New Canadian AMI prediction models demonstrated improved discrimination for 30-day in-hospital mortality (c-statistic 0.834 vs 0.814) and 30-day urgent readmission compared with existing models.
Observational (n=153,523)
Yes
Do newly developed AMI prediction models provide better discrimination for 30-day mortality and readmission compared to existing models in Canadian hospitals?
Newly developed prediction models for AMI mortality and readmission demonstrated improved discrimination over existing models, making them suitable for profiling hospital performance in Canada.
Effect estimate: c-statistic 0.834 (mortality), 0.679 (readmission)
BACKGROUND: Given changes in the care and outcomes of acute myocardial infarction (AMI) patients over the past several decades, we sought to develop prediction models that could be used to generate accurate risk-adjusted mortality and readmission outcomes for hospitals in current practice across Canada. METHODS: A Canadian national expert panel was convened to define appropriate AMI patients for reporting and develop prediction models. Preliminary candidate variable evaluation was conducted using Ontario patients hospitalized with a most responsible diagnosis of AMI from April 1, 2015 to March 31, 2018. National data from the Canadian Institute for Health Information was used to develop AMI prediction models. The main outcomes were 30-day all-cause in-hospital mortality and 30-day urgent all-cause readmission. Discrimination of these models (measured by c-statistics) was compared with that of existing Canadian Institute for Health Information models in the same study cohort. RESULTS: The AMI mortality model was assessed in 54,240 Ontario AMI patients and 153,523 AMI patients across Canada. We observed a 30-day in-hospital mortality rate of 6.3%, and a 30-day all-cause urgent readmission rate of 10.7% in Canada. The final Canadian AMI mortality model included 12 variables and had a c-statistic of 0.834. For readmission, the model had 13 variables and a c-statistic of 0.679. Discrimination of the new AMI models had higher c-statistics compared with existing models (c-statistic 0.814 for mortality; 0.673 for readmission). CONCLUSIONS: In this national collaboration, we developed mortality and readmission models that are suitable for profiling performance of hospitals treating AMI patients in Canada.
Ko et al. (Sat,) conducted a observational in Acute myocardial infarction (AMI) (n=153,523). New AMI prediction models vs. Existing Canadian Institute for Health Information models was evaluated on 30-day all-cause in-hospital mortality and 30-day urgent all-cause readmission (c-statistic 0.834 (mortality), 0.679 (readmission)). New Canadian AMI prediction models demonstrated improved discrimination for 30-day in-hospital mortality (c-statistic 0.834 vs 0.814) and 30-day urgent readmission compared with existing models.