symptoms were overrepresented and temporally clustered close to the hospitalization date. Approximately 2% of sepsis hospitalizations were associated with prior FED or AMS ED visits.

CONCLUSIONS

Treat-and-release ED encounters for FED and AMS may represent harbingers for downstream sepsis hospitalizations. The SPADE approach can be used to develop performance measures that identify pre-sepsis.

Time-ordered comorbidity correlations identify patients at risk of mis- and overdiagnosis

Diagnostic errors are common and can lead to harmful treatments. We present a data-driven, generic approach for identifying patients at risk of being mis- or overdiagnosed, here exemplified by chronic obstructive pulmonary disease (COPD). It has been estimated that 5-60% of all COPD cases are misdiagnosed. High-throughput methods are therefore needed in this domain. We have used a national patient registry, which contains hospital diagnoses for 6.9 million patients across the entire Danish population for 21 years and identified statistically significant disease trajectories for COPD patients. Using 284,154 patients diagnosed with COPD, we identified frequent disease trajectories comprising time-ordered comorbidities. Interestingly, as many as 42,459 patients did not present with these time-ordered, common comorbidities. Comparison of the individual disease history for each non-follower to the COPD trajectories, demonstrated that 9597 patients were unusual. Survival analysis showed that this group died significantly earlier than COPD patients following a trajectory. Out of the 9597 patients, we identified one subgroup comprising 2185 patients at risk of misdiagnosed COPD without the typical events of COPD patients. In all, 10% of these patients were diagnosed with lung cancer, and it seems likely that they are underdiagnosed for lung cancer as their laboratory test values and survival pattern are similar to such patients. Furthermore, only 4% had a lung function test to confirm the COPD diagnosis. Another subgroup with 2368 patients were found to be at risk of "classically" overdiagnosed COPD that survive >5.5 years after the COPD diagnosis, but without the typical complications of COPD.

Learning from tragedy - The Jessica Barnett story: challenges in the diagnosis of long QT syndrome

We describe the case of Jessica Barnett, an adolescent girl whose repeated episodes of syncope and near-syncope were ascribed to a seizure or anxiety disorder. The correct diagnoses (congenital long QT syndrome; arrythmogenic right ventricular cardiomyopathy) were established by autopsy and genetic studies only after her death at age 17. The perspective of the family is presented, along with an analysis of what went right and what went wrong in Jessica's diagnostic journey. Key lessons in this case include the value of family as engaged members of the diagnostic team, that a 'hyperventilation test' should not be used to exclude cardiac origins of syncope or pre-syncope, and the inherent challenges in the diagnosis of the long QT syndrome.

Breakdowns in the initial patient-provider encounter are a frequent source of diagnostic error among ischemic stroke cases included in a large medical malpractice claims database

Background Misdiagnosis of dangerous cerebrovascular disease is a substantial public health problem. We sought to identify and describe breakdowns in the diagnostic process among patients with ischemic stroke to facilitate future improvements in diagnostic accuracy. Methods We performed a retrospective, descriptive study of medical malpractice claims housed in the Controlled Risk Insurance Company (CRICO) Strategies Comparative Benchmarking System (CBS) database from 1/1/2006 to 1/1/2016 involving ischemic stroke patients. Baseline claimant demographics, clinical setting, primary allegation category, and outcomes were abstracted. Among cases with a primary diagnosis-related allegation, we detail presenting symptoms and diagnostic breakdowns using CRICO's proprietary taxonomy. Results A total of 478 claims met inclusion criteria; 235 (49.2%) with diagnostic error. Diagnostic errors originated in the emergency department (ED) in 46.4% (n = 109) of cases, outpatient clinic in 27.7% (n = 65), and inpatient setting in 25.1% (n = 59). Across care-settings, the most frequent process breakdown was in the initial patient-provider encounter [76.2% (n = 179 cases)]. Failure to assess, communicate, and respond to ongoing symptoms was the component of the patient-provider encounter most frequently identified as a source of misdiagnosis in the ED. Exclusively non-traditional presenting symptoms occurred in 35.7% (n = 84), mixed traditional and non-traditional symptoms in 30.6% (n = 72), and exclusively traditional in 23.8% (n = 56) of diagnostic error cases. Conclusions Among ischemic stroke patients, breakdowns in the initial patient-provider encounter were the most frequent source of diagnostic error. Targeted interventions should focus on the initial diagnostic encounter, particularly for ischemic stroke patients with atypical symptoms.

Controversies in diagnosis: contemporary debates in the diagnostic safety literature

Since the 2015 publication of the National Academy of Medicine's (NAM) Improving Diagnosis in Health Care (Improving Diagnosis in Health Care. In: Balogh EP, Miller BT, Ball JR, editors. Improving Diagnosis in Health Care. Washington (DC): National Academies Press, 2015.), literature in diagnostic safety has grown rapidly. This update was presented at the annual international meeting of the Society to Improve Diagnosis in Medicine (SIDM). We focused our literature search on articles published between 2016 and 2018 using keywords in Pubmed and the Agency for Healthcare Research and Quality (AHRQ)'s Patient Safety Network's running bibliography of diagnostic error literature (Diagnostic Errors Patient Safety Network: Agency for Healthcare Research and Quality; Available from: https://psnet.ahrq.gov/search?topic=Diagnostic-Errors&f_topicIDs=407). Three key topics emerged from our review of recent abstracts in diagnostic safety. First, definitions of diagnostic error and related concepts are evolving since the NAM's report. Second, medical educators are grappling with new approaches to teaching clinical reasoning and diagnosis. Finally, the potential of artificial intelligence (AI) to advance diagnostic excellence is coming to fruition. Here we present contemporary debates around these three topics in a pro/con format.

Patient Safety in Ambulatory Pediatrics

Purpose of Review

The majority of patient care occurs in the ambulatory setting, and pediatric patients are at high risk of medical error and harm. Prior studies have described various safety threats in ambulatory pediatrics, and little is known about effective strategies to minimize error. The purpose of this review is to identify best practices for optimizing safety in ambulatory pediatrics.

Recent Findings

The majority of the patient safety literature in ambulatory pediatrics describes frequencies and types of medical errors. Study of effective interventions to reduce error, and particularly to reduce harm, have been limited. There is evidence that medical complexity and social context are important modifiers of risk. Telemedicine has emerged as a care delivery model with potential to ameliorate and exacerbate safety threats. Though there is variation across studies, developing a safety culture, partnerships with patients and families, and use of structured communication are strategies that support patient safety.

Summary

There is no standardized taxonomy for errors in ambulatory pediatrics, but errors related to medications, vaccines, diagnosis, and care coordination and care transitions are commonly described. Evidence-based approaches to optimize safety include standardized prescribing and medication reconciliation practices, appropriate use of decision support tools in the electronic health record, and communication strategies like teach-back. Further high-quality intervention studies in pediatric ambulatory care that assess impact on patient harm and clinical outcomes should be prioritized.

Rate of diagnostic errors and serious misdiagnosis-related harms for major vascular events, infections, and cancers: toward a national incidence estimate using the “Big Three”

Background

Missed vascular events, infections, and cancers account for ~75% of serious harms from diagnostic errors. Just 15 diseases from these “Big Three” categories account for nearly half of all serious misdiagnosis-related harms in malpractice claims. As part of a larger project estimating total US burden of serious misdiagnosis-related harms, we performed a focused literature review to measure diagnostic error and harm rates for these 15 conditions.

Methods

We searched PubMed, Google, and cited references. For errors, we selected high-quality, modern, US-based studies, if available, and best available evidence otherwise. For harms, we used literature-based estimates of the generic (disease-agnostic) rate of serious harms (morbidity/mortality) per diagnostic error and applied claims-based severity weights to construct disease-specific rates. Results were validated via expert review and comparison to prior literature that used different methods. We used Monte Carlo analysis to construct probabilistic plausible ranges (PPRs) around estimates.

Results

Rates for the 15 diseases were drawn from 28 published studies representing 91,755 patients. Diagnostic error (false negative) rates ranged from 2.2% (myocardial infarction) to 62.1% (spinal abscess), with a median of 13.6% [interquartile range (IQR) 9.2–24.7] and an aggregate mean of 9.7% (PPR 8.2–12.3). Serious misdiagnosis-related harm rates per incident disease case ranged from 1.2% (myocardial infarction) to 35.6% (spinal abscess), with a median of 5.5% (IQR 4.6–13.6) and an aggregate mean of 5.2% (PPR 4.5–6.7). Rates were considered face valid by domain experts and consistent with prior literature reports.

Conclusions

Diagnostic improvement initiatives should focus on dangerous conditions with higher diagnostic error and misdiagnosis-related harm rates.

Consensus recommendations on the classification, definition and diagnostic criteria of hip-related pain in young and middle-aged active adults from the International Hip-related Pain Research Network, Zurich 2018

There is no agreement on how to classify, define or diagnose hip-related pain-a common cause of hip and groin pain in young and middle-aged active adults. This complicates the work of clinicians and researchers. The International Hip-related Pain Research Network consensus group met in November 2018 in Zurich aiming to make recommendations on how to classify, define and diagnose hip disease in young and middle-aged active adults with hip-related pain as the main symptom. Prior to the meeting we performed a scoping review of electronic databases in June 2018 to determine the definition, epidemiology and diagnosis of hip conditions in young and middle-aged active adults presenting with hip-related pain. We developed and presented evidence-based statements for these to a panel of 37 experts for discussion and consensus agreement. Both non-musculoskeletal and serious hip pathological conditions (eg, tumours, infections, stress fractures, slipped capital femoral epiphysis), as well as competing musculoskeletal conditions (eg, lumbar spine) should be excluded when diagnosing hip-related pain in young and middle-aged active adults. The most common hip conditions in young and middle-aged active adults presenting with hip-related pain are: (1) femoroacetabular impingement (FAI) syndrome, (2) acetabular dysplasia and/or hip instability and (3) other conditions without a distinct osseous morphology (labral, chondral and/or ligamentum teres conditions), and that these terms are used in research and clinical practice. Clinical examination and diagnostic imaging have limited diagnostic utility; a comprehensive approach is therefore essential. A negative flexion-adduction-internal rotation test helps rule out hip-related pain although its clinical utility is limited. Anteroposterior pelvis and lateral femoral head-neck radiographs are the initial diagnostic imaging of choice-advanced imaging should be performed only when requiring additional detail of bony or soft-tissue morphology (eg, for definitive diagnosis, research setting or when planning surgery). We recommend clear, detailed and consistent methodology of bony morphology outcome measures (definition, measurement and statistical reporting) in research. Future research on conditions with hip-related pain as the main symptom should include high-quality prospective studies on aetiology and prognosis. The most common hip conditions in active adults presenting with hip-related pain are: (1) FAI syndrome, (2) acetabular dysplasia and/or hip instability and (3) other conditions without distinct osseous morphology including labral, chondral and/or ligamentum teres conditions. The last category should not be confused with the incidental imaging findings of labral, chondral and/or ligamentum teres pathology in asymptomatic people. Future research should refine our current recommendations by determining the clinical utility of clinical examination and diagnostic imaging in prospective studies.

Understanding the roles of three academic communities in a prospective learning health ecosystem for diagnostic excellence

Inaccurate, untimely, and miscommunicated medical diagnoses represent a wicked problem requiring comprehensive and coordinated approaches, such as those demonstrated in the characteristics of learning health systems (LHSs). To appreciate a vision for how LHS methods can optimize processes and outcomes in medical diagnosis (diagnostic excellence), we interviewed 32 individuals with relevant expertise: 18 who have studied diagnostic processes using traditional behavioral science and health services research methods, six focused on machine learning (ML) and artificial intelligence (AI) approaches, and eight multidisciplinary researchers experienced in advocating for and incorporating LHS methods, ie, scalable continuous learning in health care. We report on barriers and facilitators, identified by these subjects, to applying their methods toward optimizing medical diagnosis. We then employ their insights to envision the emergence of a learning ecosystem that leverages the tools of each of the three research groups to advance diagnostic excellence. We found that these communities represent a natural fit forward, in which together, they can better measure diagnostic processes and close the loop of putting insights into practice. Members of the three academic communities will need to network and bring in additional stakeholders before they can design and implement the necessary infrastructure that would support ongoing learning of diagnostic processes at an economy of scale and scope.

Referral Patterns in Neuro-Ophthalmology

BACKGROUND

Neuro-ophthalmologists specialize in complex, urgent, vision- and life-threatening problems, diagnostic dilemmas, and management of complex work-ups. Access is currently limited by the relatively small number of neuro-ophthalmologists, and consequently, patients may be affected by incorrect or delayed diagnosis. The objective of this study is to analyze referral patterns to neuro-ophthalmologists, characterize rates of misdiagnoses and delayed diagnoses in patients ultimately referred, and delineate outcomes after neuro-ophthalmologic evaluation.

METHODS

Retrospective chart review of 300 new patients seen over 45 randomly chosen days between June 2011 and June 2015 in one tertiary care neuro-ophthalmology clinic. Demographics, distance traveled, time between onset and neuro-ophthalmology consultation (NOC), time between appointment request and NOC, number and types of providers seen before referral, unnecessary tests before referral, referral diagnoses, final diagnoses, and impact of the NOC on outcome were collected.

RESULTS

Patients traveled a median of 36.5 miles (interquartile range [IQR]: 20-85). Median time from symptom onset was 210 days (IQR: 70-1,100). Median time from referral to NOC was 34 days (IQR: 7-86), with peaks at one week (urgent requests) and 13 weeks (routine requests). Median number of previous providers seen was 2 (IQR: 2-4; range:0-10), and 102 patients (34%) had seen multiple providers within the same specialty before referral. Patients were most commonly referred for NOC by ophthalmologists (41% of referrals). Eighty-one percent (242/300) of referrals to neuro-ophthalmology were appropriate referrals. Of the 300 patients referred, 247 (82%) were complex or very complex; 119 (40%) were misdiagnosed; 147 (49%) were at least partially misdiagnosed; and 22 (7%) had unknown diagnoses. Women were more likely to be at least partially misdiagnosed-108 of 188 (57%) vs 39 of 112 (35%) of men (P < 0.001). Mismanagement or delay in care occurred in 85 (28%), unnecessary tests in 56 (19%), unnecessary consultations in 64 (22%), and imaging misinterpretation in 16 (5%). Neuro-ophthalmologists played a major role in directing treatment, such as preserving vision, preventing life-threatening complications, or avoiding harmful treatment in 62 (21%) patients.

CONCLUSIONS

Most referrals to neuro-ophthalmologists are appropriate, but many are delayed. Misdiagnosis before referral is common. Neuro-ophthalmologists often prevent vision- and life-threatening complications.

Strategies to reduce diagnostic errors: a systematic review

Background

To evaluate the effectiveness of audit and communication strategies to reduce diagnostic errors made by clinicians.

Methods

MEDLINE complete, CINHAL complete, EMBASE, PSNet and Google Advanced. Electronic and manual search of articles on audit systems and communication strategies or interventions, searched for papers published between January 1990 and April 2017. We included studies with interventions implemented by clinicians in a clinical environment with real patients.

Results

A total of 2431 articles were screened of which 26 studies met inclusion criteria. Data extraction was conducted by two groups, each group comprising two independent reviewers. Articles were classified by communication (6) or audit strategies (20) to reduce diagnostic error in clinical settings. The most common interventions were delivered as technology-based systems n = 16 (62%) and within an acute care setting n = 15 (57%). Nine studies reported randomised controlled trials. Three RCT studies on communication interventions and 3 RCTs on audit strategies found the interventions to be effective in reducing diagnostic errors.

Conclusion

Despite numerous studies on interventions targeting diagnostic errors, our analyses revealed limited evidence on interventions being practically used in clinical settings and a bias of studies originating from the US (n = 19, 73% of included studies). There is some evidence that trigger algorithms, including computer based and alert systems, may reduce delayed diagnosis and improve diagnostic accuracy. In trauma settings, strategies such as additional patient review (e.g. trauma teams) reduced missed diagnosis and in radiology departments review strategies such as team meetings and error documentation may reduce diagnostic error rates over time.

Trial registration

The systematic review was registered in the PROSPERO database under registration number CRD42017067056.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0901-1) contains supplementary material, which is available to authorized users.

Serious misdiagnosis-related harms in malpractice claims: The “Big Three” – vascular events, infections, and cancers

Background

Diagnostic errors cause substantial preventable harm, but national estimates vary widely from 40,000 to 4 million annually. This cross-sectional analysis of a large medical malpractice claims database was the first phase of a three-phase project to estimate the US burden of serious misdiagnosis-related harms.

Methods

We sought to identify diseases accounting for the majority of serious misdiagnosis-related harms (morbidity/mortality). Diagnostic error cases were identified from Controlled Risk Insurance Company (CRICO)’s Comparative Benchmarking System (CBS) database (2006–2015), representing 28.7% of all US malpractice claims. Diseases were grouped according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS) that aggregates the International Classification of Diseases diagnostic codes into clinically sensible groupings. We analyzed vascular events, infections, and cancers (the “Big Three”), including frequency, severity, and settings. High-severity (serious) harms were defined by scores of 6–9 (serious, permanent disability, or death) on the National Association of Insurance Commissioners (NAIC) Severity of Injury Scale.

Results

From 55,377 closed claims, we analyzed 11,592 diagnostic error cases [median age 49, interquartile range (IQR) 36–60; 51.7% female]. These included 7379 with high-severity harms (53.0% death). The Big Three diseases accounted for 74.1% of high-severity cases (vascular events 22.8%, infections 13.5%, and cancers 37.8%). In aggregate, the top five from each category (n = 15 diseases) accounted for 47.1% of high-severity cases. The most frequent disease in each category, respectively, was stroke, sepsis, and lung cancer. Causes were disproportionately clinical judgment factors (85.7%) across categories (range 82.0–88.8%).

Conclusions

The Big Three diseases account for about three-fourths of serious misdiagnosis-related harms. Initial efforts to improve diagnosis should focus on vascular events, infections, and cancers.