R Shulman1, C A McKenzie2, J Landa3, R S Bourne4, A Jones3, M Borthwick5, M Tomlin6, Y H Jani7, D West8, I Bates8. 1. University College London Hospitals NHS Foundation Trust, Pharmacy, London, NW1 2BU, United Kingdom. Electronic address: robert.shulman@uclh.nhs.uk. 2. Institute of Pharmaceutical Sciences, Kings College London, London, SE1 9NH, United Kingdom; Guy's and St Thomas' NHS Foundation Trust, Pharmacy and Critical Care, London, SE1 7EH, United Kingdom. 3. Guy's and St Thomas' NHS Foundation Trust, Pharmacy and Critical Care, London, SE1 7EH, United Kingdom. 4. Sheffield Teaching Hospitals NHS Foundation Trust, Pharmacy, Sheffield, S5 7AU, United Kingdom. 5. Oxford University Hospitals NHS Trust, Pharmacy, Oxford, OX3 7LE, United Kingdom. 6. University Hospitals Southampton NHS Foundation Trust, Pharmacy, Southampton, SO16 6YD, United Kingdom. 7. University College London Hospitals NHS Foundation Trust, Pharmacy, London, NW1 2BU, United Kingdom; UCL School of Pharmacy, London WC1N 1AX, United Kingdom. 8. UCL School of Pharmacy, London WC1N 1AX, United Kingdom.
Abstract
PURPOSE: The purpose was to describe clinical pharmacist interventions across a range of critical care units (CCUs) throughout the United Kingdom, to identify CCU medication error rate and prescription optimization, and to identify the type and impact of each intervention in the prevention of harm and improvement of patient therapy. MATERIALS AND METHODS: A prospective observational study was undertaken in 21 UK CCUs from November 5 to 18, 2012. A data collection web portal was designed where the specialist critical care pharmacist reported all interventions at their site. Each intervention was classified as medication error, optimization, or consult. In addition, a clinical impact scale was used to code the interventions. Interventions were scored as low impact, moderate impact, high impact, and life saving. The final coding was moderated by blinded independent multidisciplinary trialists. RESULTS: A total of 20517 prescriptions were reviewed with 3294 interventions recorded during the weekdays. This resulted in an overall intervention rate of 16.1%: 6.8% were classified as medication errors, 8.3% optimizations, and 1.0% consults. The interventions were classified as low impact (34.0%), moderate impact (46.7%), and high impact (19.3%); and 1 case was life saving. Almost three quarters of interventions were to optimize the effectiveness of and improve safety of pharmacotherapy. CONCLUSIONS: This observational study demonstrated that both medication error resolution and pharmacist-led optimization rates were substantial. Almost 1 in 6 prescriptions required an intervention from the clinical pharmacist. The error rate was slightly lower than an earlier UK prescribing error study (EQUIP). Two thirds of the interventions were of moderate to high impact. Crown
PURPOSE: The purpose was to describe clinical pharmacist interventions across a range of critical care units (CCUs) throughout the United Kingdom, to identify CCU medication error rate and prescription optimization, and to identify the type and impact of each intervention in the prevention of harm and improvement of patient therapy. MATERIALS AND METHODS: A prospective observational study was undertaken in 21 UK CCUs from November 5 to 18, 2012. A data collection web portal was designed where the specialist critical care pharmacist reported all interventions at their site. Each intervention was classified as medication error, optimization, or consult. In addition, a clinical impact scale was used to code the interventions. Interventions were scored as low impact, moderate impact, high impact, and life saving. The final coding was moderated by blinded independent multidisciplinary trialists. RESULTS: A total of 20517 prescriptions were reviewed with 3294 interventions recorded during the weekdays. This resulted in an overall intervention rate of 16.1%: 6.8% were classified as medication errors, 8.3% optimizations, and 1.0% consults. The interventions were classified as low impact (34.0%), moderate impact (46.7%), and high impact (19.3%); and 1 case was life saving. Almost three quarters of interventions were to optimize the effectiveness of and improve safety of pharmacotherapy. CONCLUSIONS: This observational study demonstrated that both medication error resolution and pharmacist-led optimization rates were substantial. Almost 1 in 6 prescriptions required an intervention from the clinical pharmacist. The error rate was slightly lower than an earlier UK prescribing error study (EQUIP). Two thirds of the interventions were of moderate to high impact. Crown
Authors: B E Bosma; N G M Hunfeld; E Roobol-Meuwese; T Dijkstra; S M Coenradie; A Blenke; W Bult; P H G J Melief; M Perenboom-Van Dixhoorn; P M L A van den Bemt Journal: Int J Clin Pharm Date: 2020-08-19
Authors: Pamela MacTavish; Tara Quasim; Martin Shaw; Helen Devine; Malcolm Daniel; John Kinsella; Carl Fenelon; Rakesh Kishore; Theodore J Iwashyna; Joanne McPeake Journal: BMJ Open Qual Date: 2019-09-27