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1.
Acad Med ; 99(2): 163, 2024 Feb 01.
Article in English | MEDLINE | ID: mdl-38294425
2.
Am J Emerg Med ; 66: 81-84, 2023 04.
Article in English | MEDLINE | ID: mdl-36736063

ABSTRACT

Emergency Department (ED) crowding and boarding impact safe and effective health care delivery. ED clinicians must balance caring for new arrivals who require stabilization and resuscitation as well as those who need longitudinal care and re-evaluation. These challenges are magnified in the setting of critically ill patients boarding for the intensive care unit. Boarding is a complex issue that has multiple solutions based on resources at individual institutions. Several different models have been described for delivery of critical care in the ED. Here, we describe the development of an ED based critical care consultation service, the early intervention team, at an urban academic ED.


Subject(s)
Critical Care , Intensive Care Units , Humans , Resuscitation , Referral and Consultation , Emergency Service, Hospital , Crowding , Length of Stay
3.
Acad Med ; 2022 Nov 15.
Article in English | MEDLINE | ID: mdl-36512815
4.
Chest ; 161(6): 1620, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35680311
5.
JAMA Netw Open ; 5(4): e227299, 2022 04 01.
Article in English | MEDLINE | ID: mdl-35420659

ABSTRACT

Importance: Bacterial and viral causes of acute respiratory illness (ARI) are difficult to clinically distinguish, resulting in the inappropriate use of antibacterial therapy. The use of a host gene expression-based test that is able to discriminate bacterial from viral infection in less than 1 hour may improve care and antimicrobial stewardship. Objective: To validate the host response bacterial/viral (HR-B/V) test and assess its ability to accurately differentiate bacterial from viral infection among patients with ARI. Design, Setting, and Participants: This prospective multicenter diagnostic study enrolled 755 children and adults with febrile ARI of 7 or fewer days' duration from 10 US emergency departments. Participants were enrolled from October 3, 2014, to September 1, 2019, followed by additional enrollment of patients with COVID-19 from March 20 to December 3, 2020. Clinical adjudication of enrolled participants identified 616 individuals as having bacterial or viral infection. The primary analysis cohort included 334 participants with high-confidence reference adjudications (based on adjudicator concordance and the presence of an identified pathogen confirmed by microbiological testing). A secondary analysis of the entire cohort of 616 participants included cases with low-confidence reference adjudications (based on adjudicator discordance or the absence of an identified pathogen in microbiological testing). Thirty-three participants with COVID-19 were included post hoc. Interventions: The HR-B/V test quantified the expression of 45 host messenger RNAs in approximately 45 minutes to derive a probability of bacterial infection. Main Outcomes and Measures: Performance characteristics for the HR-B/V test compared with clinical adjudication were reported as either bacterial or viral infection or categorized into 4 likelihood groups (viral very likely [probability score <0.19], viral likely [probability score of 0.19-0.40], bacterial likely [probability score of 0.41-0.73], and bacterial very likely [probability score >0.73]) and compared with procalcitonin measurement. Results: Among 755 enrolled participants, the median age was 26 years (IQR, 16-52 years); 360 participants (47.7%) were female, and 395 (52.3%) were male. A total of 13 participants (1.7%) were American Indian, 13 (1.7%) were Asian, 368 (48.7%) were Black, 131 (17.4%) were Hispanic, 3 (0.4%) were Native Hawaiian or Pacific Islander, 297 (39.3%) were White, and 60 (7.9%) were of unspecified race and/or ethnicity. In the primary analysis involving 334 participants, the HR-B/V test had sensitivity of 89.8% (95% CI, 77.8%-96.2%), specificity of 82.1% (95% CI, 77.4%-86.6%), and a negative predictive value (NPV) of 97.9% (95% CI, 95.3%-99.1%) for bacterial infection. In comparison, the sensitivity of procalcitonin measurement was 28.6% (95% CI, 16.2%-40.9%; P < .001), the specificity was 87.0% (95% CI, 82.7%-90.7%; P = .006), and the NPV was 87.6% (95% CI, 85.5%-89.5%; P < .001). When stratified into likelihood groups, the HR-B/V test had an NPV of 98.9% (95% CI, 96.1%-100%) for bacterial infection in the viral very likely group and a positive predictive value of 63.4% (95% CI, 47.2%-77.9%) for bacterial infection in the bacterial very likely group. The HR-B/V test correctly identified 30 of 33 participants (90.9%) with acute COVID-19 as having a viral infection. Conclusions and Relevance: In this study, the HR-B/V test accurately discriminated bacterial from viral infection among patients with febrile ARI and was superior to procalcitonin measurement. The findings suggest that an accurate point-of-need host response test with high NPV may offer an opportunity to improve antibiotic stewardship and patient outcomes.


Subject(s)
Bacterial Infections , COVID-19 , Virus Diseases , Adult , Bacteria , Bacterial Infections/drug therapy , COVID-19/diagnosis , Child , Female , Fever/diagnosis , Gene Expression , Humans , Male , Procalcitonin , Virus Diseases/diagnosis
6.
Crit Care Explor ; 4(3): e0660, 2022 Mar.
Article in English | MEDLINE | ID: mdl-35317241

ABSTRACT

Evaluate the impact of an emergency department (ED)-based critical care consultation service, hypothesizing early consultation results in shorter hospital length of stay (LOS). DESIGN: Retrospective observational study from February 2018 to 2020. SETTING: An urban academic quaternary referral center. PATIENTS: Adult patients greater than or equal to 18 years admitted to the ICU from the ED. Exclusion criteria included age less than 18 years, do not resuscitate/do not intubate documented prior to arrival, advanced directives outlining limitations of care, and inability to calculate baseline modified Sequential Organ Failure Assessment (mSOFA) score. INTERVENTIONS: ED-based critical care consultation by an early intervention team (EIT) initiated by the primary emergency medicine physician compared with usual practice. MEASUREMENTS: The primary outcome was hospital LOS, and secondary outcomes were hospital mortality, ICU LOS, ventilator-free days, and change in the mSOFA. MAIN RESULTS: A total 1,764 patients met inclusion criteria, of which 492 (27.9%) were evaluated by EIT. Final analysis, excluding those without baseline mSOFA score, limited to 1,699 patients, 476 in EIT consultation group, and 1,223 in usual care group. Baseline mSOFA scores (±sd) were higher in the EIT consultation group at 3.6 (±2.4) versus 2.6 (±2.0) in the usual care group. After propensity score matching, there was no difference in the primary outcome: EIT consultation group had a median (interquartile range [IQR]) LOS of 7.0 days (4.0-13.0 d) compared with the usual care group median (IQR) LOS of 7.0 days (4.0-13.0 d), p = 0.64. The median (IQR) boarding time was twice as long subjects in the EIT consultation group at 8.0 (5.0-15.0) compared with 4.0 (3.0-7.0) usual care, p < 0.001. CONCLUSIONS: An ED-based critical care consultation model did not impact hospital LOS. This model was used in the ED and the EIT cared for critically ill patients with higher severity of illness and longer ED boarding times.

9.
Ann Emerg Med ; 76(6): 709-716, 2020 12.
Article in English | MEDLINE | ID: mdl-32653331

ABSTRACT

The National Academy of Medicine has identified emergency department (ED) crowding as a health care delivery problem. Because the ED is a portal of entry to the hospital, 25% of all ED encounters are related to critical illness. Crowding at both an ED and hospital level can thus lead to boarding of a number of critically ill patients in the ED. EDs are required to not only deliver immediate resuscitative and stabilizing care to critically ill patients on presentation but also provide longitudinal care while boarding for the ICU. Crowding and boarding are multifactorial and complex issues, for which different models for delivery of critical care in the ED have been described. Herein, we provide a narrative review of different models of delivery of critical care reported in the literature and highlight aspects for consideration for successful local implementation.


Subject(s)
Critical Care/organization & administration , Critical Illness/therapy , Emergency Service, Hospital/organization & administration , Intensive Care Units/statistics & numerical data , Critical Care/statistics & numerical data , Critical Illness/mortality , Crowding , Delivery of Health Care/organization & administration , Health Workforce/statistics & numerical data , Hospital Mortality/trends , Humans , Length of Stay/economics , Length of Stay/statistics & numerical data , Patient Admission/statistics & numerical data , Resuscitation/methods , United States/epidemiology
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