Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE).

OBJECTIVES: Diagnostic errors are the leading cause of preventable harm in clinical practice. Implementable tools to quantify and target this problem are needed. To address this gap, we aimed to generalize the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework by developing its computable phenotype and then demonstrated how that schema could be applied in multiple clinical contexts. METHODS: We created an information model for the SPADE processes, then mapped data fields from electronic health records (EHR) and claims data in use to that model to create the SPADE information model (intention) and the SPADE computable phenotype (extension). Later we validated the computable phenotype and tested it in four case studies in three different health systems to demonstrate its utility. RESULTS: We mapped and tested the SPADE computable phenotype in three different sites using four different case studies. We showed that data fields to compute an SPADE base measure are fully available in the EHR Data Warehouse for extraction and can operationalize the SPADE framework from provider and/or insurer perspective, and they could be implemented on numerous health systems for future work in monitor misdiagnosis-related harms. CONCLUSIONS: Data for the SPADE base measure is readily available in EHR and administrative claims. The method of data extraction is potentially universally applicable, and the data extracted is conveniently available within a network system. Further study is needed to validate the computable phenotype across different settings with different data infrastructures.

The Role for Policy in AI-Assisted Medical Diagnosis.

This JAMA Forum discusses the promise and pitfalls of using large language models and artificial intelligence (AI) in the diagnosis of patients.

Quantifying Induced Nystagmus Using a Smartphone Eye Tracking Application (EyePhone).

BACKGROUND: There are ≈5 million annual dizziness visits to US emergency departments, of which vestibular strokes account for over 250 000. The head impulse, nystagmus, and test of skew eye examination can accurately distinguish vestibular strokes from peripheral dizziness. However, the eye-movement signs are subtle, and lack of familiarity and difficulty with recognition of abnormal eye movements are significant barriers to widespread emergency department use. To break this barrier, we sought to assess the accuracy of EyePhone, our smartphone eye-tracking application, for quantifying nystagmus. METHODS AND RESULTS: We prospectively enrolled healthy volunteers and recorded the velocity of induced nystagmus using a smartphone eye-tracking application (EyePhone) and then compared the results with video oculography (VOG). Following a calibration protocol, the participants viewed optokinetic stimuli with incremental velocities (2-12 degrees/s) in 4 directions. We extracted slow phase velocities from EyePhone data in each direction and compared them with the corresponding slow phase velocities obtained by the VOG. Furthermore, we calculated the area under the receiver operating characteristic curve for nystagmus detection by EyePhone. We enrolled 10 volunteers (90% men) with an average age of 30.2±6 years. EyePhone-recorded slow phase velocities highly correlated with the VOG recordings (r=0.98 for horizontal and r=0.94 for vertical). The calibration significantly increased the slope of linear regression for horizontal and vertical slow phase velocities. Evaluating the EyePhone's performance using VOG data with a 2 degrees/s threshold showed an area under the receiver operating characteristic curve of 0.87 for horizontal and vertical nystagmus detection. CONCLUSIONS: We demonstrated that EyePhone could accurately detect and quantify optokinetic nystagmus, similar to the VOG goggles.

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.

Assessing clinical reasoning skills following a virtual patient dizziness curriculum.

OBJECTIVES: Dizziness is a common medical symptom that is frequently misdiagnosed. While virtual patient (VP) education has been shown to improve diagnostic accuracy for dizziness as assessed by VPs, trainee performance has not been assessed on human subjects. The study aimed to assess whether internal medicine (IM) interns after training on a VP-based dizziness curriculum using a deliberate practice framework would demonstrate improved clinical reasoning when assessed in an objective structured clinical examination (OSCE). METHODS: All available interns volunteered and were randomized 2:1 to intervention (VP education) vs. control (standard clinical teaching) groups. This quasi-experimental study was conducted at one academic medical center from January to May 2021. Both groups completed pre-posttest VP case assessments (scored as correct diagnosis across six VP cases) and participated in an OSCE done 6 weeks later. The OSCEs were recorded and assessed using a rubric that was systematically developed and validated. RESULTS: Out of 21 available interns, 20 participated. Between intervention (n=13) and control (n=7), mean pretest VP diagnostic accuracy scores did not differ; the posttest VP scores improved for the intervention group (3.5 [SD 1.3] vs. 1.6 [SD 0.8], p=0.007). On the OSCE, the means scores were higher in the intervention (n=11) compared to control group (n=4) for physical exam (8.4 [SD 4.6] vs. 3.9 [SD 4.0], p=0.003) and total rubric score (43.4 [SD 12.2] vs. 32.6 [SD 11.3], p=0.04). CONCLUSIONS: The VP-based dizziness curriculum resulted in improved diagnostic accuracy among IM interns with enhanced physical exam skills retained at 6 weeks post-intervention.

Guidelines for reasonable and appropriate care in the emergency department 3 (GRACE-3): Acute dizziness and vertigo in the emergency department.

This third Guideline for Reasonable and Appropriate Care in the Emergency Department (GRACE-3) from the Society for Academic Emergency Medicine is on the topic adult patients with acute dizziness and vertigo in the emergency department (ED). A multidisciplinary guideline panel applied the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence and strength of recommendations regarding five questions for adult ED patients with acute dizziness of less than 2 weeks' duration. The intended population is adults presenting to the ED with acute dizziness or vertigo. The panel derived 15 evidence-based recommendations based on the timing and triggers of the dizziness but recognizes that alternative diagnostic approaches exist, such as the STANDING protocol and nystagmus examination in combination with gait unsteadiness or the presence of vascular risk factors. As an overarching recommendation, (1) emergency clinicians should receive training in bedside physical examination techniques for patients with the acute vestibular syndrome (AVS; HINTS) and the diagnostic and therapeutic maneuvers for benign paroxysmal positional vertigo (BPPV; Dix-Hallpike test and Epley maneuver). To help distinguish central from peripheral causes in patients with the AVS, we recommend: (2) use HINTS (for clinicians trained in its use) in patients with nystagmus, (3) use finger rub to further aid in excluding stroke in patients with nystagmus, (4) use severity of gait unsteadiness in patients without nystagmus, (5) do not use brain computed tomography (CT), (6) do not use routine magnetic resonance imaging (MRI) as a first-line test if a clinician trained in HINTS is available, and (7) use MRI as a confirmatory test in patients with central or equivocal HINTS examinations. In patients with the spontaneous episodic vestibular syndrome: (8) search for symptoms or signs of cerebral ischemia, (9) do not use CT, and (10) use CT angiography or MRI angiography if there is concern for transient ischemic attack. In patients with the triggered (positional) episodic vestibular syndrome, (11) use the Dix-Hallpike test to diagnose posterior canal BPPV (pc-BPPV), (12) do not use CT, and (13) do not use MRI routinely, unless atypical clinical features are present. In patients diagnosed with vestibular neuritis, (14) consider short-term steroids as a treatment option. In patients diagnosed with pc-BPPV, (15) treat with the Epley maneuver. It is clear that as of 2023, when applied in routine practice by emergency clinicians without special training, HINTS testing is inaccurate, partly due to use in the wrong patients and partly due to issues with its interpretation. Most emergency physicians have not received training in use of HINTS. As such, it is not standard of care, either in the legal sense of that term ("what the average physician would do in similar circumstances") or in the common parlance sense ("the standard action typically used by physicians in routine practice").

Impact of Clinician Training Background and Stroke Location on Bedside Diagnostic Test Accuracy in the Acute Vestibular Syndrome - A Meta-Analysis.

OBJECTIVE: Acute dizziness/vertigo is usually due to benign inner-ear causes but is occasionally due to dangerous neurologic ones, particularly stroke. Because symptoms and signs overlap, misdiagnosis is frequent and overuse of neuroimaging is common. We assessed the accuracy of bedside findings to differentiate peripheral vestibular from central neurologic causes. METHODS: We performed a systematic search (MEDLINE and Embase) to identify studies reporting on diagnostic accuracy of physical examination in adults with acute, prolonged dizziness/vertigo ("acute vestibular syndrome" [AVS]). Diagnostic test properties were calculated for findings. Results were stratified by examiner type and stroke location. RESULTS: We identified 6,089 citations and included 14 articles representing 10 study cohorts (n = 800). The Head Impulse, Nystagmus, Test of Skew (HINTS) eye movement battery had high sensitivity 95.3% (95% confidence interval [CI] = 92.5-98.1) and specificity 92.6% (95% CI = 88.6-96.5). Sensitivity was similar by examiner type (subspecialists 94.3% [95% CI = 88.2-100.0] vs non-subspecialists 95.0% [95% CI = 91.2-98.9], p = 0.55), but specificity was higher among subspecialists (97.6% [95% CI = 94.9-100.0] vs 89.1% [95% CI = 83.0-95.2], p = 0.007). HINTS sensitivity was lower in anterior cerebellar artery (AICA) than posterior inferior cerebellar artery (PICA) strokes (84.0% [95% CI = 65.3-93.6] vs 97.7% [95% CI = 93.3-99.2], p = 0.014) but was "rescued" by the addition of bedside hearing tests (HINTS+). Severe (grade 3) gait/truncal instability had high specificity 99.2% (95% CI = 97.8-100.0) but low sensitivity 35.8% (95% CI = 5.2-66.5). Early magnetic resonance imaging (MRI)-diffusion-weighted imaging (DWI; within 24-48 hours) was falsely negative in 15% of strokes (sensitivity 85.1% [95% CI = 79.2-91.0]). INTERPRETATION: In AVS, HINTS examination by appropriately trained clinicians can differentiate peripheral from central causes and has higher diagnostic accuracy for stroke than MRI-DWI in the first 24-48 hours. These techniques should be disseminated to all clinicians evaluating dizziness/vertigo. ANN NEUROL 2023;94:295-308.

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.

Misdiagnosis-related harm quantification through mixture models and harm measures.

Investigating and monitoring misdiagnosis-related harm is crucial for improving health care. However, this effort has traditionally focused on the chart review process, which is labor intensive, potentially unstable, and does not scale well. To monitor medical institutes' diagnostic performance and identify areas for improvement in a timely fashion, researchers proposed to leverage the relationship between symptoms and diseases based on electronic health records or claim data. Specifically, the elevated disease risk following a false-negative diagnosis can be used to signal potential harm. However, off-the-shelf statistical methods do not fully accommodate the data structure of a well-hypothesized risk pattern and thus fail to address the unique challenges adequately. To fill these gaps, we proposed a mixture regression model and its associated goodness-of-fit testing. We further proposed harm measures and profiling analysis procedures to quantify, evaluate, and compare misdiagnosis-related harm across institutes with potentially different patient population compositions. We studied the performance of the proposed methods through simulation studies. We then illustrated the methods through data analyses on stroke occurrence data from the Taiwan Longitudinal Health Insurance Database. From the analyses, we quantitatively evaluated risk factors for being harmed due to misdiagnosis, which unveiled some insights for health care quality research. We also compared general and special care hospitals in Taiwan and observed better diagnostic performance in special care hospitals using various new evaluation measures.

Short-term stroke risk after emergency department treat-and-release headache visit.

OBJECTIVE: To evaluate whether patients discharged to home after an emergency department (ED) visit for headache face a heightened short-term risk of stroke. BACKGROUND: Stroke hospitalizations that occur soon after ED visits for headache complaints may reflect diagnostic error. METHODS: We conducted a retrospective cohort study using statewide administrative claims data for all ED visits and admissions at nonfederal hospitals in Florida 2005-2018 and New York 2005-2016. Using standard International Classification of Diseases (ICD) codes, we identified adult patients discharged to home from the ED (treat-and-release visit) with a benign headache diagnosis (cohort of interest) as well as those with a diagnosis of renal colic or back pain (negative controls). The primary study outcome was hospitalization within 30 days for stroke (ischemic or hemorrhagic) defined using validated ICD codes. We assess the relationship between index ED visit discharge diagnosis and stroke hospitalization adjusting for patient demographics and vascular comorbidities. RESULTS: We identified 1,502,831 patients with an ED treat-and-release headache visit; mean age was 41 (standard deviation: 17) years and 1,044,520 (70%) were female. A total of 2150 (0.14%) patients with headache were hospitalized for stroke within 30 days. In adjusted analysis, stroke risk was higher after headache compared to renal colic (hazard ratio [HR]: 2.69; 95% confidence interval [CI]: 2.29-3.16) or back pain (HR: 4.0; 95% CI: 3.74-4.3). In the subgroup of 26,714 (1.78%) patients with headache who received brain magnetic resonance imaging at index ED visit, stroke risk was only slightly elevated compared to renal colic (HR: 1.47; 95% CI: 1.22-1.78) or back pain (HR: 1.49; 95% CI: 1.24-1.80). CONCLUSION: Approximately 1 in 700 patients discharged to home from the ED with a headache diagnosis had a stroke in the following month. Stroke risk was three to four times higher after an ED visit for headache compared to renal colic or back pain.

aEYE: A deep learning system for video nystagmus detection.

Background: Nystagmus identification and interpretation is challenging for non-experts who lack specific training in neuro-ophthalmology or neuro-otology. This challenge is magnified when the task is performed via telemedicine. Deep learning models have not been heavily studied in video-based eye movement detection. Methods: We developed, trained, and validated a deep-learning system (aEYE) to classify video recordings as normal or bearing at least two consecutive beats of nystagmus. The videos were retrospectively collected from a subset of the monocular (right eye) video-oculography (VOG) recording used in the Acute Video-oculography for Vertigo in Emergency Rooms for Rapid Triage (AVERT) clinical trial (#NCT02483429). Our model was derived from a preliminary dataset representing about 10% of the total AVERT videos (n = 435). The videos were trimmed into 10-sec clips sampled at 60 Hz with a resolution of 240 × 320 pixels. We then created 8 variations of the videos by altering the sampling rates (i.e., 30 Hz and 15 Hz) and image resolution (i.e., 60 × 80 pixels and 15 × 20 pixels). The dataset was labeled as "nystagmus" or "no nystagmus" by one expert provider. We then used a filtered image-based motion classification approach to develop aEYE. The model's performance at detecting nystagmus was calculated by using the area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, and accuracy. Results: An ensemble between the ResNet-soft voting and the VGG-hard voting models had the best performing metrics. The AUROC, sensitivity, specificity, and accuracy were 0.86, 88.4, 74.2, and 82.7%, respectively. Our validated folds had an average AUROC, sensitivity, specificity, and accuracy of 0.86, 80.3, 80.9, and 80.4%, respectively. Models created from the compressed videos decreased in accuracy as image sampling rate decreased from 60 Hz to 15 Hz. There was only minimal change in the accuracy of nystagmus detection when decreasing image resolution and keeping sampling rate constant. Conclusion: Deep learning is useful in detecting nystagmus in 60 Hz video recordings as well as videos with lower image resolutions and sampling rates, making it a potentially useful tool to aid future automated eye-movement enabled neurologic diagnosis.

Acute unilateral vestibulopathy/vestibular neuritis: Diagnostic criteria.

This paper describes the diagnostic criteria for Acute Unilateral Vestibulopathy (AUVP), a synonym for vestibular neuritis, as defined by the Committee for the Classification of Vestibular Disorders of the Bárány Society. AUVP manifests as an acute vestibular syndrome due to an acute unilateral loss of peripheral vestibular function without evidence for acute central or acute audiological symptoms or signs. This implies that the diagnosis of AUVP is based on the patient history, bedside examination, and, if necessary, laboratory evaluation. The leading symptom is an acute or rarely subacute onset of spinning or non-spinning vertigo with unsteadiness, nausea/vomiting and/or oscillopsia. A leading clinical sign is a spontaneous peripheral vestibular nystagmus, which is direction-fixed and enhanced by removal of visual fixation with a trajectory appropriate to the semicircular canal afferents involved (generally horizontal-torsional). The diagnostic criteria were classified by the committee for four categories: 1. "Acute Unilateral Vestibulopathy", 2. "Acute Unilateral Vestibulopathy in Evolution", 3. "Probable Acute Unilateral Vestibulopathy" and 4. "History of Acute Unilateral Vestibulopathy". The specific diagnostic criteria for these are as follows:"Acute Unilateral Vestibulopathy": A) Acute or subacute onset of sustained spinning or non-spinning vertigo (i.e., an acute vestibular syndrome) of moderate to severe intensity with symptoms lasting for at least 24 hours. B) Spontaneous peripheral vestibular nystagmus with a trajectory appropriate to the semicircular canal afferents involved, generally horizontal-torsional, direction-fixed, and enhanced by removal of visual fixation. C) Unambiguous evidence of reduced VOR function on the side opposite the direction of the fast phase of the spontaneous nystagmus. D) No evidence for acute central neurological, otological or audiological symptoms. E) No acute central neurological signs, namely no central ocular motor or central vestibular signs, in particular no pronounced skew deviation, no gaze-evoked nystagmus, and no acute audiologic or otological signs. F) Not better accounted for by another disease or disorder."Acute Unilateral Vestibulopathy in Evolution": A) Acute or subacute onset of sustained spinning or non-spinning vertigo with continuous symptoms for more than 3 hours, but not yet lasting for at least 24 h hours, when patient is seen; B) - F) as above. This category is useful for diagnostic reasons to differentiate from acute central vestibular syndromes, to initiate specific treatments, and for research to include patients in clinical studies."Probable Acute Unilateral Vestibulopathy": Identical to AUVP except that the unilateral VOR deficit is not clearly observed or documented."History of acute unilateral vestibulopathy": A) History of acute or subacute onset of vertigo lasting at least 24 hours and slowly decreasing in intensity. B) No history of simultaneous acute audiological or central neurological symptoms. C) Unambiguous evidence of unilaterally reduced VOR function. D) No history of simultaneous acute central neurological signs, namely no central ocular motor or central vestibular signs and no acute audiological or otological signs. E) Not better accounted for by another disease or disorder. This category allows a diagnosis in patients presenting with a unilateral peripheral vestibular deficit and a history of an acute vestibular syndrome who are examined well after the acute phase.It is important to note that there is no definite test for AUVP. Therefore, its diagnosis requires the exclusion of central lesions as well as a variety of other peripheral vestibular disorders. Finally, this consensus paper will discuss other aspects of AUVP such as etiology, pathophysiology and laboratory examinations if they are directly relevant to the classification criteria.

Eye and Head Movement Recordings Using Smartphones for Telemedicine Applications: Measurements of Accuracy and Precision.

Objective: Smartphones have shown promise in the assessment of neuro-ophthalmologic and vestibular disorders. We have shown that the head impulse test results recorded using our application are comparable with measurements from clinical video-oculography (VOG) goggles. The smartphone uses ARKit's capability to acquire eye and head movement positions without the need of performing a calibration as in most eye-tracking devices. Here, we measure the accuracy and precision of the eye and head position recorded using our application. Methods: We enrolled healthy volunteers and asked them to direct their eyes, their heads, or both to targets on a wall at known eccentricities while recording their head and eye movements with our smartphone application. We measured the accuracy as the error between the eye or head movement measurement and the location of each target and the precision as the standard deviation of the eye or head position for each of the target positions. Results: The accuracy of head recordings (15% error) was overall better than the accuracy of eye recordings (23% error). We also found that the accuracy for horizontal eye movements (17% error) was better than for vertical (27% error). Precision was also better for head movement (0.8 degrees) recordings than eye movement recordings (1.3 degrees) and variability tended to increase with eccentricity. Conclusion: Our results provide basic metrics evaluating the utility of smartphone applications in the quantitative assessment of head and eye movements. While the new method may not replace the more accurate dedicated VOG devices, they provide a more accessible quantitative option. It may be advisable to include a calibration recording together with any planned clinical test to improve the accuracy.

Vascular vertigo and dizziness: Diagnostic criteria.

This paper presents diagnostic criteria for vascular vertigo and dizziness as formulated by the Committee for the Classification of Vestibular Disorders of the Bárány Society. The classification includes vertigo/dizziness due to stroke or transient ischemic attack as well as isolated labyrinthine infarction/hemorrhage, and vertebral artery compression syndrome. Vertigo and dizziness are among the most common symptoms of posterior circulation strokes. Vascular vertigo/dizziness may be acute and prolonged (≥24 hours) or transient (minutes to  < 24 hours). Vascular vertigo/dizziness should be considered in patients who present with acute vestibular symptoms and additional central neurological symptoms and signs, including central HINTS signs (normal head-impulse test, direction-changing gaze-evoked nystagmus, or pronounced skew deviation), particularly in the presence of vascular risk factors. Isolated labyrinthine infarction does not have a confirmatory test, but should be considered in individuals at increased risk of stroke and can be presumed in cases of acute unilateral vestibular loss if accompanied or followed within 30 days by an ischemic stroke in the anterior inferior cerebellar artery territory. For diagnosis of vertebral artery compression syndrome, typical symptoms and signs in combination with imaging or sonographic documentation of vascular compromise are required.

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.