Two predictive models created using ACC's Chest Pain – MI Registry data could predict length of stay (LOS) and discharge to a postacute facility after hospital admission for an acute myocardial infarction (AMI), according to a study published in Circulation: Cardiovascular Quality and Outcomes.

Jason H. Wasfy, MD, MPhil, FACC, et al., used an analysis cohort of 906,324 patients admitted with a STEMI or an NSTEMI to a hospital participating in ACC's Chest Pain – MI Registry between July 1, 2008 to March 31, 2017. Of these, 633,737 patients (70 percent) were included in the training cohort and 272,587 patients (30 percent) in the validation cohort.

The authors developed hierarchical proportional models to predict LOS and hierarchical logistic regression models to predict discharge to postacute care (extended care, transitional care unit or rehabilitation).

After multivariable adjustment and stepwise elimination, factors independently associated with a longer LOS included: older age and at admission heart failure, higher heart rate, systolic blood pressure <150 mm Hg or >150 mm Hg, shock, diabetes, lower glomerular filtration rate, and lower hemoglobin. After multivariable adjustment and stepwise elimination, factors independently associated with greater odds of discharge to a postacute facility included: older age and at admission heart failure, higher heart rate, shock, prior cerebrovascular disease and lower hemoglobin.

The authors write, "We have demonstrated that with clinical characteristics known at the time of initial hospitalization for AMI, both LOS and postacute utilization can be predicted with moderate and strong predictive accuracy, respectively."

They add, "We think that these models may substantially improve the ability of health care providers and health delivery organizations to improve performance in [episode payment models] and other types of payment mechanisms that incentivize judicious use of resources and costs, although further research into how best to use these models is needed."

Clinical Topics: Vascular Medicine

Keywords: Chest Pain MI Registry, Subacute Care, Logistic Models, Glomerular Filtration Rate, Length of Stay, Blood Pressure, Heart Rate, Diabetes Mellitus, Chest Pain, Registries, National Cardiovascular Data Registries, Cerebrovascular Disorders, Health Personnel, Hemoglobins

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