12 research outputs found

    Characteristics of U.S. acute care hospitals that have implemented telemedicine critical care

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    OBJECTIVES: Telemedicine critical care is associated with improved efficiency, quality, and cost-effectiveness. As of 2010, fewer than 5% of U.S. hospitals had telemedicine critical care, and fewer than 10% of ICU beds were covered. We evaluated recent telemedicine critical care implementation and bed coverage rates in the United States and compared characteristics of hospitals with and without telemedicine critical care. DESIGN: Cross-sectional study of 2018 American Hospital Association Annual Survey Database. SETTING: U.S. hospitals. PATIENTS: None. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We obtained data regarding telemedicine critical care implementation, ICU capability (defined as ≥ 1 ICU bed), other hospital characteristics, and the Herfindahl-Hirschman Index, a measure of ICU market competition based on hospital referral regions. Among 4,396 hospitals (response rate 71%), 788 (17.9%) had telemedicine critical care, providing potential coverage to 27,624 (28% of total) ICU beds. Among 306 hospital referral regions, 197 (64%) had a respondent hospital with telemedicine critical care. Telemedicine critical care implementation was associated with being a nonprofit (odds ratio, 7.75; 95% CI, 5.18-11.58) or public (odds ratio, 4.16 [2.57-6.73]) compared with for-profit hospital; membership in a health system (odds ratio, 3.83 [2.89-5.08]; stroke telemedicine presence (odds ratio, 6.87 [5.35-8.81]); ICU capability (odds ratio, 1.68 [1.25-2.26]); and more competitive ICU markets (odds ratio per 1,000-point decrease in Herfindahl-Hirschman Index 1.11 [1.01-1.22]). Notably, rural critical access hospitals had lower odds of telemedicine critical care implementation (odds ratio, 0.49 [0.34-0.70]). Teaching status, geographic region, and rurality were not associated with telemedicine critical care implementation. CONCLUSIONS: About one fifth of respondent hospitals had telemedicine critical care by 2018, providing potential coverage of nearly one third of reported ICU beds. This represents a substantial increase in telemedicine critical care implementation over the last decade. Future expansion to include more rural hospitals that could benefit most may be aided by addressing hospital financial and market barriers to telemedicine critical care implementation

    Associations between subspecialty fellowship interest and knowledge of internal medicine: A hypothesis-generating study of internal medicine residents

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    <p>Abstract</p> <p>Background</p> <p>Little is known about whether and how medical knowledge relates to interest in subspecialty fellowship training. The purpose of this study was to examine the relationships between residents' interest in subspecialty fellowship training and their knowledge of internal medicine (IM).</p> <p>Methods</p> <p>A questionnaire was emailed to 48 categorical postgraduate-year (PGY) two and three residents at a New York university-affiliated IM residency program in 2007 using the Survey Monkey online survey instrument. Overall and content area-specific percentile scores from the IM in-training examination (IM-ITE) for the same year was used to determine objective knowledge.</p> <p>Results</p> <p>Forty-five of 48 residents (response rate was 93.8%) completed the survey. Twenty-two (49%) were PG2 residents and 23(51%) were PGY3 residents. Sixty percent of respondents were male. Six (13%) residents were graduates of U.S. medical schools. Eight (18%) reported formal clinical training prior to starting internal medicine residency in the U.S. Of this latter group, 6 (75%) had training in IM and 6 (75) % reported a training length of 3 years or less. Thirty-seven of 45 (82%) residents had a subspecialty fellowship interest. Residents with a fellowship interest had a greater mean overall objective knowledge percentile score (56.44 vs. 31.67; p = 0.04) as well as greater mean percentile scores in all content areas of IM. The adjusted mean difference was statistically significant (p < 0.02) across three content areas.</p> <p>Conclusions</p> <p>More than half of surveyed residents indicated interest in pursuing a subspecialty fellowship. Fellowship interest appears positively associated with general medical knowledge in this study population. Further work is needed to explore motivation and study patterns among internal medicine residents.</p

    Risk Factors for and Prediction of Post-Intubation Hypotension in Critically Ill Adults: A Multicenter Prospective Cohort Study

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    OBJECTIVE: Hypotension following endotracheal intubation in the ICU is associated with poor outcomes. There is no formal prediction tool to help estimate the onset of this hemodynamic compromise. Our objective was to derive and validate a prediction model for immediate hypotension following endotracheal intubation. METHODS: A multicenter, prospective, cohort study enrolling 934 adults who underwent endotracheal intubation across 16 medical/surgical ICUs in the United States from July 2015-January 2017 was conducted to derive and validate a prediction model for immediate hypotension following endotracheal intubation. We defined hypotension as: 1) mean arterial pressure \u3c 65 mmHg; 2) systolic blood pressure \u3c 80 mmHg and/or decrease in systolic blood pressure of 40% from baseline; 3) or the initiation or increase in any vasopressor in the 30 minutes following endotracheal intubation. RESULTS: Post-intubation hypotension developed in 344 (36.8%) patients. In the full cohort, 11 variables were independently associated with hypotension: increasing illness severity; increasing age; sepsis diagnosis; endotracheal intubation in the setting of cardiac arrest, mean arterial pressure \u3c 65 mmHg, and acute respiratory failure; diuretic use 24 hours preceding endotracheal intubation; decreasing systolic blood pressure from 130 mmHg; catecholamine and phenylephrine use immediately prior to endotracheal intubation; and use of etomidate during endotracheal intubation. A model excluding unstable patients’ pre-intubation (those receiving catecholamine vasopressors and/or who were intubated in the setting of cardiac arrest) was also developed and included the above variables with the exception of sepsis and etomidate. In the full cohort, the 11 variable model had a C-statistic of 0.75 (95% CI 0.72, 0.78). In the stable cohort, the 7 variable model C-statistic was 0.71 (95% CI 0.67, 0.75). In both cohorts, a clinical risk score was developed stratifying patients’ risk of hypotension. CONCLUSIONS: A novel multivariable risk score predicted post-intubation hypotension with accuracy in both unstable and stable critically ill patients. STUDY REGISTRATION: Clinicaltrials.gov identifier: NCT02508948 and Registered Report Identifier: RR2-10.2196/11101

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    Risk factors for and outcomes associated with peri-intubation hypoxemia: A multicenter prospective cohort study

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    BACKGROUND: Little is known about hypoxemia surrounding endotracheal intubation in the critically ill. Thus, we sought to identify risk factors associated with peri-intubation hypoxemia and its effects\u27 on the critically ill. METHODS: Data from a multicenter, prospective, cohort study enrolling 1,033 critically ill adults who underwent endotracheal intubation across 16 medical/surgical ICUs in the United States from July 2015-January 2017 were used to identify risk factors associated with peri-intubation hypoxemia and its effects on patient outcomes. We defined hypoxemia as any pulse oximetry ≤ 88% during and up to 30 minutes following endotracheal intubation. Results: In the full analysis (n = 1,033), 123 (11.9%) patients experienced the primary outcome. Five risk factors independently associated with our outcome were identified on multiple logistic regression: cardiac related reason for endotracheal intubation (OR 1.67, [95% CI 1.04, 2.69]); pre-intubation noninvasive ventilation (OR 1.66, [95% CI 1.09, 2.54]); emergency intubation (OR 1.65, [95% CI 1.06, 2.55]); moderate-severe difficult bag-mask ventilation (OR 2.68, [95% CI 1.72, 4.19]); and crystalloid administration within the preceding 24 hours (OR 1.24, [95% CI 1.07, 1.45]; per liter up to 4 liters). Higher baseline SpO2 was found to be protective (OR 0.93, [95% CI 0.91, 0.96]; per percent up to 97%). Consistent results were seen in a separate analysis on only stable patients (n = 921, 93 [10.1%]) (those without baseline hypoxemia ≤ 88%). Peri-intubation hypoxemia was associated with in-hospital mortality (OR 2.40, [95% CI 1.33, 4.31]; stable patients: OR 2.67, [95% CI 1.38, 5.17]) but not ICU length of stay (point estimate 0.9 days, [95% CI -1.0, 2.8 days]; stable patients: point estimate 1.5 days, [95% CI -0.4, 3.4 days]) after adjusting for age, body mass index, illness severity, airway related reason for intubation (i.e., acute respiratory failure), and baseline SPO2. CONCLUSIONS: Patients with pre-existing noninvasive ventilation and volume loading who were intubated emergently in the setting of hemodynamic compromise with bag-mask ventilation described as moderate-severe were at increased risk for peri-intubation hypoxemia. Higher baseline oxygenation was found to be protective against peri-intubation hypoxemia. Peri-intubation hypoxemia was associated with in-hospital mortality but not ICU length of stay. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT02508948 and Registered Report Identifier: RR2-10.2196/11101

    Risk factors for and prediction of post-intubation hypotension in critically ill adults: A multicenter prospective cohort study

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    OBJECTIVE: Hypotension following endotracheal intubation in the ICU is associated with poor outcomes. There is no formal prediction tool to help estimate the onset of this hemodynamic compromise. Our objective was to derive and validate a prediction model for immediate hypotension following endotracheal intubation. METHODS: A multicenter, prospective, cohort study enrolling 934 adults who underwent endotracheal intubation across 16 medical/surgical ICUs in the United States from July 2015-January 2017 was conducted to derive and validate a prediction model for immediate hypotension following endotracheal intubation. We defined hypotension as: 1) mean arterial pressure \u3c65 \u3emmHg; 2) systolic blood pressure/or decrease in systolic blood pressure of 40% from baseline; 3) or the initiation or increase in any vasopressor in the 30 minutes following endotracheal intubation. RESULTS: Post-intubation hypotension developed in 344 (36.8%) patients. In the full cohort, 11 variables were independently associated with hypotension: increasing illness severity; increasing age; sepsis diagnosis; endotracheal intubation in the setting of cardiac arrest, mean arterial pressure \u3c65 \u3emmHg, and acute respiratory failure; diuretic use 24 hours preceding endotracheal intubation; decreasing systolic blood pressure from 130 mmHg; catecholamine and phenylephrine use immediately prior to endotracheal intubation; and use of etomidate during endotracheal intubation. A model excluding unstable patients\u27 pre-intubation (those receiving catecholamine vasopressors and/or who were intubated in the setting of cardiac arrest) was also developed and included the above variables with the exception of sepsis and etomidate. In the full cohort, the 11 variable model had a C-statistic of 0.75 (95% CI 0.72, 0.78). In the stable cohort, the 7 variable model C-statistic was 0.71 (95% CI 0.67, 0.75). In both cohorts, a clinical risk score was developed stratifying patients\u27 risk of hypotension. CONCLUSIONS: A novel multivariable risk score predicted post-intubation hypotension with accuracy in both unstable and stable critically ill patients. STUDY REGISTRATION: Clinicaltrials.gov identifier: NCT02508948 and Registered Report Identifier: RR2-10.2196/11101
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