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Tu LH, Melnick E, Venkatesh AK, Sheth KN, Navaratnam D, Yaesoubi R, Forman HP, Mahajan A. Cost-Effectiveness of CT, CTA, MRI, and Specialized MRI for Evaluation of Patients Presenting to the Emergency Department With Dizziness. AJR Am J Roentgenol 2024; 222:e2330060. [PMID: 37937837 DOI: 10.2214/ajr.23.30060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
BACKGROUND. Underlying stroke is often misdiagnosed in patients presenting with dizziness. Although such patients are usually ineligible for acute stroke treatment, accurate diagnosis may still improve outcomes through selection of patients for secondary prevention measures. OBJECTIVE. The purpose of our study was to investigate the cost-effectiveness of differing neuroimaging approaches in the evaluation of patients presenting to the emergency department (ED) with dizziness who are not candidates for acute intervention. METHODS. A Markov decision-analytic model was constructed from a health care system perspective for the evaluation of a patient presenting to the ED with dizziness. Four diagnostic strategies were compared: noncontrast head CT, head and neck CTA, conventional brain MRI, and specialized brain MRI (including multiplanar high-resolution DWI). Differing long-term costs and outcomes related to stroke detection and secondary prevention measures were compared. Cost-effectiveness was calculated in terms of lifetime expenditures in 2022 U.S. dollars for each quality-adjusted life year (QALY); deterministic and probabilistic sensitivity analyses were performed. RESULTS. Specialized MRI resulted in the highest QALYs and was the most cost-effective strategy with US$13,477 greater cost and 0.48 greater QALYs compared with noncontrast head CT. Conventional MRI had the next-highest health benefit, although was dominated by extension with incremental cost of US$6757 and 0.25 QALY; CTA was also dominated by extension, with incremental cost of US$3952 for 0.13 QALY. Non-contrast CT alone had the lowest utility among the four imaging choices. In the deterministic sensitivity analyses, specialized MRI remained the most cost-effective strategy. Conventional MRI was more cost-effective than CTA across a wide range of model parameters, with incremental cost-effectiveness remaining less than US$30,000/QALY. Probabilistic sensitivity analysis yielded similar results as found in the base-case analysis, with specialized MRI being more cost-effective than conventional MRI, which in turn was more cost-effective than CTA. CONCLUSION. The use of MRI in patients presenting to the ED with dizziness improves stroke detection and selection for subsequent preventive measures. MRI-based evaluation leads to lower long-term costs and higher cumulative QALYs. CLINICAL IMPACT. MRI, incorporating specialized protocols when available, is the preferred approach for evaluation of patients presenting to the ED with dizziness, to establish a stroke diagnosis and to select patients for secondary prevention measures.
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Affiliation(s)
- Long H Tu
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 20 York St, New Haven, CT 06510
| | - Edward Melnick
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT
| | - Arjun K Venkatesh
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT
| | - Kevin N Sheth
- Department of Neurology, Yale School of Medicine, New Haven, CT
| | | | - Reza Yaesoubi
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT
| | - Howard P Forman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 20 York St, New Haven, CT 06510
| | - Amit Mahajan
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 20 York St, New Haven, CT 06510
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Platts-Mills TF, Nagurney JM, Melnick ER. Tolerance of Uncertainty and the Practice of Emergency Medicine. Ann Emerg Med 2019; 75:715-720. [PMID: 31874767 DOI: 10.1016/j.annemergmed.2019.10.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Indexed: 12/16/2022]
Affiliation(s)
| | - Justine M Nagurney
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center, and the Institute for Aging Research, Hebrew Senior Life, Boston, MA
| | - Edward R Melnick
- Department of Emergency Medicine, Yale-New Haven Hospital, New Haven, CT
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Ghassemi MM, Al-Hanai T, Raffa JD, Mark RG, Nemati S, Chokshi FH. How is the Doctor Feeling? ICU Provider Sentiment is Associated with Diagnostic Imaging Utilization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2018:4058-4064. [PMID: 30441248 DOI: 10.1109/embc.2018.8513325] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The judgment of intensive care unit (ICU) providers is difficult to measure using conventional structured electronic medical record (EMR) data. However, provider sentiment may be a proxy for such judgment. Utilizing 10 years of EMR data, this study evaluates the association between provider sentiment and diagnostic imaging utilization. We extracted daily positive / negative sentiment scores of written provider notes, and used a Poisson regression to estimate sentiment association with the total number of daily imaging reports. After adjusting for confounding factors, we found that (1) negative sentiment was associated with increased imaging utilization $(p < 0.01)$, (2) sentiment's association was most pronounced at the beginning of the ICU stay $(p < 0.01)$, and (3) the presence of any form of sentiment increased diagnostic imaging utilization up to a critical threshold $(p < 0.01)$. Our results indicate that provider sentiment may clarify currently unexplained variance in resource utilization and clinical practice.
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Mower WR, Gupta M, Rodriguez R, Hendey GW. Validation of the sensitivity of the National Emergency X-Radiography Utilization Study (NEXUS) Head computed tomographic (CT) decision instrument for selective imaging of blunt head injury patients: An observational study. PLoS Med 2017; 14:e1002313. [PMID: 28700585 PMCID: PMC5507397 DOI: 10.1371/journal.pmed.1002313] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 04/28/2017] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Clinicians, afraid of missing intracranial injuries, liberally obtain computed tomographic (CT) head imaging in blunt trauma patients. Prior work suggests that clinical criteria (National Emergency X-Radiography Utilization Study [NEXUS] Head CT decision instrument [DI]) can reliably identify patients with important injuries, while excluding injury, and the need for imaging in many patients. Validating this DI requires confirmation of the hypothesis that the lower 95% confidence limit for its sensitivity in detecting serious injury exceeds 99.0%. A secondary goal of the study was to complete an independent validation and comparison of the Canadian and NEXUS Head CT rules among the subgroup of patients meeting the inclusion and exclusion criteria. METHODS AND FINDINGS We conducted a prospective observational study of the NEXUS Head CT DI in 4 hospital emergency departments between April 2006 and December 2015. Implementation of the rule requires that patients satisfy 8 criteria to achieve "low-risk" classification. Patients are excluded from "low-risk" classification and assigned "high-risk" status if they fail to meet 1 or more criteria. We examined the instrument's performance in assigning "high-risk" status to patients requiring neurosurgical intervention among a cohort of 11,770 blunt head injury patients. The NEXUS Head CT DI assigned high-risk status to 420 of 420 patients requiring neurosurgical intervention (sensitivity, 100.0% [95% confidence interval [CI]: 99.1%-100.0%]). The instrument assigned low-risk status to 2,823 of 11,350 patients who did not require neurosurgical intervention (specificity, 24.9% [95% CI: 24.1%-25.7%]). None of the 2,823 low-risk patients required neurosurgical intervention (negative predictive value [NPV], 100.0% [95% CI: 99.9%-100.0%]). The DI assigned high-risk status to 759 of 767 patients with significant intracranial injuries (sensitivity, 99.0% [95% CI: 98.0%-99.6%]). The instrument assigned low-risk status to 2,815 of 11,003 patients who did not have significant injuries (specificity, 25.6% [95% CI: 24.8%-26.4%]). Significant injuries were absent in 2,815 of the 2,823 patients assigned low-risk status (NPV, 99.7% [95% CI: 99.4%-99.9%]). Of our patients, 7,759 (65.9%) met the inclusion and exclusion criteria of the Canadian Head CT rule, including 111 patients (1.43%) who required neurosurgical intervention and 306 (3.94%) who had significant intracranial injuries. In our study, the Canadian criteria for neurosurgical intervention identified 108 of 111 patients requiring neurosurgical intervention to yield a sensitivity of 97.3% (95% CI: 92.3%-99.4%) and exhibited a specificity of 58.8% (95% CI: 57.7%-59.9%). The NEXUS rule, when applied to this same cohort, identified all 111 patients requiring neurosurgical intervention, yielding a sensitivity of 100% (95% CI: 96.7%-100.0%) with a specificity of 32.6% (95% CI: 31.5%-33.6%). Our study found that the Canadian medium-risk factors identified 301 of 306 patients with significant injuries (sensitivity = 98.4%; 95% CI: 96.2%-99.5%), while the NEXUS rule identified 299 of these patients (sensitivity = 97.7%; 95% CI: 95.3%-99.1%). In our study, the Canadian medium-risk rule exhibited a specificity of 12.3% (95% CI: 11.6%-13.1%), while the NEXUS rule exhibited a specificity of 33.3% (95% CI: 32.3%-34.4%). Limitations of the study may arise from application of the rule by different clinicians in different environments. Clinicians may vary in their interpretation and application of the instrument's criteria and risk assignment and may also vary in deciding which patients require intervention. The instrument's specificity is also subject to spectrum bias and may change with variations in the proportion of "low-risk" patients seen in other centers. CONCLUSIONS The NEXUS Head CT DI reliably identifies blunt trauma patients who require head CT imaging and could significantly reduce the use of CT imaging.
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Affiliation(s)
- William R. Mower
- UCLA Department of Emergency Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, California, United States of America
- * E-mail:
| | - Malkeet Gupta
- UCLA Department of Emergency Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, California, United States of America
- Antelope Valley Hospital Emergency Department, Lancaster, California, United States of America
| | - Robert Rodriguez
- San Francisco General Hospital, Department of Emergency Medicine, UCSF School of Medicine, San Francisco, California, United States of America
| | - Gregory W. Hendey
- UCLA Department of Emergency Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, California, United States of America
- UCSF Fresno, Community Regional Medical Center, Fresno, California, United States of America
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Hanley D, Prichep LS, Bazarian J, Huff JS, Naunheim R, Garrett J, Jones EB, Wright DW, O'Neill J, Badjatia N, Gandhi D, Curley KC, Chiacchierini R, O'Neil B, Hack DC. Emergency Department Triage of Traumatic Head Injury Using a Brain Electrical Activity Biomarker: A Multisite Prospective Observational Validation Trial. Acad Emerg Med 2017; 24:617-627. [PMID: 28177169 DOI: 10.1111/acem.13175] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 01/25/2017] [Accepted: 01/31/2017] [Indexed: 11/28/2022]
Abstract
OBJECTIVES A brain electrical activity biomarker for identifying traumatic brain injury (TBI) in emergency department (ED) patients presenting with high Glasgow Coma Scale (GCS) after sustaining a head injury has shown promise for objective, rapid triage. The main objective of this study was to prospectively evaluate the efficacy of an automated classification algorithm to determine the likelihood of being computed tomography (CT) positive, in high-functioning TBI patients in the acute state. METHODS Adult patients admitted to the ED for evaluation within 72 hours of sustaining a closed head injury with GCS 12 to 15 were candidates for study. A total of 720 patients (18-85 years) meeting inclusion/exclusion criteria were enrolled in this observational, prospective validation trial, at 11 U.S. EDs. GCS was 15 in 97%, with the first and third quartiles being 15 (interquartile range = 0) in the study population at the time of the evaluation. Standard clinical evaluations were conducted and 5 to 10 minutes of electroencephalogram (EEG) was acquired from frontal and frontal-temporal scalp locations. Using an a priori derived EEG-based classification algorithm developed on an independent population and applied to this validation population prospectively, the likelihood of each subject being CT+ was determined, and performance metrics were computed relative to adjudicated CT findings. RESULTS Sensitivity of the binary classifier (likely CT+ or CT-) was 92.3% (95% confidence interval [CI] = 87.8%-95.5%) for detection of any intracranial injury visible on CT (CT+), with specificity of 51.6% (95% CI = 48.1%-55.1%) and negative predictive value (NPV) of 96.0% (95% CI = 93.2%-97.9%). Using ternary classification (likely CT+, equivocal, likely CT-) demonstrated enhanced sensitivity to traumatic hematomas (≥1 mL of blood), 98.6% (95% CI = 92.6%-100.0%), and NPV of 98.2% (95% CI = 95.5%-99.5%). CONCLUSION Using an EEG-based biomarker high accuracy of predicting the likelihood of being CT+ was obtained, with high NPV and sensitivity to any traumatic bleeding and to hematomas. Specificity was significantly higher than standard CT decision rules. The short time to acquire results and the ease of use in the ED environment suggests that EEG-based classifier algorithms have potential to impact triage and clinical management of head-injured patients.
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Affiliation(s)
- Daniel Hanley
- Brain Injury Outcomes The Johns Hopkins Medical Institutions Baltimore MD
| | - Leslie S. Prichep
- Department of Psychiatry New York University School of Medicine New York NY
- BrainScope Co., Inc. Bethesda MD
| | | | | | | | | | | | - David W. Wright
- Emory University School of Medicine and Grady Memorial Hospital Atlanta GA
| | | | | | - Dheeraj Gandhi
- Department of Radiology University of Maryland Baltimore MD
| | - Kenneth C. Curley
- Iatrikos Research and Development Strategies LLC Tampa FL
- Department of Surgery Uniformed Services University of the Health Sciences Bethesda MD
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Melnick ER. Big Versus Small Data and the Generalizability of the Rate of Computed Tomography Overuse in Minor Head Injury. Acad Emerg Med 2017; 24:391-392. [PMID: 27617902 DOI: 10.1111/acem.13084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Edward R. Melnick
- Department of Emergency Medicine Yale University School of Medicine New Haven CT
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Kuczawski M, Stevenson M, Goodacre S, Teare MD, Ramlakhan S, Morris F, Mason S. Should all anticoagulated patients with head injury receive a CT scan? Decision-analysis modelling of an observational cohort. BMJ Open 2016; 6:e013742. [PMID: 27974370 PMCID: PMC5168615 DOI: 10.1136/bmjopen-2016-013742] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVES It is not currently clear whether all anticoagulated patients with a head injury should receive CT scanning or only those with evidence of traumatic brain injury (eg, loss of consciousness or amnesia). We aimed to determine the cost-effectiveness of CT for all compared with selective CT use for anticoagulated patients with a head injury. DESIGN Decision-analysis modelling of data from a multicentre observational study. SETTING 33 emergency departments in England and Scotland. PARTICIPANTS 3566 adults (aged ≥16 years) who had suffered blunt head injury, were taking warfarin and underwent selective CT scanning. MAIN OUTCOME MEASURES Estimated expected benefits in terms of quality-adjusted life years (QALYs) were the entire cohort to receive a CT scan; estimated increased costs of CT and also the potential cost implications associated with patient survival and improved health. These values were used to estimate the cost per QALY of implementing a strategy of CT for all patients compared with observed practice based on guidelines recommending selective CT use. RESULTS Of the 1420 of 3534 patients (40%) who did not receive a CT scan, 7 (0.5%) suffered a potentially avoidable head injury-related adverse outcome. If CT scanning had been performed in all patients, appropriate treatment could have gained 3.41 additional QALYs but would have incurred £193 149 additional treatment costs and £130 683 additional CT costs. The incremental cost-effectiveness ratio of £94 895/QALY gained for unselective compared with selective CT use is markedly above the threshold of £20-30 000/QALY used by the UK National Institute for Care Excellence to determine cost-effectiveness. CONCLUSIONS CT scanning for all anticoagulated patients with head injury is not cost-effective compared with selective use of CT scanning based on guidelines recommending scanning only for those with evidence of traumatic brain injury. TRIAL REGISTRATION NUMBER NCT 02461498.
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Affiliation(s)
- Maxine Kuczawski
- School of Health and Related Research, University of Sheffield, SheffieldUK
| | - Matt Stevenson
- School of Health and Related Research, University of Sheffield, SheffieldUK
| | - Steve Goodacre
- School of Health and Related Research, University of Sheffield, SheffieldUK
| | - M Dawn Teare
- School of Health and Related Research, University of Sheffield, SheffieldUK
| | | | - Francis Morris
- Emergency Department, Northern General Hospital, SheffieldUK
| | - Suzanne Mason
- School of Health and Related Research, University of Sheffield, SheffieldUK
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