Abstract T MP88: Algorithms for Identification of Acute Stroke Hospitalizations in Medicare Data
Background: Medicare claims (MC) are a source of nationwide data on various disease conditions including stroke. We developed and tested algorithms to accurately identify acute stroke hospitalizations in MC data using a population-based acute stroke hospitalization database.
Methods: Data were obtained from year 2000 Minnesota Stroke Survey (MSS), a surveillance study of stroke incidence and prevalence in the Minneapolis-St. Paul metro area. Stroke cases were ascertained with acute stroke discharge codes (ICD-9 431, 432, 434, 436, 437) and validated with clinical criteria after medical record abstraction. Stroke was defined as a neurological deficit of vascular origin lasting at least 24 hours or until death. MSS subjects aged 65-74 years (n=464) were linked to MC hospitalization claims. A random sample of non-stroke MC hospitalization claims was included in the dataset (n=1,384). We randomly selected 2/3 of the data for training and 1/3 for testing. Classification and Regression Tree (CART) models were used for algorithm development. We report algorithm sensitivity (SN), specificity (SP), likelihood ratio positive and negative (LR+/LR-), discriminative performance (AUC) and total misclassification error (ME).
Results: The CART algorithm showed high discriminative performance on training and test data (Table). Test data performance was: SN=91%, SP=95%, LR+=19.97, LR-=0.09, AUC 0.93, ME=6%. The algorithm automatically selected these MC variables as informative about stroke hospitalizations: diagnostic group code, hospital discharge codes, hospital discharge destination, number of private room days, physical and occupational therapy charges.
Conclusion: Our CART algorithm shows good performance and is available for validation with other data sets. Potential utility of developed algorithms has broader implications for stroke epidemiology and health services research.
Author Disclosures: C. Fuller: None. A. Banerjee: None. J.S. Pankow: None. K. Lakshminarayan: None.
- © 2014 by American Heart Association, Inc.