HEART FAILURE READMISSION RISK PREDICTION: EVALUATION ON DIFFERENT APPROACHES FOR PATIENT LEVEL PROFILING OF READMISSION

Characteristic CMSHF Model YaleCORE HF Risk Calculator Model DataUtilized Administrative/claimsdata at discharge Chart abstraction /clinical data at admission RiskFactor Variables Included Age >=65, GenderPast claims data on diagnoses and procedures Age >=65, GenderComorbidities identifiedVita...

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Bibliographic Details
Published in:Journal of the American College of Cardiology 2016-04, Vol.67 (13), p.1430-1430
Main Authors: Lewis, Connie, Lai, Pikki, Cox, Zachary L, Lenihan, Daniel
Format: Article
Language:English
Subjects:
Accuracy
Cardiology
Cardiovascular
Heart failure
Hospitalization
Internal Medicine
Online Access:Get full text
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Summary:Characteristic CMSHF Model YaleCORE HF Risk Calculator Model DataUtilized Administrative/claimsdata at discharge Chart abstraction /clinical data at admission RiskFactor Variables Included Age >=65, GenderPast claims data on diagnoses and procedures Age >=65, GenderComorbidities identifiedVital signsLaboratory dataLVEF at admission Numberof risk factor variables 37 20 Sensitivity (% of cases with actual readmission successfully identified) 59% 54% Specificity (% of cases without readmission successfully identified as No) 62% 62% Accuracy (successfully classify cases with and without readmission) 62% 56% Stabilityon accuracy over successive 5 years (July 2009 to June 2014) Yes Yes Robuston accuracy for different readmission venues: readmission back to index or readmissionto other hospital.
ISSN:0735-1097
1558-3597
DOI:10.1016/S0735-1097(16)31431-0