title: Predictors of warfarin-associated adverse events in hospitalized patients: Opportunities to prevent patient harm.
abstract: BACKGROUND
  The optimum international normalized ratio (INR) monitoring frequency for hospitalized patients receiving warfarin is unknown.
  
  
  OBJECTIVE
  Assess relationship between daily versus less frequent INR monitoring and overanticoagulation and warfarin-related adverse events.
  
  
  METHODS
  Retrospective cohort study using Medicare Patient Safety Monitoring System data.
  
  
  METHODS
  Randomly selected acute care hospitals across the United States.
  
  
  METHODS
  Patients hospitalized from 2009 to 2013 for pneumonia, acute cardiac disease, or surgery who received warfarin.
  
  
  METHODS
  None.
  
  
  METHODS
  (1) Association between frequency of INR monitoring and an INR ≥6.0 or warfarin-related adverse event. (2) Association between the rate of change of the INR and a subsequent INR ≥5.0 and ≥6.0.
  
  
  RESULTS
  Among 8529 patients who received warfarin for ≥3 days, for 1549 (18.2%) the INR was not measured on 2 or more days. These patients had higher propensity-adjusted odds ratios (ORs) of having a warfarin-associated adverse event (OR: 1.48, 95% confidence interval [CI]: 1.02-2.17) for cardiac patients and surgical patients (OR: 1.73, 95% CI: 1.20-2.48), with no significant association for pneumonia patients. Cardiac and pneumonia patients with 1 day or more without an INR measurement had higher propensity-adjusted ORs of having an INR ≥6.0 (OR: 1.61, 95% CI: 1.07-2.41 and OR: 1.92, 95% CI: 1.36-2.71, respectively). A 1-day increase in the INR of ≥0.9 occurred in 621 patients (12.5%) and predicted a subsequent INR of ≥6.0 (positive likelihood ratio of 4.2).
  
  
  CONCLUSIONS
  Daily INR measurement and recognition of a rapidly rising INR might decrease the frequency of warfarin-associated adverse events in hospitalized patients.
authors.affiliation: Qualidigm, Wethersfield, Connecticut.|Division of Pulmonary and Critical Care Medicine, University of Connecticut School of Medicine, Farmington, Connecticut.
authors.forename: Mark L
authors.initials: ML
authors.lastname: Metersky
authors.affiliation: Agency for Healthcare Research and Quality, United States Department of Health and Human Services, Rockville, Maryland.
authors.forename: Noel
authors.initials: N
authors.lastname: Eldridge
authors.affiliation: Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
authors.forename: Yun
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Qualidigm, Wethersfield, Connecticut.|Department of Pharmacy, Griffin Hospital, Derby, Connecticut.
authors.forename: Lisa
authors.initials: L
authors.lastname: Jaser
authors.affiliation: Frank H. Netter MD School of Medicine at Quinnipiac, Hamden, Connecticut.
authors.forename: Robert
authors.initials: R
authors.lastname: Bona
authors.affiliation: Qualidigm, Wethersfield, Connecticut.
authors.forename: Sheila
authors.initials: S
authors.lastname: Eckenrode
authors.affiliation: Qualidigm, Wethersfield, Connecticut.
authors.forename: Anila
authors.initials: A
authors.lastname: Bakullari
authors.affiliation: Centers for Medicare & Medicaid, United States Department of Health and Human Services, Baltimore, Maryland.
authors.forename: Mary
authors.initials: M
authors.lastname: Andrawis
authors.affiliation: Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah.
authors.forename: David
authors.initials: D
authors.lastname: Classen
authors.affiliation: Section of General Internal Medicine, Yale University School of Medicine, New Haven, Connecticut.|Section of Cardiovascular Medicine and the Robert Wood Johnson Foundation Clinical Scholars Program, Yale University School of Medicine, New Haven, Connecticut.|Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut.|Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut.
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000925:Anticoagulants / Q000009:adverse effects*; D015331:Cohort Studies; D016903:Drug Monitoring / Q000379:methods / Q000639:trends; D005544:Forecasting; D006323:Heart Arrest / Q000139:chemically induced / Q000453:epidemiology; D006760:Hospitalization / Q000639:trends; D006801:Humans; D019934:International Normalized Ratio / Q000639:trends; D020300:Intracranial Hemorrhages / Q000139:chemically induced / Q000453:epidemiology; D006278:Medicare / Q000639:trends; D008875:Middle Aged; D064406:Patient Harm / Q000517:prevention & control* / Q000639:trends; D011897:Random Allocation; D014481:United States / Q000453:epidemiology; D014859:Warfarin / Q000009:adverse effects*
chemical_list: D000925:Anticoagulants; D014859:Warfarin