Tara Collins

Telemedicine coverage for post-operative ICU patients:

Introduction There is an increased demand for intensive care unit (ICU) beds. We sought to determine if we could create a safe surge capacity model to increase ICU capacity by treating ICU patients in the post-anaesthesia care unit (PACU) utilizing a collaborative model between an ICU service and a telemedicine service during peak ICU bed demand. Methods We evaluated patients managed by the surgical critical care service in the surgical intensive care unit (SICU) compared to patients managed in the virtual intensive care unit (VICU) located within the PACU. A retrospective review of all patients seen by the surgical critical care service from January 1st 2008 to July 31st 2011 was conducted at an urban, academic, tertiary centre and level 1 trauma centre. Results Compared to the SICU group (n = 6652), patients in the VICU group (n = 1037) were slightly older (median age 60 (IQR 47–69) versus 58 (IQR 44–70) years, p = 0.002) and had lower acute physiology and chronic health evaluation (APACHE) II scores (median 10 (IQR 7–14) versus 15 (IQR 11–21), p < 0.001). The average amount of time patients spent in the VICU was 13.7 + /–9.6 hours. In the VICU group, 750 (72%) of patients were able to be transferred directly to the floor; 287 (28%) required subsequent admission to the surgical intensive care unit. All patients in the VICU group were alive upon transfer out of the PACU while mortality in the surgical intensive unit cohort was 5.5%. Discussion A collaborative care model between a surgical critical care service and a telemedicine ICU service may safely provide surge capacity during peak periods of ICU bed demand. The specific patient populations for which this approach is most appropriate merits further investigation.

Development and implementation of a risk identification tool to facilitate critical care transitions for high-risk surgical patients

Quality problem Patients recently discharged from the intensive care unit (ICU) are at high risk for clinical deterioration. Initial assessment Unreliable and incomplete handoffs of complex patients contributed to preventable ICU readmissions. Respiratory decompensation was responsible for four times as many readmissions as other causes. Choice of solution Form a multidisciplinary team to address care coordination surrounding the transfer of patients from the ICU to the surgical ward. Implementation A quality improvement intervention incorporating verbal handoffs, time-sensitive patient evaluations and visual cues was piloted over a 1-year period in consecutive high-risk surgical patients discharged from the ICU. Process metrics and clinical outcomes were compared to historical controls. Evaluation The intervention brought the primary team and respiratory therapists to the bedside for a baseline examination within 60 min of ward arrival. Stakeholders viewed the intervention as such a valuable adjunct to patient care that the intervention has become a standard of care. While not significant, in a comparatively older and sicker intervention population, the rate of readmissions due to respiratory decompensation was 12.5%, while 35.0% in the control group (P = 0.28). Lessons learned The implementation of this ICU transition protocol is feasible and internationally applicable, and results in improved care coordination and communication for a high-risk group of patients.

Advanced practitioner-driven critical care outreach to reduce intensive care unit readmission mortality

Objectives: Intensive care unit (ICU) readmission is associated with poorer outcomes as compared to primary admissions. Recognizing new or recurrent critical care issues on the wards postICU discharge may improve outcomes, especially in those subsequently requiring readmission. Herein, we describe and evaluate a pilot surgical critical care outreach initiative to reduce mortality in patients ultimately requiring ICU readmission. Methods: Each patient discharged from the ICU was visited within 48 h by a Critical Care Advanced practitioner who examined the patient, reviewed the chart, recent laboratory results, and orders, and then communicated any concerns to the primary service. Patient demographics, outreach issues identified, and severity of issues were recorded prospectively. Retrospectively, patient outcomes were assessed including the need and timing of any ICU readmission and mortality both before and after outreach implementation. Results: Pre and postoutreach readmission rates were 2.41% (37/1534) versus 3.54% (54/1524), respectively (P = 0.07). Mortality rates before and after outreach were 5.08% (n = 78) versus 5.64% (n = 86) overall (P = 0.052) and 18.9% (n = 7) versus 9.25% (n = 5) for readmissions (P = 0.21), respectively. Conclusions: Critical care outreach postICU discharge did not decrease readmission mortality in this pilot study. Further studies are required to evaluate its effects on not only readmission mortality but also readmission rates and timing along with the incident of subsequent ICU complications. The following core competencies are addressed in this article: Patient care, Systems based practice, Communication.

601: PROPENSITY MATCHED ANALYSIS COMPARING HYPOTENSION BETWEEN ETOMIDATE AND KETAMINE IN SEPTIC PATIENTS

Learning Objectives: Etomidate is commonly used for intubation with minimal hemodynamic effects, however its suppression of cortisol production may have a significant impact on a patient’s ability to maintain hemodynamic stability. Ketamine is also frequently used and has minimal effects on hemodynamics but no proven influence on the adrenal axis. Methods: A retrospective cohort study was performed to compare the incidence of clinical hypotension between ketamine and etomidate in critically ill septic patients. Clinical hypotension was defined as: mean arterial pressure (MAP) decrease > 40% and MAP <70 mmHg, MAP <60 mmHg, systolic blood pressure (SBP) 15 min, initiation of vasopressors, or increase to > 30% of the initial vasopressor dose. In addition, patients were evaluated for length of hospital and ICU stay, and mortality. Statistical analyses included unmatched and matched cohorts using a propensity score analysis. Multivariable logistic regression was used to evaluate the incidence of clinical hypotension 24 hr post intubation and vasopressor requirements. Results: A total of 260 patients were included for analysis (129 etomidate and 131 ketamine) with 138 patients matched 1:1 based on propensity score. Prior to propensity matching, clinical hypotension 24 hr post intubation was 75.2% in the etomidate group compared to 69.5% in the ketamine group (p=0.302) and there was no statistical difference in new post intubation shock (37.2%; 48.5%, p=0.067). After matching no statistical difference was found in clinical hypotension within 24 hr (40.6%; 40.6%, p=0.99). A random-effects logistic regression model was applied and there was a 38% reduction in clinical hypotension with ketamine (OR=0.62; 95% CI 0.3–1.29, p=0.2). There was also no statistical difference in ICU or hospital length of stay or mortality. Conclusions: Administration of etomidate for intubation did not increase the incidence of clinical hypotension 24 hr post intubation when compared to ketamine in septic patients. Large, prospective trials are warranted to confirm these results.