scholarly journals Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients: A Before and After Study

PLoS Medicine ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. e1001164 ◽  
Author(s):  
Johanna I. Westbrook ◽  
Margaret Reckmann ◽  
Ling Li ◽  
William B. Runciman ◽  
Rosemary Burke ◽  
...  
Keyword(s):  
Error Rates ◽  
Electronic Prescribing ◽  
Prescribing Error ◽  
Before And After ◽  
Before And After Study

scholarly journals The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study

2020 ◽  
Vol 11 (02) ◽  
pp. 323-335 ◽  
Author(s):  
Moninne M. Howlett ◽  
Eileen Butler ◽  
Karen M. Lavelle ◽  
Brian J. Cleary ◽  
Cormac V. Breatnach
Keyword(s):  
Intensive Care ◽  
New Technology ◽  
Tertiary Care ◽  
Pediatric Intensive Care ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Prescribing Errors ◽  
Before And After ◽  
The Impact ◽  
Before And After Study

Abstract Background Increased use of health information technology (HIT) has been advocated as a medication error reduction strategy. Evidence of its benefits in the pediatric setting remains limited. In 2012, electronic prescribing (ICCA, Philips, United Kingdom) and standard concentration infusions (SCIs)—facilitated by smart-pump technology—were introduced into the pediatric intensive care unit (PICU) of an Irish tertiary-care pediatric hospital. Objective The aim of this study is to assess the impact of the new technology on the rate and severity of PICU prescribing errors and identify technology-generated errors. Methods A retrospective, before and after study design, was employed. Medication orders were reviewed over 24 weeks distributed across four time periods: preimplementation (Epoch 1); postimplementation of SCIs (Epoch 2); immediate postimplementation of electronic prescribing (Epoch 3); and 1 year postimplementation (Epoch 4). Only orders reviewed by a clinical pharmacist were included. Prespecified definitions, multidisciplinary consensus and validated grading methods were utilized. Results A total of 3,356 medication orders for 288 patients were included. Overall error rates were similar in Epoch 1 and 4 (10.2 vs. 9.8%; p = 0.8), but error types differed (p < 0.001). Incomplete and wrong unit errors were eradicated; duplicate orders increased. Dosing errors remained most common. A total of 27% of postimplementation errors were technology-generated. Implementation of SCIs alone was associated with significant reductions in infusion-related prescribing errors (29.0% [Epoch 1] to 14.6% [Epoch 2]; p < 0.001). Further reductions (8.4% [Epoch 4]) were identified after implementation of electronically generated infusion orders. Non-infusion error severity was unchanged (p = 0.13); fewer infusion errors reached the patient (p < 0.01). No errors causing harm were identified. Conclusion The limitations of electronic prescribing in reducing overall prescribing errors in PICU have been demonstrated. The replacement of weight-based infusions with SCIs was associated with significant reductions in infusion prescribing errors. Technology-generated errors were common, highlighting the need for on-going research on HIT implementation in pediatric settings.

P30 The effects of introducing electronic prescribing for paediatric chemotherapy using aria on prescribing error rates at a primary treatment centre

2018 ◽  
Vol 103 (2) ◽  
pp. e2.33-e2
Author(s):  
Peter Cook ◽  
Andy Fox
Keyword(s):  
Acute Lymphoblastic Leukaemia ◽  
Error Rate ◽  
Lymphoblastic Leukaemia ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Patient Specific ◽  
Prescribing Errors ◽  
Prescribing Error ◽  
Error Type ◽  
Before And After

IntroductionPrescribing of medication in children is a very complex process that involves an understanding of paediatric physiology, disease states, medication used and pharmacokinetics as well as patient specific details, their co-morbidities and their clinical condition. The most common medication errors have been identified as dosing, route of administration, and frequency of administration. Computerised provider order entry has been shown to reduce the number of prescribing errors related to chemotherapy as well as the likelihood of dose and calculation errors in paediatric chemotherapy prescribing. Locally, paediatric chemotherapy is prescribed on pre-printed paper prescriptions. Adaptation and implementation of ARIA electronic prescribing (EP) system for use in paediatric chemotherapy was undertaken by a Specialist Paediatric Oncology Pharmacist and was rolled out for use in January 2016 for patients with acute lymphoblastic leukaemia.MethodThe United Kingdom National Randomised Trial for Children and Young Adults with Acute Lymphoblastic Leukaemia and Lymphoma 2011 (UKALL, 2011) was developed for use on EP, with prescribing of all other chemotherapy remaining on paper. The number and type of prescribing errors were collected during a pre-implementation phase from January 2015 to June 2015. After the introduction of EP and following a 2 month acclimatisation period, a second period of data collection took place between March 2016 and July 2016. Overall prescribing error rates and the frequency of each error type were calculated both before and after implementation.ResultsBefore the introduction of EP for paediatric chemotherapy, the overall error rate was 18.4% with a total of 16 different errors seen. Post implementation, overall error rate increased to 25.7% (p<0.001) with a total of 10 different errors seen. After introduction of EP, prescribing error rates on paper were 30.6% and on EP were 7.0% (p<0.001). Only 5 different error types were seen with electronic prescribing. The most commonly seen errors in prescribing with paper, both before and after were almost eliminated with the introduction of EP.ConclusionThe introduction of EP has resulted in a significant reduction in prescribing error rates compared to paper based prescribing for paediatric chemotherapy. Overall the prescribing error rate increased after the introduction of EP but this was related to an increased rate on the paper prescriptions. One possible reason for this was the use of dual systems for prescribing. In addition there was unforeseen relocation and building work within the paediatric cancer unit, which affected prescribing time allocation. There were also several staff shortages within the prescribing team after implementation and this resulted in an increased workload on the remaining chemotherapy prescribers. All these issues could have attributed to the increase in error rates. The most common errors seen with chemotherapy prescribing have been reduced with EP as protocols have been developed with a focus on prescribing safety. Further work is needed as more prescribing takes place on EP to assess the full impact it has on paediatric chemotherapy error rates.

scholarly journals How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis

2020 ◽  
Author(s):  
Peter J Gates ◽  
Rae-Anne Hardie ◽  
Magdalena Z Raban ◽  
Ling Li ◽  
Johanna I Westbrook
Keyword(s):  
Systematic Review ◽  
Medication Error ◽  
Medication Errors ◽  
Meta Analysis ◽  
Error Rates ◽  
Prescribing Error ◽  
Before And After ◽  
Actual Harm ◽  
Computer Based ◽  
Wide Scale

Abstract Objective To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS. Materials and Methods We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed. Results There was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18–8.38, P = .8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72–0.83, P = .004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence. Discussion and Conclusion Despite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks.

scholarly journals Changes in medication administration error rates associated with the introduction of electronic medication systems in hospitals: a multisite controlled before and after study

2020 ◽  
Vol 27 (3) ◽  
pp. e100170
Author(s):  
Johanna I Westbrook ◽  
Neroli S Sunderland ◽  
Amanda Woods ◽  
Magda Z Raban ◽  
Peter Gates ◽  
...  
Keyword(s):  
Medication Administration ◽  
Error Rates ◽  
Teaching Hospitals ◽  
Medication Administration Error ◽  
Medication Systems ◽  
Before And After ◽  
Wrong Dose ◽  
Administration Error ◽  
Trained Observers ◽  
Before And After Study

BackgroundElectronic medication systems (EMS) have been highly effective in reducing prescribing errors, but little research has investigated their effects on medication administration errors (MAEs).ObjectiveTo assess changes in MAE rates and types associated with EMS implementation.MethodsThis was a controlled before and after study (three intervention and three control wards) at two adult teaching hospitals. Intervention wards used an EMS with no bar-coding. Independent, trained observers shadowed nurses and recorded medications administered and compliance with 10 safety procedures. Observational data were compared against medication charts to identify errors (eg, wrong dose). Potential error severity was classified on a 5-point scale, with those scoring ≥3 identified as serious. Changes in MAE rates preintervention and postintervention by study group, accounting for differences at baseline, were calculated.Results7451 administrations were observed (4176 pre-EMS and 3275 post-EMS). At baseline, 30.2% of administrations contained ≥1 MAE, with wrong intravenous rate, timing, volume and dose the most frequent. Post-EMS, MAEs decreased on intervention wards relative to control wards by 4.2 errors per 100 administrations (95% CI 0.2 to 8.3; p=0.04). Wrong timing errors alone decreased by 3.4 per 100 administrations (95% CI 0.01 to 6.7; p<0.05). EMS use was associated with an absolute decline in potentially serious MAEs by 2.4% (95% CI 0.8 to 3.9; p=0.003), a 56% reduction in the proportion of potentially serious MAEs. At baseline, 74.1% of administrations were non-compliant with ≥1 of 10 procedures and this rate did not significantly improve post-EMS.ConclusionsImplementation of EMS was associated with a modest, but significant, reduction in overall MAE rate, but halved the proportion of MAEs rated as potentially serious.

scholarly journals Electronic-prescribing tools improve N-acetylcysteine prescription accuracy and timeliness for patients who present following a paracetamol overdose: A digital innovation quality-improvement project

2020 ◽  
Vol 6 ◽  
pp. 205520762096504
Author(s):  
Adam McCulloch ◽  
Asif Sarwar ◽  
Tom Bate ◽  
Dave Thompson ◽  
Patrick McDowell ◽  
...  
Keyword(s):  
Secondary Care ◽  
Error Rates ◽  
Paracetamol Overdose ◽  
Electronic Prescribing ◽  
Care Hospital ◽  
Improvement Project ◽  
Prescription Errors ◽  
Electronic Tool ◽  
Before And After ◽  
The Uk

Objectives Prescription error rates and delays in treatment provision are high for N-acetylcysteine (NAC) when prescribed for paracetamol overdose (POD). We hypothesised that an electronic tool which proposed the complete NAC regimen would reduce prescription errors and improve the timeliness of NAC provision. Error rates and delays in the provision of NAC were assessed following POD, before and after the implementation of an electronic prescribing tool. Methods The NAC electronic prescribing tool proposed the three NAC infusions (dosed for weight) following entry of the patient’s weight. All NAC prescriptions were reviewed during a three-month period prior to and after the tool’s implementation. Error rates were divided into dose, infusion volume or infusion rate. Delays in NAC provision were identified using national Emergency Medicine guidelines. Results 108 NAC prescriptions were analysed for all adult patients admitted to the emergency department of a secondary care hospital in the UK between July-September 2017 and August-October 2018, respectively. There were no differences in the demographics of patients or the seniority of the prescribing clinician before or after the introduction of the electronic tool. The electronic prescribing tool was associated with a decrease in prescribing errors (25% to 0%, p < 0.0071) and an increase in the provision of NAC within recommended times (11.1% to 47.4%, p = 0.029). Conclusions An electronic prescribing tool improved prescription errors and the timeliness of NAC provision following POD. Further studies will determine the effect of this on length of stay and the benefit of wider implementation in other secondary care hospitals.

scholarly journals P029 Audit of aciclovir prescribing to assess whether changing the order of drop down box options in an electronic prescribing system can reduce prescribing errors

2019 ◽  
Vol 104 (7) ◽  
pp. e2.33-e2
Author(s):  
Clarissa Gunning ◽  
Jennifer Gray
Keyword(s):  
Patient Safety ◽  
Intensive Care ◽  
Improve Patient Safety ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Contributory Factor ◽  
List Type ◽  
Prescribing Errors ◽  
Prescribing Error ◽  
Dosing Error

AimIn December 2016 it was identified that there had been multiple reports of prescribing errors with intravenous aciclovir on the paediatric intensive care unit (PICU). After investigation it was concluded that prescribers choosing incorrectly from a drop down menu of drug and dosing options on the electronic prescribing (EP) system was the main contributory factor. From 01/02/17 the aciclovir drop down options were prioritised, with the most frequently used option appearing first, to encourage prescribers to pick the correct regimen.MethodsThe trust has been using the Phillips ICCA EP system across all intensive care units since 2016. Picking errors when prescribing are known to be a potential risk within EP systems, however tailoring these systems to guide choice also has the potential to improve patient safety by reducing the risk of prescribing errors.1 Aciclovir has a complex range of dosing recommendations, especially in paediatrics, and incorrect prescribing increases the likelihood of subtherapeutic treatment or adverse effects. The aim of this audit is to assess whether changing the order of prescription choices on the drop down menu in the EP system reduced prescribing error rates for intravenous aciclovir. All prescriptions for aciclovir on PICU were identified during the 6 months before and after implementing the change, from 01/08/16 to 31/07/17. 65 prescriptions were included in the audit and were reviewed retrospectively using the EP system and electronic medical notes to assess whether the prescribed aciclovir dose and route was correct for the patient’s age, weight and indication as well as whether the appropriate drop down option had been selected by the prescriber. Dosing was assessed against recommendations in the British National Formulary for children and trust empirical antibiotic guidelines.ResultsDosing errors were found in 22% (14/65) of prescriptions overall during the review period. Before the change was implemented 26% (9/35) of aciclovir prescription doses were incorrect, reducing to 17% (5/30) after the change. The overall dosing error rate was 14% (7/50) in prescriptions where the correct drop down option was chosen, in comparison to 47% (7/15) in cases where the wrong option had been selected, suggesting the importance of choosing the correct pre-set option to minimise prescribing error rates. In cases where doses were incorrect, the prescriber had chosen the incorrect pre-set drop down option for the patient’s age and indication in 78% (7/9) of prescriptions before the order change compared to 0% (0/5) afterwards.ConclusionThese results suggest that prescribing error rates were reduced after making alterations to the order of prescription choices on the drop down menu in the EP system and that prioritising the order of these options may positively influence prescribing. Errors were not completely eliminated suggesting more work is required to further minimise risk.ReferenceAhmed Z, Garfield S, Jani Y, et al. Impact of electronic prescribing on patient safety in hospitals: implications for the UK. Pharm J 2016;8:1–11.

scholarly journals 1 Developing consensus on hospital prescribing indicators of potential harm for infants and children

2018 ◽  
Vol 103 (2) ◽  
pp. e2.1-e2
Author(s):  
Andy Fox
Keyword(s):  
Expert Panel ◽  
Clinical Decision ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Prescribing Errors ◽  
Prescribing Error ◽  
Prescribing Indicators ◽  
Potential Harm ◽  
The Uk ◽  
Paediatric Prescribing

AimsTo develop a list of hospital based paediatric prescribing indicators that can be used to assess the impact of electronic prescribing or clinical decision support tools on paediatric prescribing errors.BackgroundMedication errors are a major cause for concern in the NHS. Prescribing is part of the medication use process and is a complex task requiring an understanding of medicines, disease processes, and patient parameters. Systematic reviews have reported that medication errors occur in as many as 50% of hospital admissions and prescribing error rates in the UK hospitals vary between 9% and 15%.Prescribing for children is further complicated by the need to take into account weight, altered physiology and pharmacokinetics. Prescribing error rates of 13.1% have been reported in children with a potentially greater impact due to the nature of the patients.Electronic prescribing (EP) while relatively uncommon in UK hospitals is an important tool in reducing prescribing errors. EP systems have been shown to have a positive impact on prescribing errors, however methodologies vary and the reduction in harm is rarely investigated. A standard tool to allow an evaluation of the harm reduction is desirable and currently does not exist for the paediatric setting.MethodsTwo rounds of an electronic consensus method (eDelphi) were carried out with 21 expert panellists from the UK. Panellists were asked to score each prescribing indicator for its likelihood of occurrence and severity of outcome should the error occur. The scores were combined to produce a risk score and a median score for each indicator calculated. The degree of consensus between panellists was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or higher was achieved and were in the high risk categories.ResultsAn expert panel consisting of 8 pharmacists and 13 paediatricians with a total of 437 years of clinical experience completed an exploratory round and two rounds of scoring. This identified 41 paediatric prescribing indicators with a high risk rating and greater than 80% consensus. The most common error type within the indicators was wrong dose (n=19) and the most common drug classes were antimicrobials (n=10) and cardiovascular (n=7).ConclusionsA set of 41 paediatric prescribing indicators describing potential harm for the hospital setting have been identified by an expert panel. The indicators provide a standardised method of evaluation of prescribing data on both paper and electronic systems. They can also be used to assess implementation of clinical decision support systems or other quality improvement initiatives.

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