Challenges in identifying the effect of hospital characteristics on outcomes after out-of-hospital cardiac arrest

Challenges in identifying the effect of hospital characteristics on outcomes after out-of-hospital cardiac arrest

e32 Poster Presentations / Resuscitation 83 (2012) e24–e123 AP021 AP022 Challenges in identifying the effect of hospital characteristics on outcom...

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e32

Poster Presentations / Resuscitation 83 (2012) e24–e123

AP021

AP022

Challenges in identifying the effect of hospital characteristics on outcomes after out-of-hospital cardiac arrest

Outcome in relation to primary rhythm in patients with not witnessed out of hospital cardiac arrest and sustained return of spontaneous circulation

Patrick Chow-In Ko 1,∗ , Tsung-Tai Chen 2 , Allen Wen-Hsiang Chiu 3 , Chi-Hung Lin 3 , Ying-Wen Hsiao 4 , Guang-Hua Xiong 4 , Wen-Chu Chiang 1 , Matthew Huei-Ming Ma 1 1 Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan 2 Department of Public Health, Fu Jen Catholic University, Taipei, Taiwan 3 Department of Health, Taipei City Government, Taipei, Taiwan 4 Taipei City Fire Department, Taipei, Taiwan

Study objective: The association between hospital characteristics and patient outcomes might be influenced by the statistical methods while conducting study about the impact of hospital characteristics. Hence, in this study, we demonstrate and compare two kinds of models: fixed effects (logistic) and mixed effects (multilevel) models to assess the impact of hospital characteristics on the patient outcome for out-of-hospital cardiac arrest (OHCA). Methods: Multilevel and logistic analyses were applied to test the models. Data were collected from the Taipei City OHCA Registry for a four-year period. The final available sample size was 4000 patients. Results: Our result demonstrated that the fixed effects model showed critical care hospital designation and private hospital ownership had a significantly positive relationship with the patient outcome, especially for the survival to discharge, however, the mixed effects model indicated no relationship of hospital designation or type with patient outcome. In addition, we found that only 2–3% of the variance in patient outcome resided between hospitals (hospital-level variance), and the total hospital variables (ownership, hospital OHCA volume, and critical care hospital designation) may account for less than 40% of the hospital-level variance using mixed effects model. Conclusion: From a methodological point of view, we suggest that both mixed effects and fixed effects models should be presented together to show sensitivity results that demonstrate hospital influences on the OHCA patient outcomes.

Alexander Spiel ∗ , Christian Wallmüller, Peter Stratil, Andreas Schober, Mathias Stöckl, Christoph Weiser, Christoph Testori, David Hörburger, Stefan Aschauer, Fritz Sterz Medical University of Vienna, Department of Emergency Medicine, Vienna, Austria Purpose of the study: Overall outcome in patients with not witnessed out of hospital cardiac arrest (OHCA) is very poor and some authors even argue against CPR efforts in this patient group. Primary shockable rhythm has a favorable prognosis in witnessed OHCA. We evaluated neurological outcome and survival in relation to primary rhythm in patients with not witnessed OHCA and sustained return of spontaneous circulation (ROSC) treated at our emergency department. Materials and methods: Retrospective chart review (from 2001 to 2012) of not witnessed OHCA patients with sustained return of spontaneous circulation (ROSC) brought by the emergency medical service (EMS) to the emergency department of a tertiary care hospital. Results: During the observation period 253 patients with not witnessed OHCA were treated at our department. Fiftytwo patients never achieved sustained ROSC and were therefore excluded from analysis. The primary rhythm was ventricular fibrillation (VF) in 73 (36%), pulseless electrical activity (PEA) in 50 (25%) and asystole in 65 (32%) patients. In 13 patients the primary rhythm was unknown. Twenty-seven (37%) patients with VF had a favorable neurological outcome, defined as Cerebral Performance Categories (CPC) 1 or 2, and twenty-eight (38%) patients survived for >180 days. Patients with PEA (CPC 1 or 2 and survival for >180 days in 8 patients, 18%) and asystole (CPC 1 or 2 and survival for >180 days in 6 patients, 9%) as primary rhythm had a considerably poorer prognosis. Conclusions: A favorable neurological outcome and a survival of >180 days in more than one third of patients with not witnessed OHCA, sustained ROSC and primary shockable rhythm definitely justifies EMD efforts in this patient group.

Further reading http://dx.doi.org/10.1016/j.resuscitation.2012.08.081 1. Fung V, et al. Meaningful variation in performance: a systematic literature review. Med Care 2010;48:140–8. 2. Austin PC, et al. Comparing hierarchical modeling with traditional logistic regression analysis among patients hospitalized with acute myocardial infarction: should we be analyzing cardiovascular outcomes data differently. Am Heart J 2003;145:27–35. 3. Chen TT, et al. Statistical considerations in assessing the impact of hospital characteristics and cardiac arrest survival. Resuscitation 2010;81:1586. 4. Stub D, et al. Hospital characteristics are associated with patient outcomes following out-of-hospital cardiac arrest. Heart 2011;97:1489–94.

http://dx.doi.org/10.1016/j.resuscitation.2012.08.080

Prevention of cardiac arrest AP023 Standardised communication during crisis on nursing wards reduces unexpected death Koen De Meester ∗ , Martijn Verspuy, Koen Monsieurs, Peter Van Bogaert Antwerp University Hospital, University Antwerp, Edegem, Antwerp, Belgium Purpose: To determine the effect of a standardised communication tool called “Situation Background Assessment Recommendation (SBAR)” on the perception of effective communication between physicians and nurses and on the incidence of serious adverse events (SAEs).1 Method: Before and after intervention study. A period of 10 months before and 10 months after the introduction of SBAR were compared. SAEs were defined as: unexpected deaths (=deaths without Do Not Attempt Resuscitation code), unplanned transfer to an Intensive Care Unit (ICU) and Cardiac Arrest Team calls. Patient