Literature DB >> 16180938

The incidence of prescribing errors in hospital inpatients: an overview of the research methods.

Bryony Dean Franklin1, Charles Vincent, Mike Schachter, Nick Barber.   

Abstract

Many different methods have been used to study the incidence of prescribing errors in hospital inpatients. The objectives of this review were to outline the methods used, highlight their strengths and limitations, and summarise the incidence of prescribing errors reported. Methods used may be retrospective or prospective and based on process or on outcome. Reported prescribing error rates vary widely, ranging from 0.3% to 39.1% of medication orders written and from 1% to 100% of hospital admissions. Unfortunately, there is no standard denominator for use when expressing prescribing error rates. It could be argued that the most meaningful is the number of medication orders written; however, it is also helpful to consider the number of medication orders written per patient stay in order to understand the risk that a given prescribing error rate poses to an individual patient. Because of wide variation in the definitions and methods used, it is difficult to make comparisons between different studies. Each method for identifying prescribing errors has advantages and disadvantages. Process-based studies potentially allow all errors to be identified, giving more scope for the identification of trends and learning opportunities, and it may be easier to collect sufficient data to show statistically significant changes in prescribing error rates following interventions to reduce them. However, studies based on process may be criticised for focusing on many minor errors that are very unlikely to have resulted in patient harm. Focusing instead on harm, as in outcome-based studies, allows efforts to reduce errors to be targeted on those areas that are likely to result in the highest impact. Therefore, the most appropriate method depends on the study's aims. However, using a combination of methods is likely to be the most useful approach if comprehensive data are required.

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Year:  2005        PMID: 16180938     DOI: 10.2165/00002018-200528100-00005

Source DB:  PubMed          Journal:  Drug Saf        ISSN: 0114-5916            Impact factor:   5.606


  50 in total

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Authors:  B Dean; N Barber; M Schachter
Journal:  Qual Health Care       Date:  2000-12

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Authors:  B Dean; M Schachter; C Vincent; N Barber
Journal:  Qual Saf Health Care       Date:  2002-12

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Journal:  JAMA       Date:  2001-07-25       Impact factor: 56.272

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Journal:  Br J Clin Pharmacol       Date:  2001-07       Impact factor: 4.335

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Journal:  J R Coll Gen Pract       Date:  1989-03

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Authors:  A C O'Neil; L A Petersen; E F Cook; D W Bates; T H Lee; T A Brennan
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  44 in total

1.  Pharmacists' interventions in prescribing errors at hospital discharge: an observational study in the context of an electronic prescribing system in a UK teaching hospital.

Authors:  Derar H Abdel-Qader; Lindsay Harper; Judith A Cantrill; Mary P Tully
Journal:  Drug Saf       Date:  2010-11-01       Impact factor: 5.606

2.  Pharmaceutical interventions on prescription problems in a Danish pharmacy setting.

Authors:  Anton Pottegård; Jesper Hallas; Jens Søndergaard
Journal:  Int J Clin Pharm       Date:  2011-11-15

3.  Medication error in mental health: implications for primary care.

Authors:  Ian D Maidment; Henk Parmentier
Journal:  Ment Health Fam Med       Date:  2009-12

Review 4.  Tools for Assessing Potential Significance of Pharmacist Interventions: A Systematic Review.

Authors:  Thi-Ha Vo; Bruno Charpiat; Claire Catoire; Michel Juste; Renaud Roubille; François-Xavier Rose; Sébastien Chanoine; Jean-Luc Bosson; Ornella Conort; Benoît Allenet; Pierrick Bedouch
Journal:  Drug Saf       Date:  2016-02       Impact factor: 5.606

5.  Errors associated with applying decision support by suggesting default doses for aminoglycosides.

Authors:  Saeid Eslami; Ameen Abu-Hanna; Nicolette F de Keizer; Evert de Jonge
Journal:  Drug Saf       Date:  2006       Impact factor: 5.606

6.  Providing feedback to hospital doctors about prescribing errors; a pilot study.

Authors:  Bryony Dean Franklin; Kara O'Grady; Christos Paschalides; Martin Utley; Steve Gallivan; Ann Jacklin; Nick Barber
Journal:  Pharm World Sci       Date:  2007-02-20

Review 7.  Evaluation of outpatient computerized physician medication order entry systems: a systematic review.

Authors:  Saeid Eslami; Ameen Abu-Hanna; Nicolette F de Keizer
Journal:  J Am Med Inform Assoc       Date:  2007-04-25       Impact factor: 4.497

8.  Medication errors caused by junior doctors.

Authors:  James McLay; Sarah Ross
Journal:  BMJ       Date:  2008-02-07

9.  Is the principle of a stable Heinrich ratio a myth? A multimethod analysis.

Authors:  Steve Gallivan; Katja Taxis; Bryony Dean Franklin; Nick Barber
Journal:  Drug Saf       Date:  2008       Impact factor: 5.606

10.  Prescribing errors during hospital inpatient care: factors influencing identification by pharmacists.

Authors:  Mary P Tully; Iain E Buchan
Journal:  Pharm World Sci       Date:  2009-09-24
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