Literature DB >> 17712089

Medication administration discrepancies persist despite electronic ordering.

Fern FitzHenry1, Josh F Peterson, Mark Arrieta, Lemuel R Waitman, Jonathan S Schildcrout, Randolph A Miller.   

Abstract

Background Up to 38% of inpatient medication errors occur at the administration stage. Although they reduce prescribing errors, computerized provider order entry (CPOE) systems do not prevent administration errors or timing discrepancies. This study determined the degree to which CPOE medication orders matched actual dose administration times. METHODS At a 658-bed academic hospital with CPOE but lacking electronic medication administration charting, authors randomly selected adult patients with eligible medication orders from historical 1999-2003 CPOE log files. Retrospective manual chart audits compared expected (from CPOE) and actual timing of medication administrations. Outcomes included: dose omissions, median lag times between ordered and charted administrations, unauthorized doses, wrong dose errors, and the rate of nurses' medication schedule shifting. RESULTS Dose omissions occurred in 756 of 6019 (12.6%) audited administration opportunities; only 313 of the omissions (5.2% of opportunities) were unexplained. Wrong doses and unexpected doses occurred for 0.1% and 0.7% of opportunities, respectively. Median lag from expected first dose to actual charted administration time was 27 minutes (IQR 0-127). Nursing staff shifted from ordered to alternate administration schedules for 10.7% of regularly scheduled recurring medication orders. Chart review identified reasons for dose omissions, delays, and dose shifting. CONCLUSION Inpatient CPOE orders are legible and conveyed electronically to nurses and the pharmacy. Nonetheless, ward-based medication administrations do not consistently occur as ordered. Medication administration discrepancies are likely to persist even after implementing CPOE and bar-coded medication administration unless recommended interventions are made to address issues such as determining the true urgency of medication administration, avoiding overlapping duplicative medication orders, and developing a safe means for shifting dosing schedules.

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Year:  2007        PMID: 17712089      PMCID: PMC2213483          DOI: 10.1197/jamia.M2359

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  27 in total

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Journal:  Hypertension       Date:  2005-08-08       Impact factor: 10.190

6.  Comprehensive analysis of a medication dosing error related to CPOE.

Authors:  Jan Horsky; Gilad J Kuperman; Vimla L Patel
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

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Authors:  D W Bates; L L Leape; D J Cullen; N Laird; L A Petersen; J M Teich; E Burdick; M Hickey; S Kleefield; B Shea; M Vander Vliet; D L Seger
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9.  Impact of computerized physician order entry on clinical practice in a newborn intensive care unit.

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  9 in total

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Journal:  Med Decis Making       Date:  2010-03-30       Impact factor: 2.583

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Authors:  Mei Liu; Eugenia Renne McPeek Hinz; Michael Edwin Matheny; Joshua C Denny; Jonathan Scott Schildcrout; Randolph A Miller; Hua Xu
Journal:  J Am Med Inform Assoc       Date:  2012-11-17       Impact factor: 4.497

3.  Duplicate orders: an unintended consequence of computerized provider/physician order entry (CPOE) implementation: analysis and mitigation strategies.

Authors:  S Magid; C Forrer; S Shaha
Journal:  Appl Clin Inform       Date:  2012-10-17       Impact factor: 2.342

4.  Dose omissions in hospitalized patients in a UK hospital: an analysis of the relative contribution of adverse drug reactions.

Authors:  Jamie J Coleman; Sarah E McDowell; Robin E Ferner
Journal:  Drug Saf       Date:  2012-08-01       Impact factor: 5.606

5.  Reducing patient re-identification risk for laboratory results within research datasets.

Authors:  Ravi V Atreya; Joshua C Smith; Allison B McCoy; Bradley Malin; Randolph A Miller
Journal:  J Am Med Inform Assoc       Date:  2012-07-21       Impact factor: 4.497

6.  Effectiveness of bar coded medication alerts for elevated potassium.

Authors:  Ryan P Radecki; Allison B McCoy; Anwar M Sirajuddin; Robert E Murphy; Dean F Sittig
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

7.  Using Latent Class Analysis to Identify Sophistication Categories of Electronic Medical Record Systems in U.S. Acute Care Hospitals.

Authors:  Christopher M Shea; Bryan J Weiner; Charles M Belden
Journal:  Soc Sci Comput Rev       Date:  2012-02-06       Impact factor: 4.578

8.  Missed medication doses in hospitalised patients: a descriptive account of quality improvement measures and time series analysis.

Authors:  Jamie J Coleman; James Hodson; Hannah L Brooks; David Rosser
Journal:  Int J Qual Health Care       Date:  2013-06-05       Impact factor: 2.038

9.  Chapter 13: Mining electronic health records in the genomics era.

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Journal:  PLoS Comput Biol       Date:  2012-12-27       Impact factor: 4.475

  9 in total

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