Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data
Objective Readmission rates are high following acute myocardial infarction (AMI), but risk stratification has proved difficult because known risk factors are only weakly predictive. In the present study, we applied hospital data to identify the risk of unplanned admission following AMI hospitalisati...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal Article |
| Published: |
CSIRO
2014
|
| Online Access: | http://hdl.handle.net/20.500.11937/18594 |