 |
 |
 |
 |
 |
 |
 |
|
|
|
|||||||||
|
|||||||||||
Senior Medical Informaticist, Department of Medical Informatics, LDS Hospital & Intermountain Health Care; Professor, Department of Medical Informatics, University of Utah School of Medicine, Salt Lake City, UT
Systems Analyst, Department of Medical Informatics, LDS Hospital & Intermountain Health Care
Head, Section of Biostatistics, Division of Clinical Epidemiology, University of Utah School of Medicine
Associate Director, Informatics Decision Enhancement and Surveillance Center, Veterans Affairs Medical Center; Assistant Professor of Medicine, Division of Geriatrics, University of Utah School of Medicine
Chief, Division of Clinical Epidemiology; Professor of Medicine, University of Utah School of Medicine
Reprints: Dr. Evans, Department of Medical Informatics, LDS Hospital, 8th Ave. and C St., Salt Lake City, UT 84143-0001, fax 810/408-5802, ldsevans{at}ihc.com
BACKGROUND: Many adverse drug events (ADEs) are the result of known pharmacologic properties, and some result from medication errors. However, some are the result of patient-specific risk factors.
OBJECTIVE: To identify inpatient risk factors for ADEs.
METHODS: Conditional logistic regression was used to analyze all
pharmacist-verified ADEs by therapeutic class of drugs and severity during a
10-year study period. All inpatients 
18 years of age from a 520-bed
tertiary teaching hospital were included. Each case patient was matched with
up to 16 control patients. Odds ratios for patient factors associated with
ADEs were calculated from different therapeutic classes of drugs.
RESULTS: Odds ratios for numerous risk factors were identified for 4376 ADEs and were found to vary depending on therapeutic classification. The risk factors for the different classifications were grouped by (1) patient characteristics—female (OR 1.5–1.7), age (0.7–0.9), weight (1.2–1.4), creatinine clearance (0.8–4.7), and number of comorbidities (1.1–12.6); (2) drug administration—dosage (1.2–3.7), administration route (1.4–149.9), and number of concomitant drugs (1.2–2.4); and (3) patient type—service (1.2–4.9), nursing division (1.5–3.8), and diagnosis-related group (1.5–5.7).
CONCLUSIONS: Some risk factors are consistent for all ADEs and across multiple therapeutic classes of drugs, while others are class specific. High-risk agents should be closely monitored based on patient characteristics (gender, age, weight, creatinine clearance, number of comorbidities) and drug administration (dosage, administration route, number of concomitant drugs).
Key Words: adverse drug events, quality improvement, risk factors
Published Online, May 16, 2005. www.theannals.com, DOI 10.1345/aph.1E642
This article has been cited by other articles:
|
|
 |
|
  D. Isacson, L. Johansson, and K. Bingefors Nationwide Survey of Subjectively Reported Adverse Drug Reactions in Sweden Ann. Pharmacother., March 1, 2008; 42(3): 347 - 353. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
O. Oladimeji, K. B Farris, J. G Urmie, and W. R Doucette Risk Factors for Self-Reported Adverse Drug Events Among Medicare Enrollees Ann. Pharmacother., January 1, 2008; 42(1): 53 - 61. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. E. Johnston, D. J. France, D. W. Byrne, H. J. Murff, B. Lee, R. A. Stiles, and T. Speroff Assessment of adverse drug events among patients in a tertiary care medical center Am. J. Health Syst. Pharm., November 15, 2006; 63(22): 2218 - 2227. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. D. Ford, J. Killebrew, P. Fugitt, J. Jacobsen, and E. M. Prystas Study of Medication Errors on a Community Hospital Oncology Ward J. Oncol. Pract, July 1, 2006; 2(4): 149 - 154. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B M. Verdel, P. C Souverein, A. C. Egberts, and H. G. Leufkens Difference in Risks of Allergic Reaction to Sulfonamide Drugs Based on Chemical Structure Ann. Pharmacother., June 1, 2006; 40(6): 1040 - 1046. [Abstract] [Full Text] [PDF]
|
|
 |
 |
 |
 |
 |
 |
 |
