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Herasevich, Svetlana

https://orcid.org/0000-0003-0525-9364

Mayo Clinic

Mayo Clinic

Citations 41

Exercise Oximetry and Pulmonary Complication Risk in Stem Cell Transplant Recipients
Zhang, Zhenmei , Yadav, H., Herasevich, Svetlana

B70. INHALE THE FUTURE: NEW FINDINGS IN PULMONARY FUNCTION | May 1, 2023 | Volume: No volume available | Issue: No issue available | Pages: A4077-A4077

10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a4077 Get It

Diagnostic error among vulnerable populations presenting to the emergency department with cardiovascular and cerebrovascular or neurological symptoms: a systematic review
Herasevich, Svetlana , Soleimani, Jalal , Huang, Chanyan , Pinevich, Yuliya , Pickering, Brian W. , Barwise, Amelia , Murad, Mohammad H, Barwise, Amelia K , Pinevich, Yuliya , Dong, Yue , Murad, M. Hassan

BMJ Quality & Safety | March 27, 2023 | Volume: 32 | Issue: 11 | Pages: 676-688

10.1136/bmjqs-2022-015038 Get It

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. Trial registration number The study protocol was registered in the International Prospective Register of Systematic Reviews PROSPERO 2020 CRD42020178885 and is available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178885.
1036: DIGITAL HEALTH STRATEGIES TO SUPPORT CLINICIAN ICU POPULATION MANAGEMENT: A CROSSOVER STUDY
Lipatov, Kirill , Pinevich, Yuliya , Pickering, Brian, Herasevich, Svetlana , Barwise, Amelia , Lindroth, Heidi , Dong, Yue , Herasevich, Vitaly , Pickering, Brian

Critical Care Medicine | December 15, 2022 | Volume: 51 | Issue: 1 | Pages: 512-512

10.1097/01.ccm.0000909872.67739.e4 Get It

1032: CRITICAL CARE CLINICIAN NEEDS FOR PRIORITIZATION OF CARE IN INTENSIVE CARE UNIT: A QUALITATIVE STUDY
Pinevich, Yuliya , Pickering, Brian, Herasevich, Svetlana , Lindroth, Heidi , Herasevich, Vitaly , Pickering, Brian, Barwise, Amelia

Critical Care Medicine | December 15, 2022 | Volume: 51 | Issue: 1 | Pages: 510-510

10.1097/01.ccm.0000909856.52081.a2 Get It

Post-Transplant and In-Hospital Risk Factors for ARDS After Hematopoietic Stem Cell Transplantation
Frank, Ryan D. , Yadav, Hemang , Herasevich, Svetlana , Hogan, William J. , Alkhateeb, Hassan B. , Limper, Andrew H. , Gajic, Ognjen

Respiratory Care | September 20, 2022 | Volume: 68 | Issue: 1 | Pages: 77-86

10.4187/respcare.10224 Get It

BACKGROUND: ARDS is a serious complication of hematopoietic stem cell transplant (HSCT). Pre-transplant risk factors for developing ARDS after HSCT have been recently identified. The objective of this study was to better understand post-transplant risk factors for developing ARDS after HSCT. METHODS: This was a nested case-control study. ARDS cases were matched to hospitalized non-ARDS controls by age, type of transplantation (allogeneic vs autologous), and time from transplantation. In a conditional logistic regression model, any potential risk factors were adjusted a priori for risk factors known to be associated with ARDS development. RESULTS: One hundred and seventy ARDS cases were matched 1:1 to non-ARDS hospitalized controls. Pre-admission, cases were more likely to be on steroids (odds ratio [OR] 1.90 [1.13–3.19], P = .02). At time of admission, cases had lower platelet count (OR 0.95 [0.91–0.99], P = .02), lower bicarbonate (OR 0.94 [0.88–0.99], P = .035), and higher creatinine (OR 1.91 [1.23–2.94], P = .004). During the first 24 h after admission, cases were more likely to have received transfusion (OR 2.41 [1.48–3.94], P < .001), opioids (OR 2.94 [1.67–5.18], P < .001), and have greater fluid administration (OR 1.52 [1.30–1.78], P < .001). During the hospitalization, ARDS cases had higher temperature (OR 1.77 [1.34–2.33], P < .001) and higher breathing frequency (OR 1.52 [1.33–1.74], P < .001). ARDS cases were more likely to have had sepsis (OR 68.0 [15.2–301.7], P < .001), bloodstream infection (OR 4.59 [2.46–8.57], P < .001), and pneumonia (OR 9.76 [5.01–19.00], P < .001). CONCLUSIONS: Several post-transplant predictors of ARDS development specific to the HSCT population were identified in the pre-hospital and early in-hospital domains. These findings can provide insights into causal mechanisms of ARDS development and be used to develop HSCT-specific risk prediction models.
Contributors to Diagnostic Error or Delay in the Acute Care Setting: A Survey of Clinical Stakeholders
Redmond, Sarah , Barwise, Amelia , Zornes, Sarah, Pinevich, Yuliya , Soleimani, Jalal , Leppin, Aaron L. , Pickering, Brian W. , Minteer, Sarah A. , Herasevich, Svetlana , Leppin, Aaron, Barwise, Amelia K , Dong, Yue , LeMahieu, Allison

Health Services Insights | September 13, 2022 | Volume: 15 | Issue: No issue available | Pages: No page available

10.1177/11786329221123540 Get It

Diagnostic error or delay (DEOD) is common in the acute care setting and results in poor patient outcomes. Many factors contribute to DEOD, but little is known about how contributors may differ across acute care areas and professional roles. As part of a sequential exploratory mixed methods research study, we surveyed acute care clinical stakeholders about the frequency with which different factors contribute to DEOD. Survey respondents could also propose solutions in open text fields. N = 220 clinical stakeholders completed the survey. Care Team Interactions, Systems and Process, Patient, Provider, and Cognitive factors were perceived to contribute to DEOD with similar frequency. Organization and Infrastructure factors were perceived to contribute to DEOD significantly less often. Responses did not vary across acute care setting. Physicians perceived Cognitive factors to contribute to DEOD more frequently compared to those in other roles. Commonly proposed solutions included: technological solutions, organization level fixes, ensuring staff know and are encouraged to work to the full scope of their role, and cultivating a culture of collaboration and respect. Multiple factors contribute to DEOD with similar frequency across acute care areas, suggesting the need for a multi-pronged approach that can be applied across acute care areas.
The Impact of Health Information Technology for Early Detection of Patient Deterioration on Mortality and Length of Stay in the Hospital Acute Care Setting: Systematic Review and Meta-Analysis
Lipatov, Kirill , Pinevich, Yuliya , Tekin, Aysun , Pickering, Brian W. , Barwise, Amelia , Herasevich, Svetlana , Lindroth, Heidi , Barwise, Amelia K , Tekin, Aysun , Herasevich, Vitaly

Critical Care Medicine | April 12, 2022 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1097/ccm.0000000000005554 Get It

Objective: To evaluate the impact of health information technology (HIT) for early detection of patient deterioration on patient mortality and length of stay (LOS) in acute care hospital settings. Data Sources: We searched MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus from 1990 to January 19, 2021. Study Selection: We included studies that enrolled patients hospitalized on the floor, in the ICU, or admitted through the emergency department. Eligible studies compared HIT for early detection of patient deterioration with usual care and reported at least one end point of interest: hospital or ICU LOS or mortality at any time point. Data Extraction: Study data were abstracted by two independent reviewers using a standardized data extraction form. Data Synthesis: Random-effects meta-analysis was used to pool data. Among the 30 eligible studies, seven were randomized controlled trials (RCTs) and 23 were pre-post studies. Compared with usual care, HIT for early detection of patient deterioration was not associated with a reduction in hospital mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT interventions demonstrated a significant association with improved hospital mortality for the entire study cohort (odds ratio, 0.78 [95% CI, 0.70–0.87]) and reduced hospital LOS overall. Conclusions: HIT for early detection of patient deterioration in acute care settings was not significantly associated with improved mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT was associated with improved hospital mortality and LOS; however, these results should be interpreted with caution. The differences in patient outcomes between the findings of the RCTs and pre-post studies may be secondary to confounding caused by unmeasured improvements in practice and workflow over time.
1267: HEALTH INFORMATION TECHNOLOGY TO DETECT PATIENT DETERIORATION: SYSTEMATIC REVIEW AND META-ANALYSIS
Lipatov, Kirill , Pinevich, Yuliya , Pickering, Brian W. , Herasevich, Svetlana , Lindroth, Heidi , Tekin, Aysun , Herasevich, Vitaly , Barwise, Amelia

Critical Care Medicine | December 16, 2021 | Volume: 50 | Issue: 1 | Pages: 634-634

10.1097/01.ccm.0000811392.52191.81 Get It

1113: IN-HOSPITAL RISK FACTORS FOR ACUTE RESPIRATORY DISTRESS SYNDROME AFTER BONE MARROW TRANSPLANTATION
Frank, Ryan D. , Yadav, Hemang , Herasevich, Svetlana , Hogan, William J. , Alkhateeb, Hassan B. , Gajic, Ognjen

Critical Care Medicine | December 16, 2021 | Volume: 50 | Issue: 1 | Pages: 555-555

10.1097/01.ccm.0000810776.95098.6f Get It