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 Implementation and outcome of an electronic tool for detection of paracetamol overdose in a tertiary care hospital

2020 ◽  
Author(s):  
Francisco Cabrera-Diaz ◽  
Claudia Zaugg ◽  
Silke Lim ◽  
Kim Blum ◽  
Ali Reza Salili
Keyword(s):  
Information System ◽  
Medication Error ◽  
Clinical Information System ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Clinical Information ◽  
Paracetamol Overdose ◽  
Care Hospital ◽  
Electronic Tool ◽  
Process Failures

Abstract Background Paracetamol is a widely used analgesic and antipyretic drug in hospitals. The development and implementation of an electronic tool with algorithm-based alerts (e-agent) in a clinical information system could reduce the risk of overdose. Objective In this study, the performance of such an e-agent developed to detect paracetamol overdosing was analyzed. Setting Swiss tertiary care hospital. Method All patients ≥ 18 years old who had documented paracetamol administration in the used clinical information system during 2017 were retrospectively screened for an absolute and relative overdosing of paracetamol (> 4 g and > 60 mg/kg/24 h, respectively). This was compared with the patients for which the e-agent had, during the same period, prospectively made an alert for absolute or relative overdosing or for a dosing interval < 4 h (potentially leading to an absolute overdose). Main outcome measure E-agent performance defined as detection rate. Results of the 13,196 adult patients who received at least one dose of paracetamol, 2292 were exposed at least once to > 4 g/day (17.4%), 39 of these (0.3% of total) were given > 5 g paracetamol. None received more than 6 g. The e-agent detected 87.2% of cases with doses > 5 g. In most cases (87.9%), the cause of the absolute overdose was a switch from intravenous to oral paracetamol, resulting in an absolute overdose the day of the change. The maximal daily dose of 60 mg/kg was exceeded in 30.1% of patients weighing < 50 kg, as well as in 42.3% of patients weighing < 60 kg. The e-agent detected 73.4% and 75.5% of those cases. Multiple absolute overdoses were found in 204 patients. The e-agent detected 72.7% of those. 90 multiple overdoses occurred during the same hospital stay and 11 on consecutive days. Conclusion Paracetamol overdose is a common medication error in hospitalized patients, which may occur due to process failures such as wrong timing when changing administration route or when factors like comedication and low body weight are ignored. The e-agent detects cases of paracetamol overdose, and therefore, can help prevent this kind of medication error in the clinical setting.

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.

P24 Developing a paediatric electronic prescribing system

2018 ◽  
Vol 103 (2) ◽  
pp. e1.29-e1
Author(s):  
Asif Yusuf ◽  
Choudhury Camrul
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Secondary Care ◽  
Clinical Decision ◽  
Support Staff ◽  
Electronic Prescribing ◽  
List Type ◽  
Care Hospital ◽  
Paediatric Drug ◽  
Clinical Support

AimTo develop an electronic prescribing system (EPS), in a tertiary care paediatric hospital.MethodOne of the many benefits of electronic prescribing (EP) in secondary care, is the reduction in prescribing error rates.1 However, implementing EP in paediatrics, presents many challenges such as the increased complexity of medication dosing2 and varying doses of drugs depending on indication.2 An EPS was acquired from a local adult secondary care hospital and developed to include a specialist paediatric drug library with clinical decision support. The pharmacy department used a dispensing patient medication record system that was incompatible with the EPS, so the latter had to work side-by- side with the former, as the drug chart. A smaller training team was deployed with external trainers, from the hospital where the system was acquired from and they were enlisted for the pilot.ResultsThe pilot was launched in April 2017, on the hepatology ward, consisting of 14 beds. All patients that were treated under the hepatology medical and surgical teams were placed on the e-prescribing system and this accounted for 95 patients, from the launch over a period of 3 months. Although the benefits of an EPS became a reality, which included a reduction in medication and administration errors, many drawbacks still existed that hindered a more complete EPS. Certain drugs were found to be missing from the drug library and drug monographs lacked the appropriate clinical decision support for prescribers and administrators alike. This was observed by the sharp rise in incident reporting from 20 reports, in the 3 months prior to the launch, to 55 reports, in the 3 months post-launch. Pharmacy processes, that proved effortless on drug charts and discharge prescriptions, became complex for pharmacists and technicians, as the EPS lacked the necessary features including insufficient message functionality to document patient’s own medicines and supply from pharmacy, discharge prescription alerting and modification of prescriptions once printed. The absence of sufficient and relevant clinical support staff became apparent soon after external trainers returned to their respective bases; with only one support member remaining that had held a clinical position previously. Difficulties quickly became apparent when attempting to explain specific clinical EP functions to non-clinical support staff.ConclusionIn preparation for rollout across the trust, many areas could be improved upon to ensure substantial progress could be made, from the pilot. Developing a more robust system to build and review drug monographs to include both medical and nursing input, from their respective clinical specialities and ensuring that all drugs whether supplied with or without pharmacy involvement are included in the paediatric drug library. Observing the work of pharmacists and other healthcare professionals, to ensure their day-today tasks, on drug charts or discharge prescriptions, are replicated successfully on the EPS. Increased pharmacy involvement in training and support, would benefit the EPS greatly, from a clinical perspective.ReferencesFranklin G, O’Grady K, Donyai P, Jacklin A, Barber N. The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: A before-and-after study. QualSaf Health Care2007;16:279–84.Johnson KB, Lehmann CU. Council on clinical information technology. Technical report: Electronic prescribing in paediatrics: Toward safer and more effective medication management. Paediatrics2013;131(4):e1350–e1356.

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

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 67 Reducing Delays to Operative Management of Anti-Coagulated Patients With Hip Fractures

2020 ◽  
Vol 49 (Supplement_1) ◽  
pp. i18-i20
Author(s):  
J Ensanullah ◽  
B Shah ◽  
M Fertleman
Keyword(s):  
Hip Fracture ◽  
Hip Fractures ◽  
Heart Valves ◽  
Guideline Implementation ◽  
Operative Management ◽  
National Guidelines ◽  
Improvement Project ◽  
Before And After ◽  
Surgery Timing ◽  
The Uk

Abstract Introduction In the UK, the gold-standard treatment of a hip fracture is surgical fixation within 36 hours. Reduced delay to surgery has been shown to minimise the risk of complications. Locally, frequent delays to surgery were observed in patients taking long-term anticoagulation. There are no national guidelines regarding anticoagulation reversal and surgery timing in patients with hip fractures, and doctors are often unfamiliar with increasingly prevalent Direct Oral Anti-coagulants (DOACs). This quality improvement project aimed to reduce delays to surgery in anti-coagulated patients with hip fractures. Methods A guideline was formulated following literature review and consultation with a Consultant Ortho-geriatrician, Orthopaedic Surgeon and Haematologist. Retrospective casenote audit was conducted including 3-month period before and after implementation. The new guideline was disseminated in poster form. Due to the observation that delays in receiving INR results resulted in reversal delay, patient’s on warfarin were recommended to receive 5 mg IV Vitamin K prior to receiving INR results. The INR was rechecked after 6 hours, and if less than 1.6, surgery could proceed. Those on DOACs could undergo surgery 24 hours after the last dose providing eGFR &gt;30, and after 48 hours if eGFR &lt;30. Exclusions were those anti-coagulated for metallic heart valves or recent venous thromboembolism. Results In the 3 months prior to guideline implementation, 71 patients had a hip fracture; 15 were anti-coagulated. Of these, 8 patients were delayed due to their anticoagulation. Repeat audit after implementation, included 46 patients with a hip fracture over the 3-month period; 7 were anti-coagulated. None were delayed due to anticoagulation (p &lt; 0.05). Conclusions This improvement project describes formulation of a simple protocol with evidence from the literature and local expert opinion in order to reduce unnecessary delays in anti-coagulated patients with hip fractures.

scholarly journals Learning from Lean: a quality improvement project using a Lean-based improvement approach to improve discharge for patients with frailty in an acute care hospital

2021 ◽  
Vol 10 (4) ◽  
pp. e001393
Author(s):  
Thomas James Rollinson ◽  
Joy Furnival ◽  
Sarah Goldberg ◽  
Aklak Choudhury
Keyword(s):  
Quality Improvement ◽  
Acute Care Hospital ◽  
Quality Improvement Project ◽  
Value Stream Mapping ◽  
Care Hospital ◽  
Improvement Project ◽  
National Initiative ◽  
Improved Performance ◽  
The Uk ◽  
The Impact

A Lean-based improvement approach was used to complete a quality improvement project (QIP) focused on improving speed and quality of discharge of frail patients on two wards at a large teaching hospital in the UK. This was part of a national initiative to embed continuous improvement within the trust. The aim of the QIP was to improve the proportion of prenoon discharges to 33% of total patients discharged from the ward each day. An ‘improvement practice process’ followed, which included seven discrete workshops that took the QIP through four distinct phases—understand, design, deliver and sustain. Several improvement methods and tools were used, including value stream mapping and plan–do–study–act (PDSA) cycles. Ten PDSA cycles were implemented across the clinical areas, including improved planning and data collection of discharge, improved communication between nursing and medical staff, and earlier referrals to community hospitals for discharge. Improved performance was identified through the outcome metric prenoon discharges on both wards, with the average increasing from 8% to 24% on ward X and from 9% to 19% on ward Y, with no other significant change seen in other measures. Pettigrew et al’s context–content–process change model was used to structure the learning from the QIP, which included the impact of varying ward contexts, the format of conducting improvement with staff, the importance of organisational support, the need for qualitative measures, agreeing to an apposite aim and the power of involving service users. The original aim of 33% prenoon discharges was not achieved, yet there was clear learning from completing the QIP which could contribute to ongoing improvement work. This identified that the Lean-based improvement approach used was effective to some degree for improving discharge processes. Further focus is required on collecting qualitative data to identify the impact on staff, especially related to behaviour and culture change.

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.

UK Fiscal Squeezes over a Century

2017 ◽  
Author(s):  
Christopher Hood ◽  
Rozana Himaz
Keyword(s):  
Data Sources ◽  
Fiscal Consolidation ◽  
Financial Outcomes ◽  
Financial Conditions ◽  
Deficit Reduction ◽  
Before And After ◽  
The Uk ◽  
Changes Over Time ◽  
Spending Cuts ◽  
Over Time

This chapter draws on historical statistics reporting financial outcomes for spending, taxation, debt, and deficit for the UK over a century to (a) identify quantitatively and compare the main fiscal squeeze episodes (i.e. major revenue increases, spending cuts, or both) in terms of type (soft squeezes and hard squeezes, spending squeezes, and revenue squeezes), depth, and length; (b) compare these periods of austerity against measures of fiscal consolidation in terms of deficit reduction; and (c) identify economic and financial conditions before and after the various squeezes. It explores the extent to which the identification of squeeze episodes and their classification is sensitive to which thresholds are set and what data sources are used. The chapter identifies major changes over time that emerge from this analysis over the changing depth and types of squeeze.

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