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5. Decision Support for Prolonged, and Tactical Combat Casualty Care

Author

Nemeth, Christopher, Amos-Binks, Adam, Keeney, Natalie, Pinevich, Yuliya, Rule, Gregory, Laufersweiler, Dawn, Flint, Isaac, Hereasevich, Vitaly, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yamamoto, Sakae, editor, and Mori, Hirohiko, editor

Published
2021
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7. Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review

Author

Garcia-Mendez, Juan P., primary, Lal, Amos, additional, Herasevich, Svetlana, additional, Tekin, Aysun, additional, Pinevich, Yuliya, additional, Lipatov, Kirill, additional, Wang, Hsin-Yi, additional, Qamar, Shahraz, additional, Ayala, Ivan N., additional, Khapov, Ivan, additional, Gerberi, Danielle J., additional, Diedrich, Daniel, additional, Pickering, Brian W., additional, and Herasevich, Vitaly, additional

Published
2023
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11. Diagnostic error among vulnerable populations presenting to the emergency department with cardiovascular and cerebrovascular or neurological symptoms: a systematic review.

Author

Herasevich, Svetlana, Soleimani, Jalal, Huang, Chanyan, Pinevich, Yuliya, Dong, Yue, Pickering, Brian W., Murad, Mohammad H., and Barwise, Amelia K.

Subjects
CARDIOVASCULAR disease diagnosis, CEREBROVASCULAR disease diagnosis, CEREBROVASCULAR disease, NEUROLOGICAL disorders, HOSPITAL emergency services, MEDICAL information storage & retrieval systems, ENGLISH language, SYSTEMATIC reviews, COMMUNICATIVE competence, CARDIOVASCULAR diseases, RACE, RISK assessment, AT-risk people, HEALTH insurance, DESCRIPTIVE statistics, DIAGNOSTIC errors, MEDLINE, AFRICAN Americans, SYMPTOMS
Abstract

Background Diagnostic error (DE) is a common problem in clinical practice, particularly in the emergency department (ED) setting. Among ED patients presenting with cardiovascular or cerebrovascular/neurological symptoms, a delay in diagnosis or failure to hospitalise may be most impactful in terms of adverse outcomes. Minorities and other vulnerable populations may be at higher risk of DE. We aimed to systematically review studies reporting the frequency and causes of DE in under-resourced patients presenting to the ED with cardiovascular or cerebrovascular/neurological symptoms. Methods We searched EBM Reviews, Embase, Medline, Scopus and Web of Science from 2000 through 14 August 2022. Data were abstracted by two independent reviewers using a standardised form. The risk of bias (ROB) was assessed using the Newcastle-Ottawa Scale, and the certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation approach. Results Of the 7342 studies screened, we included 20 studies evaluating 7436,737 patients. Most studies were conducted in the USA, and one study was multicountry. 11 studies evaluated DE in patients with cerebrovascular/ neurological symptoms, 8 studies with cardiovascular symptoms and 1 study examined both types of symptoms. 13 studies investigated missed diagnoses and 7 studies explored delayed diagnoses. There was significant clinical and methodological variability, including heterogeneity of DE definitions and predictor variable definitions as well as methods of DE assessment, study design and reporting. Among the studies evaluating cardiovascular symptoms, black race was significantly associated with higher odds of DE in 4/6 studies evaluating missed acute myocardial infarction (AMI)/acute coronary syndrome (ACS) diagnosis compared with white race (OR from 1.18 (1.12-1.24) to 4.5 (1.8-11.8)). The association between other analysed factors (ethnicity, insurance and limited English proficiency) and DE in this domain varied from study to study and was inconclusive. Among the studies evaluating DE in patients with cerebrovascular/neurological symptoms, no consistent association was found indicating higher or lower odds of DE. Although some studies showed significant differences, these were not consistently in the same direction. The overall ROB was low for most included studies; however, the certainty of evidence was very low, mostly due to serious inconsistency in definitions and measurement approaches across studies. Conclusions This systematic review demonstrated consistent increased odds of missed AMI/ACS diagnosis among black patients presenting to the ED compared with white patients in most studies. No consistent associations between demographic groups and DE related to cerebrovascular/neurological diagnoses were identified. More standardised approaches to study design, measurement of DE and outcomes assessment are needed to understand this problem among vulnerable populations. [ABSTRACT FROM AUTHOR]

Published
2023
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15. The authors reply

Author

Herasevich, Svetlana, primary, Lindroth, Heidi L., additional, Pinevich, Yuliya, additional, Lipatov, Kirill, additional, Tekin, Aysun, additional, Herasevich, Vitaly, additional, Pickering, Brian W., additional, and Barwise, Amelia K., additional

Published
2022
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19. sj-docx-4-his-10.1177_11786329221123540 – Supplemental material for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders

Author

Redmond, Sarah, Barwise, Amelia, Zornes, Sarah, Dong, Yue, Herasevich, Svetlana, Pinevich, Yuliya, Soleimani, Jalal, LeMahieu, Allison, Leppin, Aaron, and Pickering, Brian

Subjects
111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-4-his-10.1177_11786329221123540 for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders by Sarah Redmond, Amelia Barwise, Sarah Zornes, Yue Dong, Svetlana Herasevich, Yuliya Pinevich, Jalal Soleimani, Allison LeMahieu, Aaron Leppin and Brian Pickering in Health Services Insights

Published
2022
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20. sj-docx-1-his-10.1177_11786329221123540 – Supplemental material for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders

Author

Redmond, Sarah, Barwise, Amelia, Zornes, Sarah, Dong, Yue, Herasevich, Svetlana, Pinevich, Yuliya, Soleimani, Jalal, LeMahieu, Allison, Leppin, Aaron, and Pickering, Brian

Subjects
111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-1-his-10.1177_11786329221123540 for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders by Sarah Redmond, Amelia Barwise, Sarah Zornes, Yue Dong, Svetlana Herasevich, Yuliya Pinevich, Jalal Soleimani, Allison LeMahieu, Aaron Leppin and Brian Pickering in Health Services Insights

Published
2022
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21. sj-docx-2-his-10.1177_11786329221123540 – Supplemental material for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders

Author

Redmond, Sarah, Barwise, Amelia, Zornes, Sarah, Dong, Yue, Herasevich, Svetlana, Pinevich, Yuliya, Soleimani, Jalal, LeMahieu, Allison, Leppin, Aaron, and Pickering, Brian

Subjects
111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-2-his-10.1177_11786329221123540 for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders by Sarah Redmond, Amelia Barwise, Sarah Zornes, Yue Dong, Svetlana Herasevich, Yuliya Pinevich, Jalal Soleimani, Allison LeMahieu, Aaron Leppin and Brian Pickering in Health Services Insights

Published
2022
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22. sj-docx-3-his-10.1177_11786329221123540 – Supplemental material for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders

Author

Redmond, Sarah, Barwise, Amelia, Zornes, Sarah, Dong, Yue, Herasevich, Svetlana, Pinevich, Yuliya, Soleimani, Jalal, LeMahieu, Allison, Leppin, Aaron, and Pickering, Brian

Subjects
111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-3-his-10.1177_11786329221123540 for Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders by Sarah Redmond, Amelia Barwise, Sarah Zornes, Yue Dong, Svetlana Herasevich, Yuliya Pinevich, Jalal Soleimani, Allison LeMahieu, Aaron Leppin and Brian Pickering in Health Services Insights

Published
2022
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28. Bedside Clinicians’ Perceptions on the Contributing Role of Diagnostic Errors in Acutely Ill Patient Presentation

Author

Huang, Chanyan, primary, Barwise, Amelia, additional, Soleimani, Jalal, additional, Dong, Yue, additional, Svetlana, Herasevich, additional, Khan, Syed Anjum, additional, Gavin, Anne, additional, Helgeson, Scott A., additional, Moreno-Franco, Pablo, additional, Pinevich, Yuliya, additional, Kashyap, Rahul, additional, Herasevich, Vitaly, additional, Gajic, Ognjen, additional, and Pickering, Brian W., additional

Published
2021
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33. Training and Decision Support for Battlefield Trauma Care

Author

Nemeth, Christopher, primary, Amos-Binks, Adam, additional, Pinevich, Yuliya, additional, Burris, Christie, additional, Keeney, Natalie, additional, Rule, Gregory, additional, Pickering, Brian, additional, Laufersweiler, Dawn, additional, and Heresevich, Vitaly, additional

Published
2020
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34. Validation of a Machine Learning Model for Early Shock Detection.

Author

Pinevich, Yuliya, Amos-Binks, Adam, Burris, Christie S, Rule, Gregory, Bogojevic, Marija, Flint, Isaac, Pickering, Brian W, Nemeth, Christopher P, and Herasevich, Vitaly

Subjects
*MACHINE learning, *RECEIVER operating characteristic curves, *CARDIOGENIC shock, *ELECTRONIC health records, *INTENSIVE care units, *RESEARCH, *VITAL signs, *RETROSPECTIVE studies, *EVALUATION research, *COMPARATIVE studies, *RESEARCH funding, *LONGITUDINAL method
Abstract

Objectives: The objectives of this study were to test in real time a Trauma Triage, Treatment, and Training Decision Support (4TDS) machine learning (ML) model of shock detection in a prospective silent trial, and to evaluate specificity, sensitivity, and other estimates of diagnostic performance compared to the gold standard of electronic medical records (EMRs) review.Design: We performed a single-center diagnostic performance study.Patients and Setting: A prospective cohort consisted of consecutive patients aged 18 years and older who were admitted from May 1 through September 30, 2020 to six Mayo Clinic intensive care units (ICUs) and five progressive care units.Measurements and Main Results: During the study time, 5,384 out of 6,630 hospital admissions were eligible. During the same period, the 4TDS shock model sent 825 alerts and 632 were eligible. Among 632 hospital admissions with alerts, 287 were screened positive and 345 were negative. Among 4,752 hospital admissions without alerts, 78 were screened positive and 4,674 were negative. The area under the receiver operating characteristics curve for the 4TDS shock model was 0.86 (95% CI 0.85-0.87%). The 4TDS shock model demonstrated a sensitivity of 78.6% (95% CI 74.1-82.7%) and a specificity of 93.1% (95% CI 92.4-93.8%). The model showed a positive predictive value of 45.4% (95% CI 42.6-48.3%) and a negative predictive value of 98.4% (95% CI 98-98.6%).Conclusions: We successfully validated an ML model to detect circulatory shock in a prospective observational study. The model used only vital signs and showed moderate performance compared to the gold standard of clinician EMR review when applied to an ICU patient cohort. [ABSTRACT FROM AUTHOR]

Published
2022
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40. Trauma Care Decision Support Under Fire

Author

Nemeth, Christopher, primary, Pickering, Brian, additional, Amos-Binks, Adam, additional, Harrison, Andrew, additional, Pinevich, Yuliya, additional, Lowe, Ryan, additional, Rule, Gregory, additional, Laufersweiler, Dawn, additional, and Herasevich, Vitaly, additional

Published
2019
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41. 1032: CRITICAL CARE CLINICIAN NEEDS FOR PRIORITIZATION OF CARE IN INTENSIVE CARE UNIT: A QUALITATIVE STUDY.

Author

Pinevich, Yuliya, Herasevich, Svetlana, Lindroth, Heidi, Herasevich, Vitaly, Pickering, Brian, and Barwise, Amelia

Subjects
*INTENSIVE care units, *CRITICAL care medicine, *CURRICULUM
Abstract

Our objective was to understand the information and process needs that support patient prioritization by clinicians caring for multiple patients in intensive care unit (ICU) and to inform the refinement of an acute care multi patient viewer (MPV), that was designed to assist clinicians in patient prioritization. B Introduction: b To adequately care for groups of acutely ill patients, clinicians need to develop and maintain situational awareness to inform care prioritization. [Extracted from the article]

Published
2023
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