AIM: To develop a core list of 100 commonly prescribed drugs to support prescribing education. METHODS: A retrospective analysis of prescribing data from primary care in England (2006 and 2008) and from two London Teaching Hospitals (2007 and 2009) was performed. A survey of prescribing by foundation year 1 (FY1) doctors in 39 NHS Trusts across London was carried out. RESULTS: A core list of 100 commonly prescribed drugs comprising ≥0.1% prescriptions in primary and/or secondary care was developed in 2006/7. The core list remained stable over 2 years. FY1 doctors prescribed 65% drugs on the list at least monthly. Seventy-six% of FY1 doctors did not regularly prescribe any drugs not on the core list. There was a strong correlation between prescribing frequency (prescriptions for each drug class expressed as percentage of all prescriptions written) and error rate described in the EQUIP study (errors made when prescribing each drug class expressed as a percentage of all errors made), n= 39, r= 0.861, P= 0.000. CONCLUSIONS: Our core drug list identifies drugs that are commonly used and associated with error and is stable over at least 2 years. This list can now be used to develop learning resources and training programmes to improve prescribing of drugs in regular use. Complementary skills required for prescribing less familiar drugs must be developed in parallel. Ongoing research is required to monitor the effect of new training initiatives on prescribing error and patient safety.
AIM: To develop a core list of 100 commonly prescribed drugs to support prescribing education. METHODS: A retrospective analysis of prescribing data from primary care in England (2006 and 2008) and from two London Teaching Hospitals (2007 and 2009) was performed. A survey of prescribing by foundation year 1 (FY1) doctors in 39 NHS Trusts across London was carried out. RESULTS: A core list of 100 commonly prescribed drugs comprising ≥0.1% prescriptions in primary and/or secondary care was developed in 2006/7. The core list remained stable over 2 years. FY1 doctors prescribed 65% drugs on the list at least monthly. Seventy-six% of FY1 doctors did not regularly prescribe any drugs not on the core list. There was a strong correlation between prescribing frequency (prescriptions for each drug class expressed as percentage of all prescriptions written) and error rate described in the EQUIP study (errors made when prescribing each drug class expressed as a percentage of all errors made), n= 39, r= 0.861, P= 0.000. CONCLUSIONS: Our core drug list identifies drugs that are commonly used and associated with error and is stable over at least 2 years. This list can now be used to develop learning resources and training programmes to improve prescribing of drugs in regular use. Complementary skills required for prescribing less familiar drugs must be developed in parallel. Ongoing research is required to monitor the effect of new training initiatives on prescribing error and patient safety.
Authors: T P G M De Vries; J M A Daniels; C W Mulder; O A Groot; L Wewerinke; K I Barnes; H A Bakathir; N A G M Hassan; L Van Bortel; M Kriska; B Santoso; E J Sanz; M Thomas; L E Ziganshina; P D Bezemer; C Van Kan; M C Richir; H V Hogerzeil Journal: Eur J Clin Pharmacol Date: 2008-06 Impact factor: 2.953
Authors: Selma Audi; Daniel R Burrage; Dagan O Lonsdale; Sarah Pontefract; Jamie J Coleman; Andrew W Hitchings; Emma H Baker Journal: Br J Clin Pharmacol Date: 2018-08-10 Impact factor: 4.335
Authors: Widya N Insani; Cate Whittlesea; Hassan Alwafi; Kenneth K C Man; Sarah Chapman; Li Wei Journal: PLoS One Date: 2021-05-26 Impact factor: 3.240