title: Comparison of medication safety effectiveness among nine critical access hospitals.
abstract: OBJECTIVE
  The rates of medication errors across three different medication dispensing and administration systems frequently used in critical access hospitals (CAHs) were analyzed.
  
  
  METHODS
  Nine CAHs agreed to participate in this prospective study and were assigned to one of three groups based on similarities in their medication-use processes: (1) less than 10 hours per week of onsite pharmacy support and no bedside barcode system, (2) onsite pharmacy support for 40 hours per week and no bedside barcode system, and (3) onsite pharmacy support for 40 or more hours per week with a bedside barcode system. Errors were characterized by severity, phase of origination, type, and cause. Characteristics of the medication being administered and a number of best practices were collected for each medication pass. Logistic regression was used to identify significant predictors of errors.
  
  
  RESULTS
  A total of 3103 medication passes were observed. More medication errors originated in hospitals that had onsite pharmacy support for less than 10 hours per week and no bedside barcode system than in other types of hospitals. A bedside barcode system had the greatest impact on lowering the odds of an error reaching the patient. Wrong dose and omission were common error types. Human factors and communication were the two most frequently identified causes of error for all three systems.
  
  
  CONCLUSIONS
  Medication error rates were lower in CAHs with 40 or more hours per week of onsite pharmacy support with or without a bedside barcode system compared with hospitals with less than 10 hours per week of pharmacy support and no bedside barcode system.
authors.affiliation: Gary L. Cochran, Pharm.D., S.M., is Assistant Professor, Department of Pharmacy Practice, College of Pharmacy; and Gleb Haynatzki, Ph.D., is Professor, Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha.
authors.forename: Gary L
authors.initials: GL
authors.lastname: Cochran
authors.forename: Gleb
authors.initials: G
authors.lastname: Haynatzki
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control*; D001330:Electronic Data Processing; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data; D008510:Medication Systems, Hospital / Q000458:organization & administration*; D008875:Middle Aged; D004364:Pharmaceutical Preparations / Q000008:administration & dosage; D010607:Pharmacy Service, Hospital / Q000458:organization & administration*; D019095:Point-of-Care Systems; D011446:Prospective Studies; D012720:Severity of Illness Index; D013997:Time Factors
chemical_list: D004364:Pharmaceutical Preparations