The Epidemiology of Prescribing Errors: The Potential Impact of Computerized Prescriber Order Entry | Clinical Pharmacy and Pharmacology | JAMA Internal Medicine | JAMA Network
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1.
Kohn  LTCorrigan  JMDonaldson  MS To Err Is Human: Building a Safer Health System.  Washington, DC National Academy Press2000;
2.
Bates  DWCullen  DJLaird  N  et al.  Incidence of adverse drug events and potential adverse drug events: implications for prevention.  JAMA. 1995;27429- 34PubMedGoogle ScholarCrossref
3.
Brennan  TALeape  LLLaird  N  et al.  Incidence of adverse events and negligence in hospitalized patients.  N Engl J Med. 1991;324370- 376PubMedGoogle ScholarCrossref
4.
Leape  LLBrennan  TALaird  NM  et al.  The nature of adverse events in hospitalized patients.  N Engl J Med. 1991;324377- 384PubMedGoogle ScholarCrossref
5.
Bates  DWLeape  LLCullen  DJ  et al.  Effect of computerized physician order entry and a team intervention on prevention of serious medication errors.  JAMA. 1998;2801311- 1316PubMedGoogle ScholarCrossref
6.
Bates  DWTeich  JMLee  J  et al.  The impact of computerized physician order entry on medication error prevention.  J Am Med Inform Assoc. 1999;6313- 321PubMedGoogle ScholarCrossref
7.
Kuperman  GJTeich  JMGandhi  TKBates  DW Patient safety and computerized medication ordering at Brigham and Women's Hospital.  Jt Comm J Qual Improv. 2001;27509- 521PubMedGoogle Scholar
8.
The Leapfrog Group, Patient safety: setting standards. Available at: http://www.leapfroggroup.org/safety1.htm. Accessed September 1, 2002.
9.
Bates  DWBoyle  DLVander Vliet  MBSchneider  JLeape  LL Relationship between medication errors and adverse drug events.  J Gen Intern Med. 1995;10199- 205PubMedGoogle ScholarCrossref
10.
Schiff  GDRucker  DT Computerized prescribing: building the electronic infrastructure for better medication usage.  JAMA. 1998;2791024- 1029PubMedGoogle ScholarCrossref
11.
Schiff  GD Computerized prescriber order entry: models and hurdles.  Am J Health Syst Pharm. 2002;591456- 1460PubMedGoogle Scholar
12.
Shojania  KGDuncan  BWMcDonald  KMWachter  RM Safe but sound: patient safety meets evidence-based medicine.  JAMA. 2002;288508- 513PubMedGoogle ScholarCrossref
13.
Scarsi  KKFotis  MANoskin  GA Pharmacist participation in medical rounds reduces medication errors.  Am J Health Syst Pharm. 2002;592089- 2092PubMedGoogle Scholar
14.
Fotis  MA Optimizing Medication Use at NMH.  Chicago, Ill Northwestern Memorial Hospital Pharmacy and Therapeutic Drug Committee2001- 2002
15.
National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP), NCC MERP Index for Categorizing Medication Errors. Available at: http://www.nccmerp.org. Accessed September 1, 2002.
16.
US Pharmacopoeia, Summary of the 1999 Information Submitted to MedMARx: A National Database for Hospital Medication Error Reporting.  Rockville, Md USPC Inc2000;
17.
Lesar  TSBriceland  LLDelcoure  KParmalee  JCMasta-Gronic  VPohl  H Medication prescribing errors in a teaching hospital.  JAMA. 1990;2632329- 2334PubMedGoogle ScholarCrossref
18.
Lesar  TSBriceland  LLStein  DS Factors related to errors in medication prescribing.  JAMA. 1997;277312- 317PubMedGoogle ScholarCrossref
19.
Leape  LLBates  DWCullen  DJ  et al.  Systems analysis of adverse drug events.  JAMA. 1995;27435- 43PubMedGoogle ScholarCrossref
20.
California HealthCare Foundation, Addressing medication errors in hospitals: a practical tool kit. Available at: http://www.chcf.org/topics/view.cfm?itemid=12682. Accessed September 1, 2002.
21.
Dean  BSchachter  MVincent  CBarber  N Causes of prescribing errors in hospital inpatients: a prospective study.  Lancet. 2002;3591373- 1378PubMedGoogle ScholarCrossref
22.
Yarnold  PRSoltysik  RC Theoretical distributions of optima for univariate discrimination of random data.  Decision Sci. 1991;22739- 752Google ScholarCrossref
23.
Yarnold  PRSoltysik  RC Optimal Data Analysis: Guidebook With Software for Windows.  Washington, DC APA BooksIn press
24.
Lesar  TSLomaestro  BMPohl  H Medication-prescribing errors in a teaching hospital: a 9-year experience.  Arch Intern Med. 1997;1571569- 1576PubMedGoogle ScholarCrossref
25.
Folli  HLPoole  RLBenitz  WERusso  JC Medication error prevention by clinical pharmacists in two children's hospitals.  Pediatrics. 1987;79718- 722PubMedGoogle Scholar
26.
Fijn  RVan den Bemt  PMLAChow  MDe Blay  CJDe Jong-Van den Berg  LTWBrouwers  JRBJ Hospital prescribing errors: epidemiological assessment of predictors.  Br J Clin Pharmacol. 2002;53326- 331PubMedGoogle ScholarCrossref
27.
Van den Bemt  PMLAPostma  MJVan Roon  ENChow  MFijn  RBrouwers  JRBJ Cost-benefit analysis of the detection of prescribing errors by hospital pharmacy staff.  Drug Saf. 2002;25135- 143PubMedGoogle ScholarCrossref
28.
Lesar  TS Common prescribing errors [letter].  Ann Intern Med. 1992;117537PubMedGoogle ScholarCrossref
29.
Phillips  JBeam  SBrinker  A  et al.  Retrospective analysis of mortalities associated with medication errors.  Am J Health Syst Pharm. 2001;581835- 1841PubMedGoogle Scholar
30.
Rozich  JDResar  RK Medication safety: one organization's approach to the challenge.  J Clin Outcomes Manag. 2001;827- 34Google Scholar
31.
Bond  CARaehl  CLFranke  T Clinical pharmacy services, hospital pharmacy staffing, and medication errors in United States hospitals.  Pharmacotherapy. 2002;22134- 147PubMedGoogle ScholarCrossref
32.
Peterson  JFBates  DW Automated selection of drugs and drug dose in patients with renal insufficiency.  Medscape Pharmacists. 2002;3Available at: http://www.medscape.com/viewarticle/429055. Accessed September 1, 2002.Google Scholar
33.
Classen  DCPestotnic  SLEvans  RSLloyd  JFBurke  JP Adverse drug events in hospitalized patients: excess length of stay, extra costs, and attributable mortality.  JAMA. 1997;277301- 306PubMedGoogle ScholarCrossref
34.
Eskew  AGeisler  MO'Connor  LSaunders  GVinci  R Enhancing patient safety: clinician order entry with a pharmacy interface.  J Healthc Inf Manag. 2002;16 (1) 52- 7PubMedGoogle Scholar
35.
Chan  W Increasing the success of physician order entry through human factors engineering.  J Healthc Inf Manag. 2002;1671- 79PubMedGoogle Scholar
36.
Hunt  DLHaynes  RBHanna  SESmith  K Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systemic review.  JAMA. 1998;2801339- 1346PubMedGoogle ScholarCrossref
37.
Leape  LLCullen  DJClapp  MD  et al.  Pharmacist participation on physician rounds and adverse drug events in the intensive care unit.  JAMA. 1999;282267- 270PubMedGoogle ScholarCrossref
38.
Boyko  WLYurkowski  PJIvey  MFArmitstead  JARoberts  BL Pharmacist influence on economic and morbidity outcomes in a tertiary care teaching hospital.  Am J Health Syst Pharm. 1997;541591- 1595PubMedGoogle Scholar
39.
Miller  A Prescriber computer order entry: system design.  Hosp Pharm. 2000;351008- 1010Google Scholar
40.
Miller  A Computerized prescriber order entry: implementing the rules engine.  Hosp Pharm. 2002;37413- 417Google Scholar
41.
Thomas  EJLipsitz  SRStuddert  DMBrennan  TA The reliability of medical record review for estimating adverse event rates.  Ann Intern Med. 2002;136812- 816PubMedGoogle ScholarCrossref
Original Investigation
April 12, 2004

The Epidemiology of Prescribing Errors: The Potential Impact of Computerized Prescriber Order Entry

Arch Intern Med. 2004;164(7):785-792. doi:10.1001/archinte.164.7.785
Abstract

Background  Adverse drug events (ADEs) are the most common cause of injury to hospitalized patients and are often preventable. Medication errors resulting in preventable ADEs most commonly occur at the prescribing stage.

Objectives  To describe the epidemiology of medication prescribing errors averted by pharmacists and to assess the likelihood that these errors would be prevented by implementing computerized prescriber order entry (CPOE).

Methods  At a 700-bed academic medical center in Chicago, Ill, clinical staff pharmacists saved all orders that contained a prescribing error for a week in early 2002. Pharmacist investigators subsequently classified drug class, error type, proximal cause, phase of hospitalization, and potential for patient harm and rated the likelihood that CPOE would have prevented the prescribing error.

Results  A total of 1111 prescribing errors were identified (62.4 errors per 1000 medication orders), most occurring on admission (64%). Of these, 30.8% were rated clinically significant and were most frequently related to anti-infective medication orders, incorrect dose, and medication knowledge deficiency. Of all verified prescribing errors, 64.4% were rated as likely to be prevented with CPOE (including 43% of the potentially harmful errors), 13.2% unlikely to be prevented with CPOE, and 22.4% possibly prevented with CPOE depending on specific CPOE system characteristics.

Conclusions  Prescribing errors are common in the hospital setting. While CPOE systems could improve practitioner prescribing, design and implementation of a CPOE system should focus on errors with the greatest potential for patient harm. Pharmacist involvement, in addition to a CPOE system with advanced clinical decision support, is vital for achieving maximum medication safety.

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