Pediatric Medication Safety in the Emergency Department

Intercepting Medication Errors in Pediatric In-patients Using a Prescription Pre-audit Intelligent Decision System: A Single-center Study

OBJECTIVES

Medication errors can happen at any phase of the medication process at health care settings. The objective of this study is to identify the characteristics of severe prescribing errors at a pediatric hospital in the inpatient setting and to provide recommendations to improve medication safety and rational drug use.

METHODS

This descriptive retrospective study was conducted at a tertiary pediatric hospital using data collected from Jan. 1st, 2019 to Dec. 31st, 2020. During this period, the Prescription Pre-audit Intelligent Decision System was implemented. Medication orders with potential severe errors would trigger a Level 7 alert and would be intercepted before it reached the pharmacy. Trained pharmacists maintained the system and facilitated decision making when necessary. For each order intercepted by the system the following patient details were recorded and analyzed: patient age, patient's department, drug classification, dosage forms, route of administration, and the type of error.

RESULTS

A total of 2176 Level 7 medication orders were intercepted. The most common errors were associated with drug dosage, administration route, and dose frequency, accounting for 35.2%, 32.8% and 13.2%, respectively. Of all the intercepted oerrors. 53.6% occurred in infants aged < 1 year. Administration routes involved were mainly intravenous, oral and external use drugs. Most alerts came from the neonatology department and constituted 40.5% of the total alerts, followed by the nephrology department 15.9% and pediatric intensive care unit (PICU) 11.3%. As to dosage forms, injections accounted for 50.4% of alerts, with 21.3% attributable to topical solutions, 9.1% to tablets, and 5.7% to inhalation. Anti-infective agents were the most common therapeutic drugs prescribed with errors.

CONCLUSIONS

The Prescription Pre-audit Intelligent Decision System, with the supervision of trained pharmacists can validate prescriptions, increase prescription accuracy, and improve drug safety for hospitalized children. It is a medical service model worthy of consideration.

Antibiotic Prescribing Errors in Patients Discharged From the Pediatric Emergency Department

OBJECTIVES

The pediatric emergency department (PED) is an especially high-risk setting for medication errors. Several factors contribute to this risk including the need to provide care to complex patients who are unknown to staff, the frequent use of verbal orders, and the necessity of weight-based dosing. This investigation sought to assess one potentially error-prone event, antibiotic prescriptions written for patients being discharged from the PED, and to characterize the occurrence of medication errors to identify opportunities for improvement.

METHODS

This was a retrospective study of pediatric patients seen at a large academic medical center PED. All prescriptions written for an antibiotic for patients 18 years or younger that were discharged from the PED from 2015 to 2018 were evaluated for errors in directions, indication, dose, quantity, and refills. Because antibiotic dosing can vary based on indications, only disease states with guideline-specific dosing recommendations were evaluated for dosing errors.

RESULTS

A total of 11,815 antibiotic prescriptions were analyzed for patients discharged from the PED, and 1986 (16.8%) errors were identified. Of all the prescriptions reviewed, 517 (4.4%) contained an incomplete prescription error. Discharge prescriptions written by off-service physicians were more likely to contain incomplete prescription errors (5.1%) when compared with emergency medicine physicians (3.9%; P = 0.022). A dosing error rate of 18.5% (1469 prescriptions) was identified for the 7930 disease state-specific prescriptions reviewed. Underdosing errors were significantly more common (51.6%) than overdosing errors (29.3%; P < 0.0001). Among the different agents, there was noted to be a significant difference in the antibiotics most commonly involved in dosing errors (P < 0.0001). Additionally, there was also a significant difference in the incidence of dosing errors between different disease states (P < 0.0001). No significant difference was found in the incidence of dosing errors across physician specialties (P = 0.872).

CONCLUSIONS

We identified 1986 (16.8%) total errors in this analysis of antibiotic prescriptions written on discharge from the PED. Among the disease states evaluated, dosing errors were identified in 18.5% of prescriptions with the most common error being underdosing. Literature evaluating pediatric prescription errors, and specifically antibiotic discharge prescriptions, is quite limited. Further investigation is necessary in this area, and strategies should be developed leveraging technology, enhancing education, and using pharmacy personnel to help reduce antibiotic prescribing errors for patients discharged from the PED.

Comparison of Accuracy and Speed in Computer-Assisted Versus Conventional Methods for Pediatric Drug Dose Calculation: A Scenario-Based Randomized Controlled Trial

Pediatric emergency care is prone to medication errors in many aspects including prescriptions, administrations, and monitoring. This study was designed to assess the effects of computer-assisted calculation on reducing error rates and time to prescription of specific emergency drugs. We conducted a randomized crossover experimental study involving emergency medicine residents and paramedics in the Department of Emergency Medicine at Ramathibodi Hospital. Participants calculated and prescribed medications using both the conventional method and a computer-assisted method. Medication names, dosages, routes of administration, and time to prescription were collected and analyzed using logistic and quantile regression analysis. Of 562 prescriptions, we found significant differences between computer-assisted calculation and the conventional method in the calculation accuracy of overall medications, pediatric advanced life support (PALS) drugs, and sedative drugs (91.17% vs 67.26%, 86.54% vs 46.15%, and 89.29% vs 57.86%, respectively, P < .001). Moreover, there were significant differences in calculation time for overall medications, PALS drugs and sedative drugs (25 vs 47 seconds, P < .001), and computer-assisted calculation significantly decreased the gap in medication errors between doctors and paramedics (P < .001). We conclude that computer-assisted prescription calculation provides benefits over the conventional method in accuracy of all medication dosages and in time required for calculation, while enhancing the drug prescription ability of paramedics.

What causes prescribing errors in children? Scoping review

OBJECTIVES

(1) Systematically assemble, analyse and synthesise published evidence on causes of prescribing error in children. (2) Present results to a multidisciplinary group of paediatric prescribing stakeholders to validate findings and establish how causative factors lead to errors in practice.

DESIGN

Scoping review using Arksey and O'Malley's framework, including stakeholder consultation; qualitative evidence synthesis.

METHODS

We followed the six scoping review stages. (1) Research question-the research question was 'What is known about causes of prescribing error in children?' (2) Search strategy-we searched MEDLINE, EMBASE, CINAHL (from inception to February 2018), grey literature and reference lists of included studies. (3) Article selection-all published evidence contributing information on the causes of prescribing error in children was eligible for inclusion. We included review articles as secondary evidence to broaden understanding. (4) Charting data-results were collated in a custom data charting form. (5) Reporting results-we summarised article characteristics, extracted causal evidence and thematically synthesised findings. (6) Stakeholder consultation-results were presented to a multidisciplinary focus group of six prescribing stakeholders to establish validity, relevance and mechanisms by which causes lead to errors in practice.

RESULTS

68 articles were included. We identified six main causes of prescribing errors: children's fundamental differences led to individualised dosing and calculations; off-licence prescribing; medication formulations; communication with children; and experience working with children. Primary evidence clarifying causes was lacking.

CONCLUSIONS

Specific factors complicate prescribing for children and increase risk of errors. Primary research is needed to confirm and elaborate these causes of error. In the meantime, this review uses existing evidence to make provisional paediatric-specific recommendations for policy, practice and education.

[Impact of a strategy to improve the quality of care and risk management in a paediatric emergency department]

INTRODUCTION

Emergency departments are a high risk area for the occurrence of adverse events. The aim of this study is to analyse the impact of a strategy to improve the quality assurance and risk management in the notification of incidents in our Unit, and describe the improvement actions developed from the reported incidents.

MATERIAL AND METHODS

A retrospective observational study was developed during one year, divided into two periods: P1 (Start: training session and implementation of the risk management process), and P2 (Start: feed-back session of incidents reported in P1 and improvement actions developed). In each period, the number of reported incidents in relation to the number of emergencies attended (‰) and the descriptive data of each incident were recorded. The improvement actions developed from the incidents reported in P1 were described.

RESULTS

The number of notifications from P1 (4.1‰; 95%CI 3.2-5.0‰) increased in P2 (10.9‰; 95%CI 9.8-10.2‰, P<.001). The most frequent incidents in P1 were medication (33.3%), and identification errors (25.9%): both were significantly reduced in P2 (16.9%, P=.001 and 9.3%, P<.001, respectively). In P2, prescription errors of the P1 were reduced (35.9% vs 62.9%, P=.02). The factors of "Knowledge and training" (23.5%) were the most frequent in P1, decreasing in P2 (7.4%, P<.001).

CONCLUSION

It is considered that the implementation of a risk management process, and the promotion of a safety culture, through training and feed-back sessions to all professionals, contributed to increase the volume of notifications in our Unit. The voluntary and anonymous reporting of incidents is useful to identify risks, and plan corrective measures, contributing to improve quality assurance and patient safety.