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Clinical predictors easily obtained at presentation predict resource utilization in unstable angina
J E Calvin1, L W Klein, B J VandenBerg
1Section of Cardiology, Rush-Presbyterian-St. Luke's Medical Center, Chicago, Ill 60612, USA.
American Heart Journal
|September 15, 1998
Summary
A risk prediction model for unstable angina accurately predicts patient resource utilization, including length of stay and hospital costs. Higher risk groups incurred greater costs, influenced by revascularization procedures like coronary artery bypass grafting.
Area of Science:
- Cardiology
- Health Services Research
Background:
- Unstable angina requires careful resource allocation.
- Predictive models can aid in managing patient care and costs.
Purpose of the Study:
- To evaluate if a risk prediction model for unstable angina can forecast resource utilization.
- To analyze the relationship between patient risk stratification and healthcare resource consumption.
Main Methods:
- Prospective evaluation of 465 unstable angina patients.
- Analysis of resource utilization (procedures, length of stay, costs) across four risk groups.
- Multivariate regression to determine factors influencing hospital costs.
Main Results:
- Higher risk groups (Group 4) showed increased coronary care unit admissions, revascularization procedures (coronary artery bypass grafting), and longer hospital stays.
- Hospital costs significantly increased with higher risk groups, independent of procedures.
- Percutaneous transluminal coronary angioplasty and coronary artery bypass grafting substantially increased costs.
Conclusions:
- Patient acuity, estimated by a risk model, influences resource utilization in unstable angina.
- The risk prediction model independently impacts hospital costs.
- Revascularization procedures, particularly coronary artery surgery, are major drivers of hospital costs.