SP3 The effect of electronic prescribing and medicines administration systems (epmass) on paediatric medication errors

2018 ◽  
Vol 103 (2) ◽  
pp. e1.23-e1
Author(s):  
Aragon Octavio ◽  
Fayyaz Goher ◽  
Gill Andrea ◽  
Morecroft Charles

BackgroundThe complex nature of paediatric prescribing makes this population more vulnerable to medication errors.1Electronic Prescribing and Medicines Administration Systems (EPMASs) have been suggested to improve paediatric medication safety by reducing prescribing errors.AimTo identify and compare the number and nature of paediatric medication errors pre and post introduction of an EPMAS at a tertiary paediatric hospital.MethodologyPharmacists collected data monthly on the number of new items prescribed and the number of errors (if any) detected in these prescriptions following methodology from the EQUIP study.2 The EPMAS Meditechv6 was introduced in June 2015. Data analysed included forms from 1st-January-2015 to 30th-June-2015 (period 1: pre-EPMAS) and 1st-January-2016 to 30th-June-2016 (period 2: post-EPMAS). The analysis aimed to investigate the rate, type and severity of errors as well as the prescriber grade, prescribing stage and drug class associated with each. Descriptive statistical methods were used to analyse the frequency and nature of errors pre and post implementation of Meditech. Statistical significance was tested using a contingency Chi-squared (χ2) test for the difference in error rates across both periods and a Mann-Whitney test for the difference between the severities of errors across both periodsResultsAn increase of 6.4% in error rate was detected post-Meditech introduction with 67 errors in 1706 items (3.9%) during period 1 and 151 errors in 1459 items (10.3%) during period 2 (p<0.001, χ2 test). FY2 doctors and ‘admission stage’ were associated with the highest error rates across both periods. Minor severity errors were the most common in both periods, with 55.2% in period 1% and 66.2% in period 2. No statistical difference was detected (p=0.403) in the severity of errors reported although the proportion of significant and serious errors decreased from 38.8% to 27.8% and 6.0% to 0.7% respectively. No errors were classed to be potentially lethal in period 1, however there was one such incident in period 2. Underdosing was the most common error type in period 1 (22.4%), falling to 4.0% in period 2. Omission on admission was the most common error type in period 2, with an error rate of 37.7% vs 20.9% in period 1. Antibacterials and analgesics were the most common classes of drugs involved in errors in both periods, although a wider range of drug classes were involved in errors post Meditech introductionConclusionA significant increase of 6.4% in error rate was found post implementation of Meditech highlighting the concept of EPMAS-facilitated errors. The positive effect of EPMASs is also apparent as the incidence of significant and serious errors decreased in period 2, although this difference was not statistically significant. Reaching definitive conclusions is difficult due to the lack of available research into the effects of EPMASs on paediatric prescribing and due to methodological limitations. However, it can be suggested that introducing functions such as comprehensive decision support and dose calculators may overcome the shortcomings of the current system3 and allow for the true benefits of EPMASs in improving paediatric medication safety to be demonstrated.ReferencesNational Patient Safety Agency. Review of patient safety for children and young people 2009. England: National Reporting and Learning Services. http://www.nrls.npsa.nhs.uk/resources/?entryid45=5986 [Accessed: 29th October 2016].Dornan T, et al. An in-depth investigation into causes of prescribing errors by foundation trainees in relation to their medical education: EQUIP study. Final Report to the General Medical Council 2009. http://www.gmcuk.org/FINAL_Report_prevalence_and_causes_of_prescribing_errors.pdf_28935150.pdf [Accessed: 9th November 2016].Johnson KB, Lehmann CU. Electronic prescribing in paediatrics: Toward safer and more effective medication management. Paediatrics 2013;131(4):e1350–e1356. doi:10.1542/peds.2013-0193

2018 ◽  
Vol 103 (2) ◽  
pp. e2.33-e2
Author(s):  
Peter Cook ◽  
Andy Fox

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.


2020 ◽  
Vol 105 (9) ◽  
pp. e26.1-e26
Author(s):  
Kate Morgan

BackgroundA prescribing error is a preventable error that may lead to inappropriate medication use and patient harm(1). Prescribing errors are particularly important in paediatrics where dose calculations are complicated and small errors can result in significant morbidity and mortality.1 In 2017 pharmacy data showed that paediatric prescribing errors were an issue at our Hospital regarding the severity and high numbers of errors, especially for antibiotics and analgesia.ObjectivesTo achieve a zero prescribing error rate for paediatric within the hospital.MethodForm the Paediatric Medication Errors Prevention (PMEP) group consisting of the Paediatric Consultant, Paediatric Pharmacist, Children’s Assessment Unit Sister and Practice Education Senior Nurse.Paediatric Pharmacist to record and feedback all paediatric prescribing errors weekly at Doctors’ handover.Paediatric Pharmacist/Nurses to DATIX report all significant medication prescribing errorsPaediatric Pharmacist to produce and communicate monthly pharmacy prescribing newsletter.Paediatric Pharmacist to produce quick reference charts for the drugs with the most common prescribing errors e.g. antibiotics and analgesiaPaediatric Doctors to request a second check from another Doctor or Ward Sister when prescribing any medication on the drug chart of take home prescription.Paediatric Pharmacist to target Doctors’ induction to improve prescribing and implement a prescribing test.Doctors to complete reflections for errors with their educationsal supervisors.This study did not require ethics approval.ResultsFollowing implementation of the above strategies, there was a 33% reduction in the number of prescribing errors recorded by the Paediatric Pharmacist daily intervention log from 2017/2018 to 2018/2019. There were 163 prescribing errors for 2017/2018 compared to 110 for 2018/2019.ConclusionThe formation of the PMEP group and implementation of strategies to reduce paediatric prescribing errors has positively impacted on reducing the error rate at the hospital. It has also raised awareness of the necessity to report all errors and actively find ways to prevent these from re-occurring. Further work is required to reduce these errors to zero including targeting non paediatric teams prescribing on paediatrics and implementing Pharmacists prescribing on consultant ward rounds. Future work would also include replicating this model in other specialities e.g. neonatal intensive care to achieve the same success rate in reducing medication errors.ReferenceDavis T. Paediatric prescribing errors. Arch Dis Child. 2011;96:489–91. Accessed via http://adc.bmj.com on 2/4/19.


2018 ◽  
Vol 103 (2) ◽  
pp. e2.1-e2
Author(s):  
Andy Fox

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.


2019 ◽  
Vol 28 (4) ◽  
pp. 1411-1431 ◽  
Author(s):  
Lauren Bislick ◽  
William D. Hula

Purpose This retrospective analysis examined group differences in error rate across 4 contextual variables (clusters vs. singletons, syllable position, number of syllables, and articulatory phonetic features) in adults with apraxia of speech (AOS) and adults with aphasia only. Group differences in the distribution of error type across contextual variables were also examined. Method Ten individuals with acquired AOS and aphasia and 11 individuals with aphasia participated in this study. In the context of a 2-group experimental design, the influence of 4 contextual variables on error rate and error type distribution was examined via repetition of 29 multisyllabic words. Error rates were analyzed using Bayesian methods, whereas distribution of error type was examined via descriptive statistics. Results There were 4 findings of robust differences between the 2 groups. These differences were found for syllable position, number of syllables, manner of articulation, and voicing. Group differences were less robust for clusters versus singletons and place of articulation. Results of error type distribution show a high proportion of distortion and substitution errors in speakers with AOS and a high proportion of substitution and omission errors in speakers with aphasia. Conclusion Findings add to the continued effort to improve the understanding and assessment of AOS and aphasia. Several contextual variables more consistently influenced breakdown in participants with AOS compared to participants with aphasia and should be considered during the diagnostic process. Supplemental Material https://doi.org/10.23641/asha.9701690


2016 ◽  
Vol 101 (9) ◽  
pp. e2.62-e2 ◽  
Author(s):  
Sattam Alenezi ◽  
Janine Abramson ◽  
Coral Smith ◽  
Helen Sammons ◽  
Sharon Conroy

BackgroundPrescribing errors have the potential to adversely affect the safe pharmacological treatment of patients of all ages. The multi-centre General Medical Council commissioned ‘EQUIP’ study assessed the prevalence and nature of prescribing errors and found a mean rate of errors in 8.9% of medication orders.1 Paediatric data was not however analysed separately. Errors have been estimated to cause harm in paediatric patients three times more often than in adults.2 Clinical pharmacists play a role in identifying prescribing errors and minimising harm but this role has not been explored in detail in children in the UK.ObjectivesTo evaluate the prevalence and nature of prescribing errors and the role of hospital pharmacists in identifying and reducing risk in neonatal and paediatric patients.MethodsData collection sites were identified through the Neonatal and Paediatric Pharmacists Group by an email asking for volunteer centres. Clinical pharmacists working in these hospitals were asked to document prescribing errors in inpatient medication orders identified as part of their routine practice using a data collection form adapted from the EQUIP study1. A variety of hospital settings were aimed for.Data was collected monthly on six separate weekdays in most of the participating hospitals in 2013. Data was entered on to a SPSS database for collation and analysis.Classification of error type and potential severity was done using the EQUIP study categories1. Drugs were categorised according to the British National Formulary for Children3 and patient's ages were grouped according to the International Conference of Harmonisation guidelines.4 ResultsThirteen hospitals (eight specialist children's and five general teaching hospitals) from across the UK agreed to participate. Pharmacists checked 11,941 prescriptions written for 3,330 patients and identified 1,039 errors: an overall rate of 8.7% of medication orders with 20.6% of all patients having a prescribing error.Overdose was found to be the most common error followed by incorrect or missing administration times and underdose. This was in contrast to the EQUIP study where omission errors were most common. Specialist trainees/trust grade fixed term specialty training appointments (FTSTAs) made the majority of errors; however this was in proportion with the number of prescriptions which they wrote. Antibacterial and analgesic drugs were the most common classes associated with errors and the oral route was the most common route involved.70% errors were classified as minor, though 25% were considered significant, 5.4% serious and 0.22% (two errors) potentially lethal. Five patients were stated to have experienced harm.39.6% of errors occurred during the patient's hospital stay followed by 35% errors occurring on admission.ConclusionPrescribing errors occurred at a similar rate as in adult patients 1 but the most common type of errors was different with dosing errors most common in children. Clinical pharmacists' interventions play an important role in identifying and minimising harm from prescribing errors.


2018 ◽  
Vol 103 (2) ◽  
pp. e2.12-e2
Author(s):  
Moninne Howlett

AimsHealth information technology (HIT) is increasingly being promoted as a medication error reduction strategy. Electronic prescribing and smart-pump technology are examples of HIT widely advocated in the hospital setting. In critical care, the risks associated with paediatric infusions have been specifically addressed with calls for the use of standard concentration infusions (SCIs) in conjunction with smart-pump technology. Evidence on the benefits of HIT in the paediatric setting remains limited. This study aims to assess the impact of both electronic prescribing and a smart-pump drug library of SCIs on medication errors in paediatric critical care.MethodsA retrospective, observational study based on an interrupted time series design was conducted in the 23-bed paediatric intensive care unit (PICU) of a tertiary children’s hospital. 3400 randomly selected medication orders were reviewed over 4 epochs: pre-implementation of either technology (Epoch 1); post-implementation of SCIs (Epoch 2); immediate post-implementation of electronic prescribing (Epoch 3); and 1 year post-implementation of both (Epoch 4). Orders prescribed during the study period were included provided they had undergone clinical pharmacy review. Intravenous fluids, epidural/regional blocks, total parental nutrition, chemotherapy and patient/nurse controlled analgesia were excluded. Medication error rates were calculated applying pre-specified definitions and inclusion criteria.1 Novel technology-generated errors were identified and defined using a modified Delphi process. Errors were graded for severity using a combination of two validated grading tools.2,3ResultsOverall medication error rate based on all orders were similar in Epoch 1 and 4 (10.2% vs 9.7%; p=0.66). Altered error distribution was however evident. Incomplete and wrong unit errors were eradicated, but duplicate orders increased. Dosing errors remained the most common. 77% of pre-implementation errors were considered likely to be removed by the new technology. 24% of post-implementation errors were considered to be novel technology-generated errors. Examples included incorrect formulation selection and errors on altered electronic orders. In Epoch 2, the implementation of SCIs prior to electronic prescribing significantly reduced infusion-related prescribing errors (31.4% to 12.6%; p<0.01). An infusion error rate of 7.9% was reported post-implementation of electronically-generated standard infusion orders in Epoch 4.ConclusionThe overall medication error rate in PICU was largely unchanged by the introduction of electronic prescribing. Some errors disappeared but new errors directly attributable to the implemented technologies emerged. In the complex PICU environment, dosing errors remain common. A significant reduction in infusion-related errors was found as a consequence of the introduction of SCIs and smart-pump technology. The introduction of electronically-generated standard infusion orders brought further benefits. The results of this study show that the benefits of HIT in the paediatric setting cannot be assumed and highlight the need for further studies with increasing use of HIT in paediatric settings.ReferencesGhaleb MA, Barber N, Dean Franklin B, et al. What constitutes a prescribing error in paediatrics?BMJ Qual Saf2005;14(5):352–7.Dean BS, Barber ND. A validated, reliable method of scoring the severity of medication errors. Am J Health Syst Pharm1999;56(1):57–62.National Coordinating Council for Medication Error Reporting and Prevention. Taxonomy of medication errors1998. http://www.nccmerp.org/about-medication-errors


Author(s):  
S. O. Ekama ◽  
A. N. David ◽  
A. Z. Musa ◽  
I. I. Olojo ◽  
E. C. Herbertson ◽  
...  

Background: Medication errors are major challenging clinical incidents in health care settings that could jeopardize a patient’s life and well being. These errors could occur at any step of the medication use process from prescribing, prescription verification, dispensing, drug administration to monitoring. This study aims to assess and classify medication errors among doctors and pharmacists. Methods: A prospective observational study from July to September 2018. Randomly selected prescriptions were screened for errors before and after dispensing of drugs. Errors were assessed and classified according to the National Coordination Council for Medication Error Reporting and Prevention (NCCMERP) index to determine the level of harm it posed to the patient. Results: Out of 1529 prescriptions analyzed, 182(11.9%) medication errors were observed; 104(57.1%) and 78 (42.9%) among doctors and pharmacists respectively. Majority of the errors were for female patients, those on first line antiretroviral drug regimen, in the age group 41-50 years and according to the NCCMERP index of the error type D. The most common medication errors among the doctors were omission errors (36.5%) and errors in patient data (21.1%) while unsigned prescriptions (33.3%) and omitting prescribed drugs from dispensed drugs (28.2%) ranked highest among pharmacists’ errors. Doctors and pharmacists (53.3% and 75% respectively) with < 5years HIV care experience had higher error rates. Conclusion: Medication errors associated with cotrimoxazole therapy were most common for both categories of health workers and this has a potential for poor treatment outcome. There is need for continuous training of health workers in HIV management.


10.2196/24418 ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e24418
Author(s):  
Justin Clark ◽  
Catherine McFarlane ◽  
Gina Cleo ◽  
Christiane Ishikawa Ramos ◽  
Skye Marshall

Background Systematic reviews (SRs) are considered the highest level of evidence to answer research questions; however, they are time and resource intensive. Objective When comparing SR tasks done manually, using standard methods, versus those same SR tasks done using automated tools, (1) what is the difference in time to complete the SR task and (2) what is the impact on the error rate of the SR task? Methods A case study compared specific tasks done during the conduct of an SR on prebiotic, probiotic, and synbiotic supplementation in chronic kidney disease. Two participants (manual team) conducted the SR using current methods, comprising a total of 16 tasks. Another two participants (automation team) conducted the tasks where a systematic review automation (SRA) tool was available, comprising of a total of six tasks. The time taken and error rate of the six tasks that were completed by both teams were compared. Results The approximate time for the manual team to produce a draft of the background, methods, and results sections of the SR was 126 hours. For the six tasks in which times were compared, the manual team spent 2493 minutes (42 hours) on the tasks, compared to 708 minutes (12 hours) spent by the automation team. The manual team had a higher error rate in two of the six tasks—regarding Task 5: Run the systematic search, the manual team made eight errors versus three errors made by the automation team; regarding Task 12: Assess the risk of bias, 25 assessments differed from a reference standard for the manual team compared to 20 differences for the automation team. The manual team had a lower error rate in one of the six tasks—regarding Task 6: Deduplicate search results, the manual team removed one unique study and missed zero duplicates versus the automation team who removed two unique studies and missed seven duplicates. Error rates were similar for the two remaining compared tasks—regarding Task 7: Screen the titles and abstracts and Task 9: Screen the full text, zero relevant studies were excluded by both teams. One task could not be compared between groups—Task 8: Find the full text. Conclusions For the majority of SR tasks where an SRA tool was used, the time required to complete that task was reduced for novice researchers while methodological quality was maintained.


2020 ◽  
Vol 11 (02) ◽  
pp. 323-335 ◽  
Author(s):  
Moninne M. Howlett ◽  
Eileen Butler ◽  
Karen M. Lavelle ◽  
Brian J. Cleary ◽  
Cormac V. Breatnach

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.


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