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- Publisher Website: 10.1002/pds.1811
- Scopus: eid_2-s2.0-70549105007
- PMID: 19634116
- WOS: WOS:000271782200002
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Article: Methodological variability in detecting prescribing errors and consequences for the evaluation of interventions
Title | Methodological variability in detecting prescribing errors and consequences for the evaluation of interventions |
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Authors | |
Keywords | Electronic prescribing Medication errors Prescribing errors |
Issue Date | 2009 |
Publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/5669 |
Citation | Pharmacoepidemiology And Drug Safety, 2009, v. 18 n. 11, p. 992-999 How to Cite? |
Abstract | Purpose: To compare four methods of detecting prescribing errors (PE) in the same patient cohorts before and after an intervention (computerised physician order entry; CPOE) and to determine whether the impact of CPOE is identified consistently by all methods. Methods: PEs were identified using (1) prospective detection by ward pharmacist; (2) retrospective health record review; (3) retrospective use of a trigger tool and (4) spontaneous reporting over two separate 4-week periods on one surgical ward in a UK teaching hospital. Results: We reviewed 93 patients pre- and 114 post-CPOE. Using all four methods, we identified 135 PE (10.7% of all medication orders) pre-CPOE, and 127 (7.9%) post-CPOE. There was little overlap in PE detected by the different methods: prospective detection identified 48 (36% of all PE) pre- and 30 (24%) post-CPOE; retrospective review (RR) revealed 93 (69%) pre- and 105 (83%) post-CPOE, trigger tool 0 pre- and 2 (2%) post-CPOE and spontaneous reporting 1 (1%) pre- and 1 (1%) post-CPOE. The calculated relative reduction in risk of PE was 50% using prospective data, 12% with RR and 26% using data from all four methods. Conclusions: In this study, each method predominantly identified different PE. A combination of methods may be required to understand the true effectiveness of different interventions. Copyright © 2009 John Wiley & Sons, Ltd. |
Persistent Identifier | http://hdl.handle.net/10722/171389 |
ISSN | 2023 Impact Factor: 2.4 2023 SCImago Journal Rankings: 1.106 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Franklin, BD | en_US |
dc.contributor.author | Birch, S | en_US |
dc.contributor.author | Savage, I | en_US |
dc.contributor.author | Wong, I | en_US |
dc.contributor.author | Woloshynowych, M | en_US |
dc.contributor.author | Jacklin, A | en_US |
dc.contributor.author | Barber, N | en_US |
dc.date.accessioned | 2012-10-30T06:13:49Z | - |
dc.date.available | 2012-10-30T06:13:49Z | - |
dc.date.issued | 2009 | en_US |
dc.identifier.citation | Pharmacoepidemiology And Drug Safety, 2009, v. 18 n. 11, p. 992-999 | en_US |
dc.identifier.issn | 1053-8569 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/171389 | - |
dc.description.abstract | Purpose: To compare four methods of detecting prescribing errors (PE) in the same patient cohorts before and after an intervention (computerised physician order entry; CPOE) and to determine whether the impact of CPOE is identified consistently by all methods. Methods: PEs were identified using (1) prospective detection by ward pharmacist; (2) retrospective health record review; (3) retrospective use of a trigger tool and (4) spontaneous reporting over two separate 4-week periods on one surgical ward in a UK teaching hospital. Results: We reviewed 93 patients pre- and 114 post-CPOE. Using all four methods, we identified 135 PE (10.7% of all medication orders) pre-CPOE, and 127 (7.9%) post-CPOE. There was little overlap in PE detected by the different methods: prospective detection identified 48 (36% of all PE) pre- and 30 (24%) post-CPOE; retrospective review (RR) revealed 93 (69%) pre- and 105 (83%) post-CPOE, trigger tool 0 pre- and 2 (2%) post-CPOE and spontaneous reporting 1 (1%) pre- and 1 (1%) post-CPOE. The calculated relative reduction in risk of PE was 50% using prospective data, 12% with RR and 26% using data from all four methods. Conclusions: In this study, each method predominantly identified different PE. A combination of methods may be required to understand the true effectiveness of different interventions. Copyright © 2009 John Wiley & Sons, Ltd. | en_US |
dc.language | eng | en_US |
dc.publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/5669 | en_US |
dc.relation.ispartof | Pharmacoepidemiology and Drug Safety | en_US |
dc.subject | Electronic prescribing | - |
dc.subject | Medication errors | - |
dc.subject | Prescribing errors | - |
dc.subject.mesh | Drug Prescriptions - Standards | en_US |
dc.subject.mesh | Efficiency, Organizational | en_US |
dc.subject.mesh | Hospitals, Teaching | en_US |
dc.subject.mesh | Humans | en_US |
dc.subject.mesh | London | en_US |
dc.subject.mesh | Medical Order Entry Systems - Organization & Administration - Standards - Statistics & Numerical Data | en_US |
dc.subject.mesh | Medication Errors - Prevention & Control - Statistics & Numerical Data | en_US |
dc.subject.mesh | Medication Systems, Hospital - Organization & Administration - Standards - Statistics & Numerical Data | en_US |
dc.subject.mesh | Prospective Studies | en_US |
dc.subject.mesh | Retrospective Studies | en_US |
dc.title | Methodological variability in detecting prescribing errors and consequences for the evaluation of interventions | en_US |
dc.type | Article | en_US |
dc.identifier.email | Wong, I:wongick@hku.hk | en_US |
dc.identifier.authority | Wong, I=rp01480 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1002/pds.1811 | en_US |
dc.identifier.pmid | 19634116 | - |
dc.identifier.scopus | eid_2-s2.0-70549105007 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-70549105007&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 18 | en_US |
dc.identifier.issue | 11 | en_US |
dc.identifier.spage | 992 | en_US |
dc.identifier.epage | 999 | en_US |
dc.identifier.isi | WOS:000271782200002 | - |
dc.publisher.place | United Kingdom | en_US |
dc.identifier.scopusauthorid | Franklin, BD=16416542300 | en_US |
dc.identifier.scopusauthorid | Birch, S=35797911600 | en_US |
dc.identifier.scopusauthorid | Savage, I=7004074225 | en_US |
dc.identifier.scopusauthorid | Wong, I=7102513915 | en_US |
dc.identifier.scopusauthorid | Woloshynowych, M=16752525900 | en_US |
dc.identifier.scopusauthorid | Jacklin, A=6603125680 | en_US |
dc.identifier.scopusauthorid | Barber, N=7005001200 | en_US |
dc.identifier.issnl | 1053-8569 | - |