title: Development and Validation of a Predictive Model for Short- and Medium-Term Hospital Readmission Following Heart Valve Surgery.
abstract: Although models exist for predicting hospital readmission after coronary artery bypass surgery, no such models exist for predicting readmission after heart valve surgery (HVS).
  
  
  
  Using a geographically and structurally diverse sample of US hospitals (Premier Inpatient Database, January 2007-June 2011), we examined patient, hospital, and clinical factors predictive of short- and medium-term hospital readmission post-HVS. We set aside 20% of hospitals for model validation. A generalized estimating equation model accounted for clustering within hospitals. At 219 hospitals, we identified 38 532 patients (67 years, 56% male, 62% aortic valve surgery) who underwent HVS. A total of 3125 (7.8%) and 4943 (12.8%) patients were readmitted to the index hospital within 1 and 3 months, respectively. Our 3-month model predicted readmission rates between 3% and 61% with fair discrimination (C-statistic, 0.67) and good calibration (predicted vs observed differences in validation cohort averaged 1.9% across all deciles of predicted readmission risk). Results were similar for our 1-month model and our simplified 3-month model (suitable for clinical use), which used the 5 strongest predictors of readmission: transfused units of packed Red blood cells, presence of End-stage renal disease, type of Valve surgery, Emergency hospital admission, and hospital Length of stay (REVEaL).
  
  
  
  We described and validated key factors that predict short- and medium-term hospital readmission post-HVS. These models should enable clinicians to identify individuals with HVS who are at increased risk for hospital readmission and are most likely to benefit from improved postdischarge care and follow-up.
authors: Division of Cardiovascular Medicine, Baystate Medical Center, Springfield, MA Department of Internal Medicine, Baystate Medical Center, Springfield, MA Center for Quality of Care Research, Baystate Medical Center, Springfield, MA Tufts University School of Medicine, Boston, MA quinn.packmd@baystatehealth.org.
authors: Quinn R
authors: QR
authors: Pack
authors: Center for Quality of Care Research, Baystate Medical Center, Springfield, MA.
authors: Aruna
authors: A
authors: Priya
authors: Department of Internal Medicine, Baystate Medical Center, Springfield, MA Center for Quality of Care Research, Baystate Medical Center, Springfield, MA Tufts University School of Medicine, Boston, MA.
authors: Tara
authors: T
authors: Lagu
authors: Center for Quality of Care Research, Baystate Medical Center, Springfield, MA School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA.
authors: Penelope S
authors: PS
authors: Pekow
authors: Department of Surgery, Baystate Medical Center, Springfield, MA.
authors: Richard
authors: R
authors: Engelman
authors: Tufts University School of Medicine, Boston, MA Predictive Analytics and Comparative Effectiveness (PACE) Center, Institute for Clinical Research and Health Policy Studies (ICRHPS), Tufts Medical Center, Boston, MA.
authors: David M
authors: DM
authors: Kent
authors: Department of Internal Medicine, Baystate Medical Center, Springfield, MA Center for Quality of Care Research, Baystate Medical Center, Springfield, MA Tufts University School of Medicine, Boston, MA.
authors: Peter K
authors: PK
authors: Lindenauer
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D058385:Cardiac Valve Annuloplasty; D015897:Comorbidity; D004630:Emergencies / Q000453:epidemiology; D017707:Erythrocyte Transfusion / Q000706:statistics & numerical data; D005260:Female; D006349:Heart Valve Diseases / Q000453:epidemiology / Q000601:surgery*; D019918:Heart Valve Prosthesis Implantation; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D007676:Kidney Failure, Chronic / Q000453:epidemiology; D007902:Length of Stay; D008297:Male; D008875:Middle Aged; D010359:Patient Readmission / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D018570:Risk Assessment; D014481:United States / Q000453:epidemiology; D055815:Young Adult
keywords: aortic valve; mitral valve; model; prediction statistics; readmission; surgery