New Model Could Help Standardize Reporting of Survival for Hospital Cardiac Arrest
A new model to risk-standardize hospital rates of survival for in-hospital cardiac arrest could help hospitals improve quality by allowing them to benchmark their risk-adjusted performance against other hospitals, according to a new study published in the Journal of the American College of Cardiology.
Overall, 10,290 (21.1 percent) patients with an in-hospital cardiac arrest survived to hospital discharge. According to the authors, the survival rates were similar in the derivation (n=6844; 21.0%) and validation cohorts (n=3446; 21.2%). In general, the patients who survived "were younger, more frequently white, more likely to have an initial cardiac arrest rhythm of ventricular fibrillation or pulseless ventricular tachycardia, and had fewer comorbidities or interventions in place (e.g., intravenous vasopressors) at the time of cardiac arrest."
However, despite the reduction in variability with the risk-adjustment methodology, some hospitals did have notable differences in risk-standardized rates of survival. For example, 3.3 percent of hospitals had risk-standardized survival rates of >30%, or ~50% higher than the average hospital. "Which hospital factors or quality improvement initiatives are associated with the higher survival outcomes in these hospitals remain unknown," the authors note. Therefore, they suggest that identification of best practices at these top-performing hospitals be a priority in order to disseminate the information more broadly to other hospitals looking to improve their quality.
Moving forward, the authors note that their model had good discrimination (C-statistic 0.74) and excellent calibration. Importantly, they also note that the model adhered to recommended public reporting standards, including the use of hierarchical models, timely and high-quality data, and clearly defined study population and outcomes.
"Given poor survival outcomes for in-hospital cardiac arrest, there is growing national interest in developing performance metrics to benchmark hospital survival for this condition," the investigators said. "We believe that use of this model to adjust for patient case-mix represents an advance in ongoing efforts to profile hospitals in resuscitation outcomes, with the hope that clinicians and administrators will be stimulated to develop novel and effective quality improvement strategies to improve their hospital's performance."
Keywords: Renal Insufficiency, Tachycardia, Ventricular, Survival Rate, Ventricular Fibrillation, Respiration, Artificial, Comorbidity, Respiratory Insufficiency, Heart Arrest, United States, Risk Adjustment
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