title: Frequency and predictors of prescription-related issues after hospital discharge.
abstract: BACKGROUND
  In the period immediately following hospital discharge, patients often experience difficulty with medication management. The problems related to patients' handling of discharge prescriptions are not well characterized.
  
  
  METHODS
  We conducted a large observational study of patients discharged from 170 community hospitals in 2005. By combining clinical, administrative, and call center data, we were able to examine independent predictors of prescription-related issues in the 48-72 hours after hospital discharge. Issues included: not picking up prescribed discharge medications, not knowing if these medications had been picked up, not taking discharge medications, and not understanding how to take the medications.
  
  
  RESULTS
  More than half (57.0%) of the 31,199 subjects in the study were women, and the mean age was 61.1 years. Overall, 7.2% of patients (n = 2253) reported prescription-related issues, most often not filling discharge prescriptions. In multivariable analyses, prescription-related issues were more common among adults age 35-49; women; patients with Medicare HMO coverage, Medicaid, or no insurance; adults with higher severity of illness ratings; and patients prescribed 6 or more medications or an inhaler. Predictors of fewer problems were being age 65 or older; having HMO or commercial insurance; being prescribed antibiotics, anticoagulants, or angiotensin II receptor blockers; and having a major diagnosis in the skin or musculoskeletal categories.
  
  
  CONCLUSIONS
  About 7% of patients reported prescription-related issues within a few days of hospital discharge. High-risk patients should be identified and offered additional assistance prior to discharge and receive a follow-up phone call to assess if discharge prescriptions have been filled.
authors.affiliation: Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA. sunil.kripalani@vanderbilt.edu
authors.forename: Sunil
authors.initials: S
authors.lastname: Kripalani
authors.forename: Megan
authors.initials: M
authors.lastname: Price
authors.forename: Victoria
authors.initials: V
authors.lastname: Vigil
authors.forename: Kenneth R
authors.initials: KR
authors.lastname: Epstein
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003953:Diagnosis-Related Groups; D011307:Drug Prescriptions; D005260:Female; D006753:Hospital Records; D006764:Hospitals, Community; D006801:Humans; D007348:Insurance, Health; D007407:Interviews as Topic; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D019370:Observation; D016017:Odds Ratio; D010349:Patient Compliance / Q000523:psychology* / Q000706:statistics & numerical data; D010351:Patient Discharge / Q000592:standards*; D012646:Self Administration / Q000523:psychology* / Q000706:statistics & numerical data; D012720:Severity of Illness Index; D012737:Sex Factors; D014481:United States