External validation of a surgical mortality risk prediction model for inpatient noncardiac surgery in an Australian private health insurance dataset.
Jennifer Richelle ReillyDarren J WongWendy Ann BrownBelinda Jane GabbePaul Stewart MylesPublished in: ANZ journal of surgery (2022)
The low perioperative mortality rate suggests the dataset was not representative of the overall Australian surgical population, primarily due to selection bias and classification bias. Our results suggest SORT may significantly under-predict 30-day mortality in this dataset. Given potential differences in perioperative mortality, private health insurance status and hospital setting should be considered as covariables when a locally validated national surgical mortality risk prediction model is developed.
Keyphrases
- health insurance
- affordable care act
- cardiovascular events
- cardiac surgery
- patients undergoing
- healthcare
- minimally invasive
- machine learning
- mental health
- type diabetes
- deep learning
- cardiovascular disease
- acute care
- coronary artery bypass
- quality improvement
- risk assessment
- climate change
- human health
- electronic health record
- drug induced