Title | Diagnostic Error of Neuro-ophthalmologic Conditions: State of the Science |
Creator | Leanne Stunkel, MD; David E. Newman-Toker, MD, PhD; Nancy J. Newman, MD; Valérie Biousse, MD |
Subject | Diagnostic Errors |
Description | 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. |
OCR Text | Show State-of-the-Art Review Section Editors: Fiona Costello, MD, FRCP(C) Sashank Prasad, MD Diagnostic Error of Neuro-ophthalmologic Conditions: State of the Science Leanne Stunkel, MD, David E. Newman-Toker, MD, PhD, Nancy J. Newman, MD, Valérie Biousse, MD Downloaded from http://journals.lww.com/jneuro-ophthalmology by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 01/20/2021 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 neuroophthalmologic 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 neuroophthalmologic conditions have revealed misdiagnosis rates as high as 60%–70% before evaluation by a neuroophthalmology specialist, resulting in unnecessary tests and treatments. Correct performance and interpretation of the physical examination, appropriate ordering and interDepartments of Ophthalmology and Visual Sciences (LS) and Neurology (LS), Washington University in St. Louis School of Medicine, St. Louis, Missouri; Department of Neurology (DEN-T), The Johns Hopkins University School of Medicine, Baltimore, Maryland; and Departments of Ophthalmology (NJN, VB), Neurology (NJN, VB), and Neurological Surgery (NJN), Emory University School of Medicine, Atlanta, Georgia. V. Biousse and N. J. Newman are supported in part by NIH/NEI core grant P30-EY06360 (Department of Ophthalmology, Emory University School of Medicine) and by NIH/NINDS (RO1NSO89694). D. E. Newman-Toker’s effort is supported by the Armstrong Institute Center for Diagnostic Excellence. N. J. Newman is a consultant for GenSight, Santhera, Neurophoenix, and Stealth. N. J. Newman is a member of the Data Safety Monitoring Board for Quark Pharmaceuticals’ NAION clinical trial. V. Biousse is a consultant for GenSight and Neurophoenix. D. E. Newman-Toker conducts research related to diagnostic error, including serving as the principal investigator for grants on this topic. He serves as an unpaid member of the Board of Directors of the Society to Improve Diagnosis in Medicine and as its current president. He serves as a medicolegal consultant for both plaintiff and defense in cases related to diagnostic error. The remaining authors report no conflicts of interest. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www. jneuro-ophthalmology.com). Address correspondence to Valérie Biousse, MD, Emory Eye Center, 1365b Clifton Road, Atlanta, GA 30322; E-mail: bviouss@emory.edu Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 pretation 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 neuroophthalmology offers rich opportunities for further research and improvement of quality of care. Journal of Neuro-Ophthalmology 2020;00:1–16 doi: 10.1097/WNO.0000000000001031 © 2020 by North American Neuro-Ophthalmology Society T he US National Academy of Medicine describes improving diagnosis as a “moral, professional, and public health imperative.” (1) Diagnostic error is prevalent and lethal, with a death toll of 40,000–80,000 people per year in US hospitals alone (2). Correct diagnosis is a prerequisite for providing appropriate medical treatment, yet experts suggest that diagnostic errors may occur in 10%– 15% of all medical encounters in the United States, and an estimated 12 million Americans are affected by diagnostic error each year in outpatient settings alone (3). Diagnostic errors account for more than one-third of malpractice payments (4,5), and the percentage is higher in analytic, diagnosis-oriented fields (5). Investigation into diagnostic errors is an emerging field, and accurate measurement of diagnostic error is methodologically challenging (6). The study of neuroophthalmologic conditions provides a unique opportunity for improving our understanding of complex diagnostic processes and diagnostic error (Tables 1–4). Neuroophthalmologic conditions require a time-intensive diagnostic process, including a detailed examination by a provider with specialized training (36–40). However, not every patient can access a neuro-ophthalmologist—patients often face long wait times and travel long distances (10,39–43). Indeed, 6 US states have no neuro-ophthalmologist, and the national average wait time for a new patient appointment is 6–7 weeks (L. Frohman, Oral communication). Typically, 1 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review patients first present to ophthalmologists, optometrists, emergency departments, neurologists, and primary care physicians (10), and rates of diagnostic error of neuroophthalmologic conditions before evaluation by a neuroophthalmology specialist may be as high as 60%–70% (7,9–17), resulting in mismanagement, delayed diagnosis, worse outcomes, and increased costs. In this narrative review, we assess the current state of evidence related to diagnostic error in neuroophthalmology, including terminology, methods, key conditions, limitations of existing research, and lessons that may be learned from related fields. DEFINING AND MEASURING DIAGNOSTIC ERROR The US National Academy of Medicine defines a diagnostic error as 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 (1). This definition of diagnostic error can be more specifically termed a diagnostic label failure (44), essentially meaning failure to assign the correct name to a diagnosis. Misdiagnosis-related harms are defined as harms that result from a delay or failure to treat the true conditions that occur in the setting of a wrong or unknown diagnosis (45,46). Identifying diagnostic label failures may be incomplete. An additional aspect of diagnostic error is diagnostic process failure (44), meaning an inappropriate diagnostic approach, which may or may not in all cases correspond with a diagnostic label failure. For example, imagine a pupil-involving third nerve palsy that is (a) correctly identified in a general eye clinic, (b) correctly attributed to diabetes, and (c) referred to an outpatient neuro-ophthalmology clinic, without urgent neuroimaging. There was no diagnostic label failure because the correct diagnosis was made. However, there was a diagnostic process failure, in that the delay in imaging could have led to a fatal outcome if an aneurysm had been missed. Diagnostic process problems such as this are “near misses” that represent latent errors and may not be captured when studying diagnostic errors or misdiagnosis-related harms. A BRIEF UPDATE ON TERMINOLOGY The term “overdiagnosis” has been used in the neuroophthalmic literature to describe false-positive misdiagnoses (12–14,16). However, the standard meaning of “overdiagnosis” is “the diagnosis of an inconsequential disease” (44,47–49), so the term should not be used to describe false positives. These should instead be called “misdiagnosed-inexcess,” “wrong,” “incorrect,” or “false-positive” misdiagnoses. Similarly, the term “underdiagnosis” has been used in the neuro-ophthalmologic literature to describe falsenegative diagnoses (11). Standard usage within the wider field of diagnostic error would instead suggest these should 2 be called “missed,” “delayed,” or “false-negative” misdiagnoses. It should also be noted that most cases of diagnostic error could be characterized as both a false positive and a false negative, depending on the perspective of the provider. For example, tension-type headache that is misdiagnosed as idiopathic intracranial hypertension (IIH) is both a falsenegative diagnosis of tension-type headache and a falsepositive diagnosis of IIH (44). THE DEER CRITERIA The Diagnosis Error Evaluation and Research (DEER) taxonomy was designed to categorize different stages of the diagnostic process that causally relates to diagnostic errors with the goal of identifying high-yield intervention targets (see Supplemental Digital Content, Table E1, http:// links.lww.com/WNO/A426) (50,51). Fisayo et al (13) were the first neuro-ophthalmology group to apply any formalized tool to categorize the root cause or contributors to a diagnostic error. Since then, several studies of diagnostic error in neuro-ophthalmology (12,16,17) have applied this tool to better identify causal diagnostic process failures. The DEER taxonomy, although an important step toward formalizing the process of evaluating etiologies of diagnostic error, nevertheless has 2 important limitations. First, the retrospective assignment of an error’s cause is unavoidably subjective. Second, errors are often multifactorial. Assessment of multifactorial errors is problematic, especially because earlier errors may create conditions that allow additional errors to occur. For example, a poorly performed physical examination may influence inaccurate generation of the differential diagnosis. Different studies have confronted multifactorial error in different ways. For example, some studies have designating the earliest or most proximal error as the most causative (16)—this means that if a poor physical examination led to an inaccurate differential diagnosis, the DEER category assigned would be the error in performing the physical examination (Category 3A). Alternately, other studies have assigned multiple causes of error to a single case (17)—this means that if a poor physical examination led to an inaccurate differential diagnosis, both the error in performing the physical examination (3A) and the inaccurate generation of a differential diagnosis (Category 5A) would be assigned. DIAGNOSTIC ERROR IN NEUROOPHTHALMOLOGIC CONDITIONS That neuro-ophthalmologic conditions are frequently misdiagnosed is well known to neuro-ophthalmologists (36). In the 1960s, neuro-ophthalmologist David Cogan bemoaned the “abundance of erroneous diagnoses” of optic neuritis (52). There has been significant research into diagnostic error in neuro-otology, particularly into differentiating central vs. peripheral etiologies of acute dizziness presentations (Table 4) (18–35). However, only a handful of studies have Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review TABLE 1. Studies examining diagnostic error in multiple neuro-ophthalmologic conditions Source Dillon et al (7) Design/Dates Retrospective review Population Condition(s) Outcome(s) of Interest Misdiagnosis Rate DEER Taxonomy 588 consecutive new patients Optic neuropathy, diplopia, ptosis, and proptosis Unnecessary or substandard tests before referral Harm Economic costs N/A No 8 illustrative cases Various MRI insufficient to assess neuroophthalmologic conditions N/A No 84 consecutive new patients who had previously undergone diagnostic imaging Various Suboptimal imaging studies 69% incorrect referral diagnosis 23% discordant radiology interpretation No 49% No Wills Eye 1989 Wolintz et al (8) Qualitative/case series U of Michigan and Washington Hospital Center Dates unspecified McClelland et al (9) Prospective cohort study Washington U St. Louis 2009–2010 Stunkel et al (10) Retrospective review 300 new patients Various Emory 2011–2015 Characteristics of neuroophthalmology referrals Summary 20% had unnecessary tests before referral, and additional tests were substandard None suffered direct harm due to the diagnostic delay or unnecessary tests Economic costs could not be calculated because of methodologic limitations Pitfalls in obtaining an optimal study: wrong study or wrong sequences or no contrast. Pitfalls in imaging interpretation: failure to provide a neuroradiologist with appropriate clinical information, overweighing the absence of an expected finding, overweighing the presence of an incidental unrelated finding, and failure to generate an appropriate differential diagnosis for the imaging findings 38% suboptimal imaging to answer the correct clinical question 29% required additional imaging 3 most common reasons for suboptimal studies: incomplete area of imaging, wrong study type, and poor image quality 28% mismanaged or delayed care, 19% had unnecessary tests, 22% unnecessary consultations, and 5% misinterpreted imaging Access to neuroophthalmology is limited. Patients traveled long distances (.100 miles in 20% of cases), faced long wait times (median time from symptom onset 7 mo), and saw multiple previous providers (76% saw multiple previous providers and 34% saw multiple previous providers within the same specialty). DEER, Diagnosis Error Evaluation and Research; N/A, not applicable; U, University. Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 3 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review TABLE 2. Studies examining diagnostic errors in cranial nerve 3 palsies Source Design/ Dates of Collection Population Condition(s) Elmalem et al (11) Retrospective 17 patients review Emory 2010 Schroeder et al (12) Retrospective 78 new patients CN3 palsy review referred for CN3 palsy 2014–2017 Washington U St. Louis and Michigan State U Outcome(s) of Interest CN3 palsy due to Missed diagnosis Pcomm (MRA/CTA that aneurysm showed a Pcomm aneurysm incorrectly read as normal) Misdiagnosis (not CN3 palsy) Unnecessary interventions Causes of diagnostic errors Misdiagnosis DEER Rate Taxonomy 47% No 22% Yes Summary Misinterpretation more likely when radiologists did not have training in neuroradiology or inaccurate clinical information was provided in interpreting radiologists 53% of misdiagnosed had unnecessary imaging 71% of errors were in performance or interpretation of the physical examination CN3, cranial nerve 3; CTA, computed tomography angiogram; DEER, Diagnosis Error Evaluation and Research; Pcomm, posterior communicating artery; U, University. attempted to formally measure diagnostic error of neuroophthalmologic conditions (Tables 1–3) (7–17). Studies Examining Diagnostic Error of Neuroophthalmologic Conditions in General Several studies (7–10) have explored the diagnostic process for various neuro-ophthalmologic conditions before neuroophthalmologic consultation (Table 1). These studies have shown a high rate of misdiagnosis (up to 69%) (9,10) and identified neuroimaging as a common source of error. Diagnostic errors were frequently traced in choosing an incorrect scan type and/or scan emphasis to answer the relevant clinical question and failure to use contrast material when appropriate (e.g., ordering a brain MRI without contrast instead of a dedicated orbital MRI with contrast and fat suppression for an isolated optic neuropathy), and misinterpretation of imaging findings (such as incorrectly attributing symptoms to an incidental finding on imaging; e.g., incidental empty sella on the MRI of a patient with isolated chronic headaches subsequently misdiagnosed as IIH despite the lack of papilledema). High-yield targets for improving diagnostic accuracy include careful selection of imaging based on clinical examination and providing the radiologist with accurate and complete clinical information. Optic Neuropathies and Optic Disc Edema Several studies have focused on diagnostic accuracy for conditions affecting the optic nerve, including IIH (13), optic nerve sheath meningioma (17), and intracranial 4 hypertension due to a meningioma compressing the venous sinuses (15) or the role of accurate identification of optic disc edema (14) (Table 2). These have uncovered high rates of diagnostic error—up to 60% for common conditions such as optic neuritis (16) and up to 71% for diagnostic delay of uncommon conditions such as optic nerve sheath meningioma (15,17). Misdiagnosis of optic neuropathies was commonly attributable to poor history taking, difficulty with the examination (particularly assessing for a relative afferent pupillary defect and performing an accurate fundus examination), generation of an incomplete differential diagnosis, and suboptimal use of imaging studies (insufficient studies to rule out alternative etiologies, incorrect study type, poor interpretation by radiologists, or underweighing a normal imaging result). Diagnostic error of conditions affecting the optic nerve can lead to poor visual outcomes, as well as unnecessary tests and treatments. Cranial Nerve 3 Palsies Poor performance or interpretation of the physical examination is a frequent source of error in diagnosis of cranial nerve 3 palsies (12). Diagnostic imaging interpretation was noted to be a pitfall in the identification of aneurysmal compression (11), consistent with other studies of diagnostic error of neuro-ophthalmologic conditions (7,9,10). Targets for improvement include providing the radiologist with appropriate clinical information and interpretation of images only by radiologists with subspecialty training in neuroradiology (Table 3). Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review TABLE 3. Studies examining diagnostic errors in papilledema and optic neuropathies Source Design/Dates of Collection Papilledema Fisayo et al (13) Retrospective review Emory 2013–2014 Blanch et al (14) Avon, UK Prospective Hartmann et al (15) Retrospective 2012–2016 Washington U St. Louis Misdiagnosis Rate DEER Taxonomy Misdiagnosis (not IIH) Unnecessary interventions Causes of diagnostic errors 40% Yes Correct identification of papilledema based on fundus photographs alone 21% N/A 16 patients with Intracranial hypertension intracranial secondary to hypertension compression of secondary to dural venous compression sinus by of dural meningioma venous sinus Delayed diagnosis of compression of the dural venous sinus 63% No 122 new patients referred for optic neuritis Misdiagnosis (not optic neuritis) Unnecessary interventions Causes of diagnostic errors 60% Yes Condition(s) 165 consecutive IIH new patients referred for IIH Papilledema 16 clinicians rated fundus photographs Dates unspecified from 198 (12 to 14 yr olds) Emory, Minnesota U, and Wills Eye Optic neuropathies Stunkel et al (16) Outcome(s) of Interest Population Retrospective crosssectional study 2016–2017 Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Optic neuritis Summary In misdiagnosed patients: 80% had LP 85% had brain MRI 24% had MRV/CTV 76% had medical treatment 1 underwent lumbar drain 24% had an alternative diagnosis that was delayed due to misdiagnosis Most common errors: Inaccurate ophthalmoscopic examination Thinking biases Detection of papilledema on fundus photographs had high sensitivity but low specificity, ranging from 53% among ED physicians to 90% among neurologists. 21% false-positive rate, suggesting likely unnecessary interventions 40% of misdiagnosed patients had poor visual outcomes Common errors: Failure to recognize that the meningioma involving the dural venous sinus was the cause of the intracranial hypertension Failure to obtain MRV as part of the initial evaluation 16% had normal MRI preceding referral 16% had unnecessary LP 11% received unnecessary IV steroids Most common errors: Failure in taking a history Failure to generate an appropriate differential diagnosis Overweighing subjective aspects of the examination (i.e., red desaturation) Failure to check for an RAPD Misinterpretation of diagnostic imaging results 5 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review (Continued ) Source Design/Dates of Collection Kahraman-Koytak (17) Retrospective review Emory 2002–2017 Population Condition(s) 35 patients with ONSM ONSM Outcome(s) of Interest Misdiagnosis Rate DEER Taxonomy Delayed diagnosis of ONSM Visual outcomes Unnecessary interventions Causes of diagnostic errors 71% Yes Summary 64% had poor visual outcomes Unnecessary interventions based on misdiagnosis: 20% had LP 48% had labs 24% had steroids 1 underwent laser treatment for presumed retinal disease Multifactorial errors in 51% of cases, including: Failure to do a fundus examination Misinterpretation of history Failure to obtain the correct scan or sequences and/or interpret it correctly: 69% had prior MRI read as normal CTV, computed tomography venography; DEER, Diagnosis Error Evaluation and Research; ED, emergency department; IIH, idiopathic intracranial hypertension; IV, intravenous; LP, lumbar puncture; MRV, magnetic resonance venography; N/A, not applicable; ONSM, optic nerve sheath meningioma; RAPD, relative afferent pupillary defect; U, University. Dizziness and Stroke There is a well-developed literature on diagnostic error in neuro-otology (Table 4), which has led to the development of the Head Impulse, Nystagmus, and Test of Skew (HINTS) examination maneuvers to evaluate for central etiologies of dizziness (53) and, more recently, the Tele-Dizzy program (54). Like neuro-ophthalmology, neuro-otology requires specialized training and makes use of a detailed clinical examination. Acute-onset dizziness may be due to a benign, peripheral etiology or may be due to a posterior circulation stroke, sometimes with devastating outcomes (55). Emergency department evaluation is frequently suboptimal, with the potential to miss stroke diagnoses (56–59) and inefficient resource utilization (60,61). A portion of strokes that are initially missed would have been eligible for thrombolysis if correctly identified in the emergency department (32,34,35), and delayed diagnosis of stroke leads to longer hospitalizations (34) and worse outcomes (32). Much can be learned from the large body of literature on neuro-otology and stroke. One strength is the large sample sizes, achieved using data obtained from a geographic area or from a large database rather than a single institution (18,22,25,27,30,31,34,56,60–63). When rigorous epidemiologic and statistical methods are applied to such large data sets, it is possible to assess harm as a more objective outcome measure (22,25,27,30,33) or assess aggregate resource utilization (60,61). Standardization of the “SPADE” method 6 (Symptom-Disease Pair Analysis of Diagnostic Error) is a promising approach to facilitate epidemiologically valid measurement of misdiagnosis-related harms using revisit-based analysis of large, administrative data sets (64); this approach could eventually lead to widespread quality monitoring using diagnostic performance dashboards (65). Much can also be learned from the evolution of interventions designed to improve neuro-otologic diagnostic error. The HINTS criteria, consisting of 3 bedside diagnostic maneuvers (Table 5), were demonstrated to be a sensitive method for the detection of stroke (53,66,67). However, subsequent research after these criteria were disseminated showed that although they are sensitive for the detection of stroke by trained providers (53,68,69), they are less effective among untrained examiners (65). Thus, device-enabled telemedicine has become an active area of investigation to provide wider access to neuro-otology expertise (54,70). Multiple Sclerosis Similar to neuro-ophthalmologic conditions, multiple sclerosis is vulnerable to diagnostic error because no 2 presentations are the same, nonspecific symptoms are common, and there is no single “gold-standard” test for diagnosis (rather, diagnosis is based on a constellation of findings) (71,72). Disease-modifying therapy prevents more disability if started earlier, creating an incentive to achieve Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review TABLE 4. Studies examining diagnostic errors in neuro-otology (dizziness and stroke) Source Kerber et al (18) Design/Dates of Collection Population Condition(s) 1,666 patients .44 yrs old presenting to the ED with dizziness, vertigo, or imbalance Dizziness/vertigo 611 consecutive patients with ischemic stroke admitted within 7 d of stroke onset 413 consecutive patients presenting to the ED with dizziness Acute ischemic stroke Dizziness/vertigo Secondary analysis of the population-based cohort study 475 consecutive ED neurological consultations for dizziness 31,159 patients presenting to the ED with dizziness or vertigo and discharged without diagnosis of stroke 1,091 patients who presented to the ED for dizziness 2008–2009 Use of a prospective database 57 patients aged 16–50 yrs Acute stroke 2001–2006 Retrospective cohort study 3,021 patients hospitalized for vertigo Vertigo 951 consecutive patients referred for neuro-otology specialist evaluation 1,118 patients presenting to the ED with dizziness and discharged without diagnosis of stroke 189 patients discharged with a diagnosis of ischemic stroke Vertigo and imbalance Nueces County, TX Observational population-based study Nakajima et al (19) 2000–2003 Retrospective study Kumamoto U, Kumamoto, Japan Cheung et al (20) 2003–2005 Prospective observational study Hong Kong Royl et al (21) Charité—Universitätsmedizin, Berlin Kim et al (22) 2004 Retrospective study 2005–2006 Retrospective cohort study California 2005 Kerber et al (23) Nueces County, TX Kuruvilla et al (24) Young Stroke Registry at Wayne State U Lee et al (25) Taiwan National Health Insurance Research Database Geser and Straumann (26) U Hospital Zurich, Switzerland Lee et al (27) Taiwan National Health Insurance Research Database Lever et al (28) Dizziness/vertigo Dizziness/vertigo Dizziness 2004–2007 Retrospective 2004–2008 Retrospective cohort study 2004–2006 Retrospective chart review Yale Dizziness/vertigo Stroke 2008–2009 Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 7 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review (Continued ) Source Paul et al (29) Oxfordshire, UK (Oxford Vascular Study) Newman-Toker et al (30) Design/Dates of Collection Population Use of a prospective incidence study 45 patients with isolated brainstem transient neurological attacks preceding a vertebrobasilar stroke 198,819 patients admitted for stroke after the ED visit within previous 30 d 1,245 patients .44 yrs old presenting to the ED with dizziness and discharged without diagnosis of stroke 2,200 patients admitted to the stroke unit or ICU 2002–2010 Retrospective crosssectional study 9 US states Nueces County, TX 2008–2009 Observational population-based cohort study Richoz et al (32) 2011–2012 Retrospective review Kerber et al (31) Centre Hospitalier Universitaire Vaudois Atzema et al (33) Condition(s) 2003–2011 Retrospective cohort study Transient vertebrobasilar ischemia Dizziness/vertigo Dizziness/vertigo Acute ischemic stroke 41,794 ED discharges Dizziness/vertigo 2027 hospital admissions that presented to 16 EDs Ischemic stroke 465 patients discharged with a diagnosis of ischemic stroke Ischemic stroke Ontario, Canada Madsen et al (34) 16 EDs in Greater Cincinnati/Northern Kentucky Arch et al (35) New Haven, CT and Abington, PA Source Kerber et al (18) Nueces County, TX Nakajima et al (19) Kumamoto U, Kumamoto, Japan 8 2006–2011 Retrospective review 2010 Retrospective chart review 2013–2014 Outcome(s) of Interest Misdiagnosis Rate DEER Taxonomy Final diagnosis Whether ED diagnosis was correct 35% No Discharged from the ED and later found to have a stroke 10.0% No Summary 3% rate of acute stroke In 35% of cases, diagnosis not identified in the ED Age, male sex, and imbalance were associated with stroke Isolated dizziness negatively associated with acute stroke (0.7% of patients with isolated dizziness had stroke) Higher risk of missed stroke if: Not evaluated by a neurologist Chief complaint of dizziness Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review (Continued ) Source Cheung et al (20) Hong Kong Royl et al (21) Charité—Universitätsmedizin, Berlin Kim et al (22) California Kerber et al (23) Nueces County, TX Kuruvilla et al (24) Young Stroke Registry at Wayne State U Lee et al (25) Taiwan National Health Insurance Research Database Outcome(s) of Interest Misdiagnosis Rate DEER Taxonomy Discharged from the ED and found to have neurologic cause when contacted after 3 mos 0.6% No ED diagnosis corrected at the follow-up visit 43% No Death or hospital admission for the major vascular event within 180 d of ED discharge N/A No Nystagmus description conflicted with stated diagnosis 81% No Factors associated with misdiagnosis of acute stroke 14% No Stroke within 4 yrs of hospitalization (compared with the control group of 3,021 patients hospitalized for appendectomy) Adjusted hazard ratio: 3.01 (2.20–4.11) ,0.001 No Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Summary Nausea and/or vomiting (46%) and headache (20%) commonest associated finding Hypertension (33%) commonest prior illness Central neurological causes of dizziness in 6% Associated with stroke: Age .65 yrs, ataxia, focal neurologic symptoms, history of previous stroke, and diabetes Misdiagnosis more likely when cranial imaging not performed during the initial ED assessment 0.93% cumulative incidence rate of stroke within a month of discharge from the ED visit for dizziness or vertigo Age and male sex associated with stroke risk 19% of visits for dizziness did not have nystagmus examination documented 26% (48 of 185) visits with nystagmus documented had no further description of nystagmus characteristics Only 5.4% (10 of 185) visits had nystagmus described to the point that localization could be inferred In 81% (113 of 140), nystagmus description was not consistent with the ED provider’s stated diagnosis Misdiagnosis associated with age ,35 yrs and posterior circulation stroke Typical stroke risk factors increased risk 9 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review (Continued ) Source DEER Taxonomy Outcome(s) of Interest Misdiagnosis Rate Geser and Straumann (26) U Hospital Zurich, Switzerland Misdiagnosis at time of referral In 85% (562 of 662) of patients referred for undetermined dizziness, a specific diagnosis was made No Lee et al (27) Stroke within 3 yrs (compared with the control group of 24,639 patients without dizziness/ vertigo) 4.7% No Missed diagnosis of stroke in the ED (in patients who had been diagnosed with stroke by the time of discharge) 15% No Failure to recognize vascular etiology of symptoms 90% No Taiwan National Health Insurance Research Database Lever et al (28) Yale Paul et al (29) Oxfordshire, UK (Oxford Vascular Study) 10 Summary Undetermined dizziness was usually able to be clarified to a specific diagnosis, including BPPV or multisensory dizziness in older patients, and vestibular migraine in younger patients Proportion of patients with undetermined diagnoses decreased by 60% Higher rate of subsequent stroke in patients discharged from the ED for presumed peripheral cause of dizziness compared with a control group seen in the ED for other symptoms (not dizziness), implying that some of the cases of dizziness that were thought to be peripheral had been vascular Missed stroke was strongly associated with “nontraditional” symptoms: (P , 0.0001) —generalized weakness, altered mental status, altered gait, and dizziness. Twenty-three of 29 missed strokes presented with only nontraditional symptoms. Of 189 presentations: In patients with “traditional” stroke symptoms, 4% were initially missed. For patients with only nontraditional symptoms, 64% were initially missed. Only 22% (10 patients) of the patients who had an episode of isolated brainstem TIA symptoms preceding a stroke had sought medical attention for the TIA symptoms Vascular cause had been suspected by physicians in only 1 of those 10 patients Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review (Continued ) Source Newman-Toker et al (30) 9 US states Kerber et al (31) DEER Taxonomy Outcome(s) of Interest Misdiagnosis Rate Inpatient hospital admission for stroke preceded by an ED visit within previous 30 d 1.2% probable, 12.7% potential No Stroke event within 347 d after ED discharge 0.56% (90d stroke risk) No Failure to suspect or incorrect exclusion of stroke diagnosis while the patient was in the ED 2.1% No Stroke within 30 d of ED discharge with diagnosis of peripheral vertigo (compared with the control group of 34,872 patients discharged with diagnosis of renal colic) RR = 0.18% (rate of stroke is taken to imply misdiagnosis rate) No Physician-verified strokes in admitted patients who had not had stroke on the differential diagnosis during their ED course 14% No Nueces County, TX Richoz et al (32) Centre Hospitalier Universitaire Vaudois Atzema et al (33) Ontario, Canada Madsen et al (34) 16 EDs in Greater Cincinnati/Northern Kentucky Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Summary Estimate 15,000–165,000 misdiagnosed cerebrovascular events annually in US EDs Presenting with headache or dizziness was related to missed stroke 1% rate of stroke within 347 d of ED discharge—likely the rate of misdiagnosis of acute stroke in dizziness/vertigo patients was low Most of 90-d stroke risk (0.56%) occurred within 2 d (0.48%) Associated with missed stroke: Very mild and very severe strokes (leading to altered mentation) Younger age Cerebellar strokes If correctly diagnosed, 23.4% could have received thrombolysis Missed strokes had worse outcomes, including mortality Although the misdiagnosis rate is low, this presentation is common, and thus, absolute numbers of missed strokes are not negligible Relative risk of 30-d stroke was 9.3 (95% confidence interval [CI]: 4.3–20.3) times higher than among matched renal colic controls Risk factors for missed diagnoses were younger age, change in the level of consciousness, and nausea/vomiting Missed strokes were associated with longer hospital stays Suggested “anchor bias” as a cause of missed strokes. If a cardiac cause was found, they stopped looking for additional stroke 11 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review (Continued ) Source Arch et al (35) New Haven, CT and Abington, PA Outcome(s) of Interest Failure to diagnose stroke while the patient was in the ED Misdiagnosis Rate 22% DEER Taxonomy No Summary 37% of posterior circulation strokes initially missed compared with 16% of anterior circulation strokes 33% of the initially missed cases presented within the thrombolysis window, and an additional 11% presented within the thrombectomy window Missed stroke associated with nausea/vomiting, dizziness, and previous stroke history BPPV, benign paroxysmal positional vertigo; DEER, Diagnosis Error Evaluation and Research; ED, emergency department; ICU, intensive care unit; N/A, not applicable; RR, relative risk; TIA, transient ischemic attack; U, University. high sensitivity for the diagnosis of multiple sclerosis (73). Comparable with neuro-ophthalmologic conditions, misdiagnosis-in-excess rates up to 67% have been reported for multiple sclerosis (71,74–79). Patients may carry a misdiagnosis for a long time (76,79), unnecessarily exposing patients to the long-term risks of treatments for a disease they do not have (73). In addition to high rates of misdiagnosis-in-excess, missed or delayed diagnosis of multiple sclerosis is also common (80). Missed diagnosis in multiple sclerosis may be related to failure to take and interpret the history correctly (74,75), underweighing a normal examination (75) and misinterpretation of imaging findings (74–76), similar to pitfalls in neuro-ophthalmology (7–14,16,17). To identify high-yield opportunities for improvement, Solomon et al assessed which diagnostic errors were preventable and whether harm had occurred, finding that in many cases, careful application of the McDonald criteria would have prevented misdiagnosis (73,76). Revisions to the McDonald criteria, standard diagnostic criteria for the diagnosis of multiple sclerosis (81) must achieve an appropriately high level of sensitivity without permitting inordinate misdiagnosis-in-excess (71,72). Unfortunately, providers may apply the McDonald criteria incorrectly, leading to diagnostic error (76). The 2017 revision to the McDonald Criteria (81) incorporated diagnostic error research (72,81), prompting changes to recommendations for interpretation of MRI findings (72,81), such as the inclusion of symptomatic brainstem or spinal cord lesions and the exclusion of optic neuritis for the determination of dissemination in space and time. It was felt that doing so improved diagnostic sensitivity without compromising TABLE 5. Head Impulse, Nystagmus, and Test of Skew (HINTS) in the acute vestibular syndrome Examination Maneuver Head impulse Nystagmus Test of skew Performance “Central” if: The patient fixates on the examiner’s nose while his or her head is moved quickly and unexpectedly in the horizontal plane from lateral to center Examine for nystagmus in primary and eccentric gazes There is no corrective saccade in either direction (implying a bilaterally normal VOR) Alternate cover testing Nystagmus changes direction with the gaze position (i.e., there is a right-beat component in right gaze and left-beat component in left gaze, regardless of primary position findings; or there is a shift to a vertical vector) Vertical component of refixation VOR, vestibulo-ocular reflex. 12 Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review specificity, and the exclusion of optic neuritis was likely done to limit false positives, given the high risk of misdiagnosis of optic neuritis in general (72,81). Common Themes Attempts to characterize the cause of diagnostic errors allow us to identify common themes among multiple neuroophthalmologic conditions, including errors in the performance and interpretation of the physical examination (such as funduscopic examination or identification of a relative afferent pupillary defect), errors in the performance and interpretation of diagnostic imaging (such as brain MRI instead of orbital MRI with contrast), errors in the generation of an appropriate differential diagnosis (such as assuming that a young woman with an optic neuropathy can only have an optic neuritis), cognitive biases (such as assuming that a young, obese woman with headache must have IIH), and premature closure (such as failure to evaluate for other etiologies for blurred vision after identifying a cataract) (7– 9,11–13,16,17). However, even in the related fields of neuro-ophthalmology, multiple sclerosis, and stroke, there are myriad causes of diagnostic error—there can be no one-size-fits-all approach to improving diagnostic accuracy. FUTURE DIRECTIONS FOR DIAGNOSTIC ERROR RESEARCH Existing studies on diagnostic error in neuro-ophthalmology are mostly descriptive (7–13,16,17), and only one realworld study was prospective (9). Retrospective studies (7,10–13,16,17) are limited by the quality of records available from referring providers. Many of the studies have evaluated diagnostic error of a single condition (11– 14,16,17), and for the most part, studies were limited to patients seen at one (7,9–11,13,16,17) or 2 (12) universitybased, tertiary referral neuro-ophthalmology clinics. Overrepresentation of academic practices may inflate the rate of diagnostic error if there is a bias toward complicated cases (i.e., measurement of diagnostic error rates may be affected by referral bias). Nearly all the neuro-ophthalmologic studies to date selected patients at the time of initial neuro-ophthalmologic evaluation and used the final diagnosis by a neuroophthalmologist as the “gold standard” for correct diagnosis (7–13,16,17). However, this methodology has several important limitations. First, there are undoubtedly some patients with neuro-ophthalmologic conditions who are never referred to a neuro-ophthalmologist or may not have access to a neuro-ophthalmologist—these patients are not captured in this research model. Second, it is often impossible to distinguish between a firm vs. a tentative or “rule out” referral diagnosis, which likely artificially inflates the measured rates of diagnostic error. Moreover, if patients were referred urgently anyway, they may not have suffered any diagnostic delay or harm even from an incorrect referral Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 diagnosis. Third, neuro-ophthalmologists are not infallible, and many neuro-ophthalmologic conditions do not have a “gold-standard,” definitive diagnostic test (e.g., visual aura of migraine or transient ischemic attack). Thus, diagnostic uncertainty may remain even after neuro-ophthalmology evaluation, and some “final diagnoses” may be incorrect. Previous attempts to measure harm directly or quantify costs have been limited by methodological constraints (7,17). Previous studies have attempted to capture a sense of the costs and risk of harm that results from diagnostic error by quantifying the number of patients who underwent unnecessary diagnostic tests, consultation, treatments, or procedures (9,10,12,13,16) but have not captured whether patients actually suffered harm from these interventions. Going forward, it is important to design studies that directly measure patient harms and capture the financial costs of diagnostic error. Directly measuring harm will improve objectivity and may allow us to better direct resources toward combatting the errors that cause the most harm. In addition, studying larger populations in varied settings, as demonstrated in the neuro-otology and stroke literature, has the potential to improve the generalizability of diagnostic error research. Although many neuroophthalmologic conditions are rare, achieving larger sample sizes through use of “big data” is a potential avenue for further research into diagnostic error (64,65,82). APPLICATIONS More than 25 years ago, Dillon et al suggested that it would be more efficient for certain chief complaints to trigger a fast track to neuro-ophthalmologic consultation (7). Today, access to neuro-ophthalmologic consultation remains a limited resource (10). Recent studies investigating diagnostic errors in neuro-ophthalmology continue to show high rates of misdiagnosis of neuro-ophthalmologic conditions before evaluation by a neuro-ophthalmologist, leading to unnecessary interventions (6–17,83). The implication is that better access to a neuro-ophthalmologist has the potential to protect patients from harm, improve outcomes, and improve health care resource utilization. Measures to stimulate more physicians to train in and practice neuro-ophthalmology are required to improve patient access. To improve access to appropriate care, a paradigm shift may be required. Options include harnessing the potential of telemedicine using fundus photography or other means (54,84–88) or by focusing on improving education of generalists (89). Further research into diagnostic error in neuroophthalmology should focus on how to bring neuroophthalmologic care to patients who need it. CONCLUSIONS Diagnostic error is prevalent and costly, and the appropriate investigative methodology for research on diagnostic error is 13 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review still evolving. Consistent with other specialties, bedside diagnostic process failures in history taking, examination, test choice, or test interpretation are the most commonly identified causal factors among patients referred for neuroophthalmology evaluation (46,51). A high rate of diagnostic error among neuro-ophthalmologic conditions and identified process failure targets provide ample opportunity to develop more rigorous research in this field on burdens, causes, and solutions. Future avenues for investigation include capturing harms, quantifying costs, harnessing “big data,” and implementing solutions. SEARCH METHODS We reviewed the medical literature published in the English language through search of PubMed and Google Scholar using varied combinations of search terms “diagnostic errors,” “neuro-ophthalmology,” and “neurology.” Additional articles were identified by hand search using references from relevant articles and from our personal archives. We prioritized recent references. Studies that focused on the usefulness of a single test or intervention were excluded. The list of references is not exhaustive. REFERENCES 1. Committee on Diagnostic Error in Health Care; Board on Health Care Services; Institute of Medicine; The National Academies of Sciences, Engineering, and Medicine. Chapter 3: 3, overview of diagnostic error in health care. In: Balogh EP, Miller BT, Ball JR, eds. Improving diagnosis in health care. Washington, DC: National Academies Press (US), 2015. 2. Leape LL, Berwick DM, Bates DW. Counting deaths due to medical errors (in reply). JAMA. 2002;288:2404–2405. 3. Singh H, Meyer AN, Thomas EJ. The frequency of diagnostic errors in outpatient care: estimations from three large observational studies involving US adult populations. BMJ Qual Saf. 2014;23:727–731. 4. Saber Tehrani AS, Lee H, Mathews SC, Shore A, Makary MA, Pronovost PJ, Newman-Toker DE. 25-Year summary of US malpractice claims for diagnostic errors 1986-2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf. 2013;22:672–680. 5. Schaffer AC, Jena AB, Seabury SA, Singh H, Chalasani V, Kachalia A. Rates and characteristics of paid malpractice claims among US physicians by specialty, 1992-2014. JAMA Intern Med. 2017;177:710–718. 6. National Quality Forum. Improving diagnostic quality and safety. 2017. Available at: https://www.qualityforum.org/ Publications/2017/09/Improving_Diagnostic_Quality_and_ Safety_Final_Report.aspx. Accessed January 29, 2020. 7. Dillon EC, Sergott RC, Savino PJ, Bosley TM. Diagnostic management by gatekeepers is not cost effective for neuroophthalmology. Ophthalmology. 1994;101:1627–1630. 8. Wolintz RJ, Trobe JD, Cornblath WT, Gebarski SS, Mark AS, Kolsky MP. Common errors in the use of magnetic resonance imaging for neuro-ophthalmic diagnosis. Surv Ophthalmol. 2000;45:107–114. 9. McClelland C, Van Stavern GP, Shepherd JB, Gordon M, Huecker J. Neuroimaging in patients referred to a neuroophthalmology service: the rates of appropriateness and concordance in interpretation. Ophthalmology. 2012;119:1701–1704. 10. Stunkel L, Mackay DD, Bruce BB, Newman NJ, Biousse V. “Referral patterns in neuro-ophthalmology.” J Neuroophthalmol. 2019 (epub ahead of print). 14 11. Elmalem VI, Hudgins PA, Bruce BB, Newman NJ, Biousse V. Underdiagnosis of posterior communicating artery aneurysm in non-invasive brain vascular studies. J Neuroophthalmol. 2011;31:103–109. 12. Schroeder R, Stunkel L, Ebot J, Gowder MTA, Kendall E, Nagia L, Eggenberger ER, Van Stavern GP. Factors Leading to the Overdiagnosis of 3rd Nerve palsy. North American NeuroOphthalmology Society 45th Annual Meeting; March 19, 2019; NV. 13. Fisayo A, Bruce BB, Newman NJ, Biousse V. Overdiagnosis of idiopathic intracranial hypertension. Neurology. 2016;86:341– 350. 14. Blanch RJ, Horsburgh J, Creavin A; DOPS Study Group, Burdon MA, Williams C. Detection of Papilloedema Study (DOPS): rates of false positive papilloedema in the community. Eye (Lond). 2019;33:1073–1080. 15. Hartmann AJPW, Latting MW, Lee MS, Moster ML, Saindane AM, Newman NJ, Biousse V. Papilloedema from dural venous sinus compression by meningiomas. Neuro-Ophthalmol. 2019;43:171–179. 16. Stunkel L, Kung NH, Wilson B, McClelland CM, Van Stavern GP. Incidence and causes of overdiagnosis of optic neuritis. JAMA Ophthalmol. 2018;136:76–81. 17. Kahraman-Koytak P, Bruce BB, Peragallo JH, Newman NJ, Biousse V. Diagnostic errors in initial misdiagnosis of optic nerve sheath meningiomas. JAMA Neurol. 2019;76:326–332. 18. Kerber KA, Brown DL, Lisabeth LD, Smith MA, Morgenstern LB. Stroke among patients with dizziness, vertigo, and imbalance in the emergency department: a population-based study. Stroke. 2006;37:2484–2487. 19. Nakajima M, Hirano T, Uchino M. Patients with acute stroke admitted on the second visit. J Stroke Cerebrovasc Dis. 2008;17:382–387. 20. Cheung CS, Mak PS, Manley KV, Lam JM, Tsang AY, Chan HM, Rainer TH, Graham CA. Predictors of important neurological causes of dizziness among patients presenting to the emergency department. Emerg Med J. 2010;27:517–521. 21. Royl G, Ploner CJ, Leithner C. Dizziness in the emergency room: diagnoses and misdiagnoses. Eur Neurol. 2011;66:256–263. 22. Kim AS, Fullerton HJ, Johnston SC. Risk of vascular events in emergency department patients discharged home with diagnosis of dizziness or vertigo. Ann Emerg Med. 2011;57:34–41. 23. Kerber KA, Morgenstern LB, Meurer WJ, McLaughlin T, Hall PA, Forman J, Fendrick AM, Newman-Toker DE. Nystagmus assessments documented by emergency physicians in acute dizziness presentations: a target for decision support? Acad Emerg Med. 2011;18:619–626. 24. Kuruvilla A, Bhattacharya P, Rajamani K, Chaturvedi S. Factors associated with misdiagnosis of acute stroke in young adults. J Stroke Cerebrovasc Dis. 2011;20:523–527. 25. Lee CC, Su YC, Ho HC, Hung SK, Lee MS, Chou P, Huang YS. Risk of stroke in patients hospitalized for isolated vertigo: a four-year follow-up study. Stroke. 2011;42:48–52. 26. Geser R, Straumann D. Referral and final diagnoses of patients assessed in an academic vertigo center. Front Neurol. 2012;28:169. 27. Lee CC, Ho HC, Su YC, Chiu BC, Su YC, Lee YD, Chou P, Chien SH, Huang YS. Increased risk of vascular events in emergency room patients discharged home with diagnosis of dizziness or vertigo: a 3-year follow-up study. PLoS One. 2012;7:e35923. 28. Lever NM, Nyström KV, Schindler JL, Halliday J, Wira C III, Funk M. Missed opportunities for recognition of ischemic stroke in the emergency department. J Emerg Nurs. 2013;39:434–439. 29. Paul NL, Simoni M, Rothwell PM; Oxford Vascular Study. Transient isolated brainstem symptoms preceding posterior circulation stroke: a population-based study. Lancet Neurol. 2013;12:65–71. 30. Newman-Toker DE, Moy E, Valente E, Coffey R, Hines AL. Missed diagnosis of stroke in the emergency department: a Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. cross-sectional analysis of a large population-based sample. Diagnosis. 2014;1:155–166. Kerber KA, Zahuranec DB, Brown DL, Meurer WJ, Burke JF, Smith MA, Lisabeth LD, Fendrick AM, McLaughlin T, Morgenstern LB. Stroke risk after non-stroke ED dizziness presentations: a population-based cohort study. Ann Neurol. 2014;75:899–907. Richoz B, Hugli O, Dami F, Carron PN, Faouzi M, Michel P. Acute stroke chameleons in a university hospital: risk factors, circumstances, and outcomes. Neurology. 2015;85:505–511. Atzema CL, Grewal K, Lu H, Kapral MK, Kulkarni G, Austin PC. Outcomes among patients discharged from the emergency department with a diagnosis of peripheral vertigo. Ann Neurol. 2016;79:32–41. Madsen TE, Khoury J, Cadena R, Adeoye O, Alwell KA, Moomaw CJ, McDonough E, Flaherty ML, Ferioli S, Woo D, Khatri P, Broderick JP, Kissela BM, Kleindorfer D. Potentially missed diagnosis of ischemic stroke in the emergency department in the Greater Cincinnati/Northern Kentucky Stroke Study. Acad Emerg Med. 2016;23:1128–1135. Arch AE, Weisman DC, Coca S, Nystrom KV, Wira CR III, Schindler JL. Missed ischemic stroke diagnosis in the emergency department by emergency medicine and neurology services. Stroke. 2016;47:668–673. Stunkel L, Newman NJ, Biousse V. Diagnostic error and neuroophthalmology. Curr Opin Neurol. 2018;32:62–67. Chung SM, Custer PL. Patient safety: its history and relevance to neuro-ophthalmology. J Neuroophthalmol. 2017;37:225– 229. Mehta S, Loener LA, Mikityansky I, Langlotz C, Ying GS, Tamhankar MA, Shindler KS, Volpe NJ. The diagnostic and economic yield of neuroimaging in neuro-ophthalmology. J Neuroophthal. 2012;32:139–144. Subramanian PS, Frohman LP, Biousse V. Quality of NeuroOphthalmic Care Committee of the North American NeuroOphthalmology Society. Impact of the elimination of consultation codes on neuro-ophthalmology in the United States. J Neuroophthalmol. 2018;38:4–6. Frohman LP. Neuro-Ophthalmology: transitioning from old to new models of health care delivery. J Neuroophthalmol. 2017;37:206–209. Frohman L, Digre K. Elimination of consult codes in neuroophthalmology: another blow to our subspecialty? J Neuroophthalmol 2010;30:210–211. Fuhrmans V. Medical Specialties Hit by a Growing Pay Gap. The Wall Street Journal [newspaper on the Internet]. 2008 May 5 [cited 2018 September 9]. Available at: https://www.wsj.com/ articles/SB120995022062766515. Accessed July 8, 2020. Mathew PG, Najib U, Krel R, Rizzoli PB. Idiopathic Intracranial Hypertension: Papilledema and Neuro-Ophthalmology Referral Patterns. Practical Neurology [magazine on the Internet]. October 2016. Available at: http://practicalneurology.com/ 2016/10/idiopathic-intracranial-hypertension-papilledemaand-neuro-ophthalmology-referral-patterns/. Accessed April 16, 2019. Newman-Toker DE. A unified conceptual model for diagnostic errors: underdiagnosis, overdiagnosis, and misdiagnosis. Diagnosis (Berl). 2014;1:43–48. Newman-Toker DE, Pronovost PJ. Diagnostic errors-the next frontier for patient safety. JAMA. 2009;301:1060–1062. Newman-Toker DE, Schaffer AC, Yu-Moe CW, et al. Serious misdiagnosis-related harms in malpractice claims: the “Big Three”—vascular events, infections, and cancers. Diagnosis (Berl). 2019;6:227–240. Morrison A. Screening in Chronic Disease. New York: Oxford University Press, 1992. Bulliard JL, Chiolero A. Screening and overdiagnosis: public health implications. Public Health Rev. 2015;36:8. Abdulhussein D, Seth I, Badat N. Incidence and causes of overdiagnosis of optic neuritis: physician insecurity. JAMA Ophthalmol. 2018;136:1312. Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 50. Schiff GD, Kim S, Abrams R, Cosby K, Lambert B, Elstein AS, Hasler S, Krosnjar N, Odwazny R, Wisniewski MF, McNutt RA. Diagnosing diagnosis errors: lessons from a multi-institutional collaborative project. In: Henriksen K, Battles JB, Marks ES, Lewin DI, eds. Advances in Patient Safety: From Research to Implementation. Vol 2. Concepts and Methodology. Rockville, MD: Agency for Healthcare Research and Quality, 2005:255– 278. 51. Schiff GD, Hasan O, Kim S, Abrams R, Cosby K, Lambert BL, Elstein AS, Hasler S, Kabongo ML, Krosnjar N, Odwazny R, Wisniewski MF, McNutt RA. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009;169:1881–1887. 52. Cogan DG. Neurology of the Visual System. Springfield, IL: Charles C Thomas, 1966. 53. Kattah JC, Talkad AV, Wang DZ, Hsieh YH, Newman-Toker DE. HINTS to diagnose stroke in the acute vestibular syndrome: three-step bedside oculomotor examination more sensitive than early MRI diffusion-weighted imaging. Stroke. 2009;40:3504–3510. 54. Gold D, Peterson S, McClenney A, Tourkevich R, Brune A, Choi W, Shemesh A, Maliszewski B, Bosley J, Otero-Millan J, Fanai M, Roberts D, Tevzadze N, Zee D, Newman-Toker D. Diagnostic impact of a device-enabled remote "Tele-Dizzy" consultation service [abstract]. Diagnostic Error in Medicine, 12th Annual Conference; Washington, DC; November 10–13, 2019. 55. Savitz SI, Caplan LR, Edlow JA. Pitfalls in the diagnosis of cerebellar infarction. Acad Emerg Med. 2007;14:63–68. 56. Saber Tehrani AS, Kattah JC, Kerber KA, Gold DR, Zee DS, Urrutia VC, Newman-Toker DE. Diagnosing stroke in acute dizziness and vertigo: pitfalls and pearls. Stroke. 2018;49:788–795. 57. Kerber KA, Newman-Toker DE. Misdiagnosing dizzy patients: common pitfalls in clinical practice. Neurol Clin. 2015;33:565–575. 58. Newman-Toker DE. Missed stroke in acute vertigo and dizziness: it is time for action, not debate. Ann Neurol. 2016;79:27–31. 59. Tarnutzer AA, Lee SH, Robinson KA, Wang Z, Edlow JA, Newman-Toker DE. ED misdiagnosis of cerebrovascular events in the era of modern neuroimaging: a meta-analysis. Neurology. 2017;88:1468–1477. 60. Saber Tehrani AS, Coughlan D, Hsieh YH, Mantokoudis G, Korley FK, Kerber KA, Frick KD, Newman-Toker DE. Rising annual costs of dizziness presentations to U.S. emergency departments. Acad Emerg Med. 2013;20:689–696. 61. Kerber KA, Meurer WJ, West BT, Fendrick AM. Dizziness presentations in U.S. emergency departments, 1995-2004. Acad Emerg Med. 2008;15:744–750. 62. Newman-Toker DE, Hsieh YH, Camargo CA Jr, Pelletier AJ, Butchy GT, Edlow JA. Spectrum of dizziness visits to US emergency departments: cross-sectional analysis from a nationally representative sample. Mayo Clin Proc. 2008;83:765–775. 63. Chase M, Goldstein JN, Selim MH, Pallin DJ, Camacho MA, O’Connor JL, Ngo L, Edlow JA. A prospective pilot study of predictors of acute stroke in emergency department patients with dizziness. Mayo Clin Proc. 2014;89:173–180. 64. Liberman AL, Newman-Toker DE. Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosisrelated harms using big data. BMJ Qual Saf. 2018;27:557– 566. 65. Mane KK, Rubenstein KB, Nassery N, Sharp AL, Shamim EA, Sangha NS, Hassoon A, Fanai M, Wang Z, Newman-Toker DE. Diagnostic performance dashboards: tracking diagnostic errors using big data. BMJ Qual Saf. 2018;27:567–570. 66. Cnyrim CD, Newman-Toker D, Karch C, Brandt T, Strupp M. Bedside differentiation of vestibular neuritis from central “vestibular pseudoneuritis”. J Neurol Neurosurg Psychiatry. 2008;79:458–460. 15 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review 67. Newman-Toker DE, Kattah JC, Alvernia JE, Wang DZ. Normal head impulse test differentiates acute cerebellar strokes from vestibular neuritis. Neurology. 2008;70:2378–2385. 68. Chen L, Lee W, Chambers BR, Dewey HM. Diagnostic accuracy of acute vestibular syndrome at the bedside in a stroke unit. J Neurol. 2011;258:855–861. 69. Newman-Toker DE, Kerber KA, Hsieh YH, Pula JH, Omron R, Saber Tehrani AS, Mantokoudis G, Hanley DF, Zee OS, Kaltah JC. HINTS Outperforms ABCD2 to Screen for stroke in acute continuous vertigo and dizziness. Acad Emerg Med. 2013;20:987–996. 70. Newman-Toker DE, Saber Tehrani AS, Mantokoudis G, Pula JH, Guede CI, Kerber KA, Blitz A, Ying SH, Hsieh YH, Rothman RE, Hanley DF, Zee DS, Kattah JC. Quantitative video-oculography to help diagnose stroke in acute vertigo and dizziness: toward an ECG for the eyes. Stroke. 2013;44:1158–1161. 71. Solomon AJ, Naismith RT, Cross AH. Misdiagnosis of multiple sclerosis: impact of the 2017 McDonald criteria on clinical practice. Neurology. 2019;92:26–33. 72. Brownlee WJ. Misdiagnosis of multiple sclerosis: if you have a hammer, everything looks like a nail? Neurology. 2019;92:15–16. 73. Solomon AJ, Corboy JR. The tension between early diagnosis and misdiagnosis of multiple sclerosis. Nat Rev Neurol. 2017;13:567–572. 74. Poser CM. Misdiagnosis of multiple sclerosis. Lancet. 1997;349:1916. 75. Carmosino MJ, Brousseau KM, Arciniegas DB, Corboy JR. Initial evaluations for multiple sclerosis in a university multiple sclerosis center: outcomes and role of magnetic resonance imaging in referral. Arch Neurol. 2005;62:585–590. 76. Solomon AJ, Bourdette DN, Cross AH, Applebee A, Skidd PM, Howard DB, Spain RI, Cameron MH, Kim E, Mass MK, Yadav V, Whitham RH, Longbrake EE, Naismith RT, Wu GF, Parks BJ, Wingerchuk DM, Rabin BL, Toledano M, Tobin WO, Kantarci OH, Carter JL, Keegan BM, Weinshenker BG. The contemporary spectrum of multiple sclerosis misdiagnosis: a multicenter study. Neurology. 2016;87:1393–1399. 77. Yamout BI, Khoury SJ, Ayyoubi N, Doumiati H, Fakhreddine M, Ahmed SF, Tamim H, Al-Hashel JY, Behbehani R, Alroughani R. Alternative diagnoses in patients referred to specialized centers for suspected MS. Mult Scler Relat Disord. 2017;18:85–89. 78. Kaisey M, Solomon AJ, Luu M, Giesser BS, Sicotte NL. Incidence of multiple sclerosis misdiagnosis in referrals to two academic centers. Mult Scler Relat Disord. 2019;30:51–56. 16 79. Solomon AJ, Klein EP, Bourdette D. Undiagnosing multiple sclerosis: the challenge of misdiagnosis in MS. Neurology. 2012;78:1986–1991. 80. Levin N, Mor M, Ben-Hur T. Patterns of misdiagnosis of multiple sclerosis. Isr Med Assoc J. 2003;5:489–490. 81. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, Correale J, Fazekas F, Filippi M, Freedman MS, Fujihara K, Galetta SL, Hartung HP, Kappos L, Lublin FD, Marrie RA, Miller AE, Miller DH, Montalban X, Mowry EM, Sorensen PS, Tintoré M, Traboulsee AL, Trojano M, Uitdehaag BMJ, Vukusic S, Waubant E, Weinshenker BG, Reingold SC, Cohen JA. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17:162–173. 82. Moss HE, Joslin CE, Rubin DS, Roth S. Big data research in neuro-ophthalmology: promises and pitfalls. J Neuroophthalmol. 2019;39:480–486. 83. Sadun AA, Chu ER, Boisvert CJ. Neuro-ophthalmology safer than MRI? Ophthalmology. 2013;120:879. 84. Bruce BB, Lamirel C, Biousse V, Ward A, Heilpern KL, Newman NJ, Wright DW. Nonmydriatic ocular fundus photography in the emergency department. N Engl J Med. 2011;364:387–389. 85. Bruce BB, Lamirel C, Biousse V, Ward A, Heilpern KL, Newman NJ, Wright DW. Feasibility of nonmydriatic ocular fundus photography in the emergency department: phase I of the FOTO-ED study. Acad Emerg Med. 2011;18:928–933. 86. Bruce BB, Thulasi P, Fraser CL, Keadey MT, Ward A, Heilpern KL, Wright DW, Newman NJ, Biousse V. Diagnostic accuracy and use of nonmydriatic ocular fundus photography by emergency physicians: phase II of the FOTO-ED study. Ann Emerg Med. 2013;62:28–33. 87. Lamirel C, Bruce BB, Wright DW, Delaney KP, Newman NJ, Biousse V. Quality of nonmydriatic digital fundus photography obtained by nurse practitioners in the emergency department: the FOTO-ED study. Ophthalmol. 2012;119:617–624. 88. Bruce BB, Bidot S, Hage R, Clough LC, Fajoles-Vasseneix C, Melomed M, Keadey MT, Wright DW, Newman NJ, Biousse V. Fundus photography vs. Ophthalmoscopy outcomes in the emergency department (FOTO-ED) phase III: web-based, inservice training of emergency providers. Neuroophthalmology. 2018;42:269–274. 89. Kotwal S, Fanai M, Bery A, Tevzadze N, Gold D, Wang Z, Fu W, Omron R, Garibaldi B, Wright S, Newman-Toker D. Real-world virtual patients: case-based simulation using actual history and physical exam data to improve diagnosis. Diagnostic Error in Medicine, 12th Annual Conference; Washington, DC; November 10–13, 2019. Stunkel et al: J Neuro-Ophthalmol 2020; 00: 1-16 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. |
Date | 2021 |
Date Digital | 2021 |
Language | eng |
Format | application/pdf |
Type | Text |
Source | Journal of Neuro-Ophthalmology 2000;00:1-16 |
Collection | Neuro-Ophthalmology Virtual Education Library: NOVEL https://NOVEL.utah.edu |
Publisher | North American Neuro-Ophthalmology Society |
Holding Institution | Spencer S. Eccles Health Sciences Library, University of Utah |
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