Electronic prescribing does not prevent most harmful paediatric prescribing errors, study finds

ObjectiveThe aim of this research was to ascertain the effectiveness of current electronic prescribing (EP) systems to prevent a standardised set of paediatric prescribing errors likely to cause harm if they reach the patient.DesignSemistructured survey.SettingUK hospitals using EP in the paediatric setting.Outcome measuresNumber and type of erroneous orders able to be prescribed, and the level of clinical decision support (CDS) provided during the prescribing process.Results90.7% of the erroneous orders were able to be prescribed across the seven different EP systems tested. Levels of CDS varied between systems and between sites using the same system.ConclusionsEP systems vary in their ability to prevent harmful prescribing errors in the hospital paediatric setting. Differences also occur between sites using the same system, highlighting the importance of how a system is set up and optimised.

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

Archives of Disease in Childhood ◽

10.1136/archdischild-2017-314584.3 ◽

2018 ◽

Vol 103 (2) ◽

pp. e1.23-e1

Author(s):

Aragon Octavio ◽

Fayyaz Goher ◽

Gill Andrea ◽

Morecroft Charles

Keyword(s):

Medication Errors ◽

Error Rate ◽

Error Rates ◽

Electronic Prescribing ◽

Prescribing Errors ◽

Error Type ◽

Common Error ◽

Period 2 ◽

The Difference ◽

Paediatric Prescribing

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

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

Archives of Disease in Childhood ◽

10.1136/archdischild-2017-314585.1 ◽

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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Impact of Electronic Prescription on Prescribing Errors

Journal of Pharmaceutical Research International ◽

10.9734/jpri/2021/v33i32a31733 ◽

2021 ◽

pp. 212-220

Author(s):

Ameen M. Almohammadi ◽

Huda M. Al-Dhahri ◽

Shroug H. Al-Harbi

Keyword(s):

Study Design ◽

Intervention Study ◽

Dosage Forms ◽

Electronic Prescribing ◽

Prescribing Errors ◽

Post Intervention ◽

Electronic Prescription ◽

Prescription Errors ◽

Trade Names ◽

The Impact

Aims: There are series of medical errors that can be prevented by taking precautions. Therefore, the study evaluates the impact of the electronic prescribing system on prescription errors. Study Design: A pre-post study design was conducted. Place and Duration of Study: The study was conducted at outpatient pharmacy services of a teaching hospital in Jeddah city. Methodology: Prescriptions were evaluated for the presence of the essential prescription elements such as patient information, drug name, dose, frequency, strength, and other prescription completeness parameters. Results: In the pre-intervention study, 1182 handwritten prescriptions were evaluated, and 6627 errors were detected from these prescriptions. The length of the pre-and post-intervention period was two weeks each. The most prevalent prescribing errors were that of medications written without defined dosage forms were recorded 1653 (55.90%) time followed by prescriptions written by trade names 1493 (22.5%), without route of administration 1266 (19.1%), and without specified duration 1009 (15.2%). However, 1512 prescriptions were evaluated in the post-intervention study, among which 339 errors were detected. The errors included prescriptions written without diagnosis (5.09%), or without doctor’s name or stamp (1.52%), written by trade names (4.49%), without defined dosage forms (4.29%), and without specified duration (2.84%). Conclusion: The study concluded that E-prescribing eliminated prescription errors that resulted from handwritten prescriptions.

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P047 Evaluating the impact of pre-prepared neonatal intubation premedication kits on a level 3 neonatal unit (Project NIK)

Archives of Disease in Childhood ◽

10.1136/archdischild-2019-nppc.56 ◽

2019 ◽

Vol 104 (7) ◽

pp. e2.52-e2

Author(s):

Suzannah Hibberd ◽

Alok Sharma ◽

Marhamat Chavoshzadeh

Keyword(s):

Nursing Staff ◽

Response Rate ◽

Electronic Prescribing ◽

Drug Preparation ◽

Prescribing Errors ◽

Before And After ◽

Level 3 ◽

Perceived Impact ◽

Set Up ◽

The Impact

BackgroundIn January 2018, neonatal intubation premedication kits containing atropine, suxamethonium and fentanyl were introduced alongside the implementation of dose- banding for these medicines according to patient’s weight and regardless of the patient’s gestation. A prescribing bundle on the electronic prescribing system was also created to automatically populate the doses based on the patient’s weight. Seven kits are produced each week by the Pharmacy Technical Services Unit.AimTo assess the staff perceived impact of pre-prepared intubation drug kits with associated dose-banding of the medication.MethodsThree months after the kits were implemented, a survey was sent to all nursing and medical staff to establish their thoughts on the intubation process before and after the introduction of pre-made intubation drug kits.Results78 staff responded, 45.5% were doctors and 54.5% were nursing staff. The response rate was 53.8%. 78% of respondents reported being part of a difficult intubation over the last 5 years. The main problems identified, prior to the implementation of the neonatal intubation drug kits, included the intubation process (51.5%), preparation and communication prior to intubation, (13.6%), time drawing up intubation drugs (10.6%) and the patient having a difficult airway (9%). 87.2% found the premade intubation kits very useful, none of the respondents thought the kits were not useful. Four themes were found irrespective of whether the respondent was a doctor or member of nursing staff. The themes were: they made the process easier; quicker; reduced risk of error and helped provide better patient care. When asked if any complications had arisen, 4% reported that they had run out of kits and 2.7% said there was confusion when signing the kits out of the controlled drug (CD) register.Three weeks out of 25 saw all the kits being used, average usage is 4 intubation kits per week. 97.4% reported the doses used were effective in sedating and paralysing the baby prior to intubation, 2.6% commented that they were somewhat effective but that in one occasion the paralysis had not been optimal, however they questioned whether the cannula had been functioning properly.ConclusionThe implementation of ready to use intubation drug kits has made the process of preparing for an intubation easier and quicker for all involved in the process. Having the dose banding set up on the electronic prescribing system has reduced the chance of prescribing errors and the pre- filled kits have reduced the chances of calculation errors during drug preparation. When the kits run out there are instructions in the guideline detailing how to make the required concentrations. As a result of this study standardised teaching videos were introduced from the beginning of July 18. Further simulations have been completed to ensure that all staff follow a standardised process. Next steps are to ensure that the documentation in the CD register includes all necessary information without any need for amendments. To overcome this, a stamp is being designed to use in the book each time a patient requires a kit, thereby providing a prompt for the nurses.

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P007 Improving paediatric chemotherapy prescribing through use of an electronic prescribing system

Archives of Disease in Childhood ◽

10.1136/archdischild-2019-nppc.17 ◽

2019 ◽

Vol 104 (7) ◽

pp. e2.9-e2

Author(s):

Charlotte Summerfield ◽

Susan Kafka ◽

Michelle Lewis ◽

Guy Makin ◽

Joseph Williams ◽

...

Keyword(s):

Cancer Therapy ◽

Malignant Disease ◽

Electronic Prescribing ◽

List Type ◽

Prescribing Errors ◽

Exact Test ◽

Anti Cancer ◽

Treatment Data ◽

Cost Implications ◽

Electronic Prescriptions

AimPaediatric prescriptions are almost 50% more likely to contain an error than adult orders. The risk of prescription error is further increased when prescribing for malignant disease.1 In 2017 the Trust introduced ChemoCare, an electronic prescribing system for paediatric chemotherapy. The primary aim of this study was to investigate whether implementing ChemoCare has affected the incidence and type of errors made in paediatric chemotherapy prescriptions, compared with written prescriptions. A secondary aim was to explore possible reasons why these prescribing errors may occur. Since 2014 it has been mandatory for all NHS England specialist trusts to send monthly submissions to the Systemic Anti-Cancer Therapy (SACT) Database, regarding the treatment of malignant disease in secondary care.2 Therefore, the study also analysed Trust compliance with communicating treatment data to SACT.MethodsData collection took place over a four-week period in Spring 2018. Prescriptions were reviewed by pharmacists and categorised as written or electronic. Prescriptions were then checked for 7 different error types; calculation error, drug prescribed on wrong day, incorrect drug prescribed for cycle, incorrect dose of concomitant medications, incorrect surface area used, not adjusted dose for previous age or weight related toxicities, no drug prescribed. The Fisher’s Exact test was employed to detect significance between chemotherapy prescription type and error incidence. A written questionnaire was designed to obtain the views of consultants, pharmacists and specialist trainees, and explore possible reasons why prescription errors occur. ChemoCare treatment data was retrospectively reviewed in order to determine how many prescribed cycles had been marked as ‘completed’.Results143 prescriptions were analysed. 34.4%(n=21) of written prescriptions contained errors, compared with 11.4% (n=5) of electronic orders. Two of the error types measured‘wrong calculation’ and ‘wrong drug prescribed for cycle’occurred significantly more frequently in written than electronic prescriptions.The Fisher’s Exact test produced p values of 0.017 and 0.008 respectively. Of the 409 treatment cycles prescribed and administered on the electronic system, 56.5% (n=231) had not been marked as ‘completed’, so would not be returned to SACT as administered chemotherapy. Failure to communicate accurate chemotherapy data to SACT not only limits research opportunities to progress safety aspects of delivering chemotherapy, but also has significant cost implications for the Trust, as chemotherapy treatment costs are not recovered.ConclusionThis study supports the use of an electronic prescribing system for ordering paediatric chemotherapy, given the significant reduction in errors compared with written prescriptions. The introduction of a chemotherapy-specific safe prescribing poster is suggested in order to improve compliance with ChemoCare. Further studies analysing national compliance with data return to SACT, are required to identify cost implications for the NHS and subsequent areas for quality improvement.ReferencesAvery AJ, Ghaleb M, Barber N, et al. Investigating the prevalence and causes of prescribing errors in general practice: The practice study. Pharmacoepidemiol Drug Saf 2012;21:4.NCRAS. Systemic Anti-Cancer Therapy Dataset [Internet]. [cited 2018 June 26]. Available from: http://www.ncin.org.uk/collecting_and_using_data/data_collection/chemotherapy

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P37 A model for reducing paediatric prescribing errors in secondary care

Archives of Disease in Childhood ◽

10.1136/archdischild-2020-nppg.46 ◽

2020 ◽

Vol 105 (9) ◽

pp. e26.1-e26

Author(s):

Kate Morgan

Keyword(s):

Medication Errors ◽

Error Rate ◽

Neonatal Intensive Care ◽

Inappropriate Medication ◽

List Type ◽

Prescribing Errors ◽

Prescribing Error ◽

Senior Nurse ◽

Ward Rounds ◽

Paediatric Prescribing

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.

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

Applied Clinical Informatics ◽

10.1055/s-0040-1709508 ◽

2020 ◽

Vol 11 (02) ◽

pp. 323-335 ◽

Cited By ~ 3

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.

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