Standardising the Classification of Harm Associated with Medication Errors: The Harm Associated with Medication Error Classification (HAMEC)

Clinical and economic impact of medication administration errors among neonates in neonatal intensive care units

Despite efforts in improving medication safety, medication administration errors are still common, resulting in significant clinical and economic impact. Studies conducted using a valid and reliable tool to assess clinical impact are lacking, and to the best of our knowledge, studies evaluating the economic impact of medication administration errors among neonates are not yet available. Therefore, this study aimed to determine the potential clinical and economic impact of medication administration errors in neonatal intensive care units and identify the factors associated with these errors. A national level, multi centre, prospective direct observational study was conducted in the neonatal intensive care units of five Malaysian public hospitals. The nurses preparing and administering the medications were directly observed. After the data were collected, two clinical pharmacists conducted independent assessments to identify errors. An expert panel of healthcare professionals assessed each medication administration error for its potential clinical and economic outcome. A validated visual analogue scale was used to ascertain the potential clinical outcome. The mean severity index for each error was subsequently calculated. The potential economic impact of each error was determined by averaging each expert's input. Multinomial logistic regression and multiple linear regression were used to identify factors associated with the severity and cost of the errors, respectively. A total of 1,018 out of 1,288 (79.0%) errors were found to be potentially moderate in severity, while only 30 (2.3%) were found to be potentially severe. The potential economic impact was estimated at USD 27,452.10. Factors significantly associated with severe medication administration errors were the medications administered intravenously, the presence of high-alert medications, unavailability of a protocol, and younger neonates. Moreover, factors significantly associated with moderately severe errors were intravenous medication administration, younger neonates, and an increased number of medications administered. In the multiple linear regression analysis, the independent variables found to be significantly associated with cost were the intravenous route of administration and the use of high-alert medications. In conclusion, medication administration errors were judged to be mainly moderate in severity costing USD 14.04 (2.22-22.53) per error. This study revealed important insights and highlights the need to implement effective error reducing strategies to improve patient safety among neonates in the neonatal intensive care unit.

Risk Factors Associated with Medication Administration Errors in Children: A Prospective Direct Observational Study of Paediatric Inpatients

INTRODUCTION

Limited evidence exists regarding medication administration errors (MAEs) on general paediatric wards or associated risk factors exists.

OBJECTIVE

The aim of this study was to identify nurse, medication, and work-environment factors associated with MAEs among paediatric inpatients.

METHODS

This was a prospective, direct observational study of 298 nurses in a paediatric referral hospital in Sydney, Australia. Trained observers recorded details of 5137 doses prepared and administered to 1530 children between 07:00 h and 22:00 h on weekdays and weekends. Observation data were compared with medication charts to identify errors. Clinical errors, potential severity and actual harm were assessed. Nurse characteristics (e.g. age, sex, experience), medication type (route, high-risk medications, use of solvent/diluent), and work variables (e.g. time of administration, weekday/weekend, use of an electronic medication management system [eMM], presence of a parent/carer) were collected. Multivariable models assessed MAE risk factors for any error, errors by route, potentially serious errors, and errors involving high-risk medication or causing actual harm.

RESULTS

Errors occurred in 37.0% (n = 1899; 95% confidence interval [CI] 35.7-38.3) of administrations, 25.8% (n = 489; 95% CI 23.8-27.9) of which were rated as potentially serious. Intravenous infusions and injections had high error rates (64.7% [n = 514], 95% CI 61.3-68.0; and 77.4% [n = 188], 95% CI 71.7-82.2, respectively). For intravenous injections, 59.7% (95% CI 53.4-65.6) had potentially serious errors. No nurse characteristics were associated with MAEs. Intravenous route, early morning and weekend administrations, patient age ≥ 11 years, oral medications requiring solvents/diluents and eMM use were all significant risk factors. MAEs causing actual harm were 45% lower using an eMM compared with paper charts.

CONCLUSION

Medication error prevention strategies should target intravenous administrations and not neglect older children in hospital. Attention to nurses' work environments, including improved design and integration of medication technologies, is warranted.

Estimated Costs of Drug-Related Problems Prevented by Pharmacist Prescription Reviews Among Hospitalized Internal Medicine Patients

BACKGROUND AND OBJECTIVES

Data are lacking on the estimated costs of pharmacist prescription reviews (PPRs) for hospitalized internal medicine patients. This study investigates the estimated costs of drug-related problems (DRPs) prevented by PPRs among hospitalized internal medicine patients.

METHODS

We reviewed all medication orders for patients at an academic teaching hospital in China for 2 years. DRPs were categorized using the Pharmaceutical Care Network Europe classification. The severity of the potential harm of DRPs was assessed by the Harm Associated with Medication Error Classification (HAMEC) tool. The estimated cost of PPRs was calculated.

RESULTS

A total of 162426 medication orders for 4314 patients were reviewed, and 1338 DRPs were identified by pharmacists who spent 2230 hours performing PPRs. Among the 1080 DRPs that were prospectively intervened upon, 703 were resolved. The HAMEC tool showed that 47.1% of DRPs were assessed as level 2, 30.4% as level 3, 20.6% as level 1, and 0.6% carried a life-threatening risk. Pharmacist interventions contributed to the prevention of DRP errors and a reduction of $339 139.44. This resulted in a mean cost saving of $482.42 per patient at an input cost of $21 495.06 over the 2 years. The benefit-cost ratio was 15.8.

CONCLUSION

PPRs are beneficial for detecting potential DRPs and creating potential cost savings among hospitalized internal medicine patients.

Parents' understanding of medication at discharge and potential harm in children with medical complexity

OBJECTIVE

Children with medical complexity (CMC) are among the most vulnerable patient groups. This study aimed to evaluate their prevalence and risk factors for medication misunderstanding and potential harm (PH) at discharge.

DESIGN AND SETTING

Cross-sectional study at a tertiary care centre.

STUDY POPULATION

CMC admitted at Medical University of Vienna between May 2018 and January 2019.

INTERVENTION

CMC and caregivers underwent a structured interview at discharge; medication understanding and PH for adverse events were assessed by a hybrid approach.

MAIN OUTCOME MEASURES

Medication misunderstanding rate; PH.

RESULTS

For 106 included children (median age 9.6 years), a median number of 5.0 (IQR 3.0-8.0) different medications were prescribed. 83 CMC (78.3%) demonstrated at least one misunderstanding, in 33 CMC (31.1%), potential harm was detected, 5 of them severe. Misunderstandings were associated with more medications (r=0.24, p=0.013), new prescriptions (r=0.23, p=0.019), quality of medication-related communication (r=-0.21, p=0.032), low level of education (p=0.013), low language skills (p=0.002) and migratory background (p=0.001). Relative risk of PH was 2.27 times increased (95% CI 1.23 to 4.22) with new medications, 2.14 times increased (95% CI 1.10 to 4.17) with migratory background.

CONCLUSION

Despite continuous care at a tertiary care centre and high level of subjective satisfaction, high prevalence of medication misunderstanding with relevant risk for PH was discovered in CMC and their caregivers. This demonstrates the need of interventions to improve patient safety, with stratification of medication-related communication for high-risk groups and a restructured discharge process focusing on detection of misunderstandings ('unknown unknowns').

Medication errors by caregivers in the homes of children discharged from a pediatric department in Ghana

Background

Medication errors (MEs) by caregivers at home are a cause of morbidity and mortality, shortly after discharge from the hospital.

Objectives

The objective of this study was to determine the rate and types of MEs at the homes of children discharged from a hospital in Ghana and to explore the factors associated with these errors.

Design

This was a cross-sectional study of infants and children discharged from the hospital to review medication administration practices.

Methods

Caregivers of children discharged from the hospital after at least 24 hours of admission were interviewed at their homes about medication administration practices. The study assessed potential harm associated with MEs made by caregivers using the Harm Associated with Medication Error Classification tool. The Least Absolute Shrinkage and Selection Operator regression were used to identify the variables associated with MEs.

Results

A total of 95 children (mean age: 28.6 months, 52.6% female) and their caregivers were included. Overall, 65 (68.4%) children experienced one or more MEs. Out of a total of 232 medications reviewed, 102 (44.0%) (95% CI: 37.6-50.4) were associated with a ME. The top two errors, wrong time errors and errors in the frequency of dosing were, 45.1% and 21.6%, respectively. Understanding the information on the disease condition being treated and the medicines dispensed was associated with committing fewer MEs. The number of medicines prescribed was associated with a higher likelihood of MEs. Out of 102 MEs, 48 (47.1%) were assessed as posing potentially no harm, 26 (25.5%) minor harm, 15 (14.7%) moderate harm, and 13 (12.8%) serious harm to the patients. Importantly, none of the MEs were assessed as posing potentially severe or life-threatening harm to the patients.

Conclusion

MEs in children following discharge are high, and systems should be developed to prevent these errors.

Validation of a method to assess the severity of medication administration errors in Brazil

INTRODUCTION

Medication errors are frequent and have high economic and social impacts; however, some medication errors are more likely to result in harm than others. Therefore, it is critical to determine their severity. Various tools exist to measure and classify the harm associated with medication errors; although, few have been validated internationally.

METHODS

We validated an existing method for assessing the potential severity of medication administration errors (MAEs) in Brazil. Thirty healthcare professionals (doctors, nurses and pharmacists) from Brazil were invited to score 50 cases of MAEs as in the original UK study, regarding their potential harm to the patient, on a scale from 0 to 10. Sixteen cases with known harmful outcomes were included to assess the validity of the scoring. To assess test-retest reliability, 10 cases (of the 50) were scored twice. Potential sources of variability in scoring were evaluated, including the occasion on which the scores were given, the scorers, their profession and the interactions among these variables. Data were analysed using generalisability theory. A G coefficient of 0.8 or more was considered reliable, and a Bland-Altman analysis was used to assess test-retest reliability.

RESULTS

To obtain a generalisability coefficient of 0.8, a minimum of three judges would need to score each case with their mean score used as an indicator of severity. The method also appeared to be valid, as the judges' assessments were largely in line with the outcomes of the 16 cases with known outcomes. The Bland-Altman analysis showed that the distribution was homogeneous above and below the mean difference for doctors, pharmacists and nurses.

CONCLUSION

The results of this study demonstrate the reliability and validity of an existing method of scoring the severity of MAEs for use in the Brazilian health system.

Attributes of errors, facilitators, and barriers related to rate control of IV medications: a scoping review

BACKGROUND

Intravenous (IV) medication is commonly administered and closely associated with patient safety. Although nurses dedicate considerable time and effort to rate the control of IV medications, many medication errors have been linked to the wrong rate of IV medication. Further, there is a lack of comprehensive studies examining the literature on rate control of IV medications. This study aimed to identify the attributes of errors, facilitators, and barriers related to rate control of IV medications by summarizing and synthesizing the existing literature.

METHODS

This scoping review was conducted using the framework proposed by Arksey and O'Malley and PRISMA-ScR. Overall, four databases-PubMed, Web of Science, EMBASE, and CINAHL-were employed to search for studies published in English before January 2023. We also manually searched reference lists, related journals, and Google Scholar.

RESULTS

A total of 1211 studies were retrieved from the database searches and 23 studies were identified from manual searches, after which 22 studies were selected for the analysis. Among the nine project or experiment studies, two interventions were effective in decreasing errors related to rate control of IV medications. One of them was prospective, continuous incident reporting followed by prevention strategies, and the other encompassed six interventions to mitigate interruptions in medication verification and administration. Facilitators and barriers related to rate control of IV medications were classified as human, design, and system-related contributing factors. The sub-categories of human factors were classified as knowledge deficit, performance deficit, and incorrect dosage or infusion rate. The sub-category of design factor was device. The system-related contributing factors were classified as frequent interruptions and distractions, training, assignment or placement of healthcare providers (HCPs) or inexperienced personnel, policies and procedures, and communication systems between HCPs.

CONCLUSIONS

Further research is needed to develop effective interventions to improve IV rate control. Considering the rapid growth of technology in medical settings, interventions and policy changes regarding education and the work environment are necessary. Additionally, each key group such as HCPs, healthcare administrators, and engineers specializing in IV medication infusion devices should perform its role and cooperate for appropriate IV rate control within a structured system.

Patient safety classifications, taxonomies and ontologies, part 2: A systematic review on content coverage

BACKGROUND

Content coverage of patient safety ontology and classification systems should be evaluated to provide a guide for users to select appropriate ones for specific applications. In this review, we identified and compare content coverage of patient safety classifications and ontologies.

METHODS

We searched different databases and ontology/classification repositories to identify these classifications and ontologies. We included patient safety-related taxonomies, ontologies, classifications, and terminologies. We identified and extracted different concepts covered by these systems and mapped these concepts to international classification for patient safety (ICPS) and finally compared the content of these systems.

RESULTS

Finally, 89 papers (77 classifications or ontologies) were analyzed. Thirteen classifications have been developed to cover all medical domains. Among specific domain systems, most systems cover medication (16), surgery (8), medical devices (3), general practice (3), and primary care (3). The most common patient safety-related concepts covered in these systems include incident types (41), contributing factors/hazards (31), patient outcomes (29), degree of harm (25), and action (18). However, stage/phase (6), incident characteristics (5), detection (5), people involved (5), organizational outcomes (4), error type (4), and care setting (3) are some of the less covered concepts in these classifications/ontologies.

CONCLUSION

Among general systems, ICPS, World Health Organization's Adverse Reaction Terminology (WHO-ART), and Ontology of Adverse Events (OAE) cover most patient safety concepts and can be used as a gold standard for all medical domains. As a result, reporting systems could make use of these broad classifications, but the majority of their covered concepts are related to patient outcomes, with the exception of ICPS, which covers other patient safety concepts. However, the ICPS does not cover specialized domain concepts. For specific medical domains, MedDRA, NCC MERP, OPAE, ADRO, PPST, OCCME, TRTE, TSAHI, and PSIC-PC provide the broadest coverage of concepts. Many of the patient safety classifications and ontologies are not formally registered or available as formal classification/ontology in ontology repositories such as BioPortal. This study may be used as a guide for choosing appropriate classifications for various applications or expanding less developed patient safety classifications/ontologies. Furthermore, the same concepts are not represented by the same terms; therefore, the current study could be used to guide a harmonization process for existing or future patient safety classifications/ontologies.

An Evaluation of the Relationship Between Medication Regimen Complexity as Measured by the MRC-ICU to Medication Errors in Critically Ill Patients

Purpose: The purpose of this study was to determine the relationship between medication regimen complexity-intensive care unit (MRC-ICU) score at 24 hours and medication errors identified throughout the ICU. Methods: A single-center, observational study was conducted from August to October 2021. The primary outcome was the association between MRC-ICU at 24 hours and total medication errors identified. During the prospective component, ICU pharmacists recorded medication errors identified over an 8-week period. During the retrospective component, the electronic medical record was reviewed to collect patient demographics, outcomes, and MRC-ICU score at 24 hours. The primary outcome of the relationship of MRC-ICU at 24 hours to medication errors was assessed using Pearson correlation. Results: A total of 150 patients were included. There were 2 pharmacists who recorded 634 errors during the 8-week study period. No significant relationship between MRC-ICU and medication errors was observed (r2 = .13, P = .11). Exploratory analyses of MRC-ICU relationship to major interventions and harm scores showed that MRC-ICU scores >10 had more major interventions (27 vs 14, P = .27) and higher harm scores (15 vs 7, P = .33), although these values were not statistically significant. Conclusion: Medication errors appear to occur independently of medication regimen complexity. Critical care pharmacists were responsible for mitigating a large number of medication errors.

Assessing the severity of medication administration errors identified in an observational study using a valid and reliable method

BACKGROUND

Epidemiological data on medication errors severity are scarce. The assessment of the prevalence and severity of medication errors may be limited because of several reasons, including a lack of standardization in the method of identifying medication administration errors and little knowledge about the appropriate assessment tools to measure severity. Thus, in this study, we aim to assess the potential severity of errors identified by direct observation in a teaching hospital.

METHODS

We used a validated method for assessing the potential severity of medication administration errors. Responses are scored on a 10-point scale. The 203 errors identified in a previous study were organized per similarity, resulting in 67 errors. This list was assessed by a panel of a physician, a nurse, and two pharmacists. The average score for each of the 67 errors was estimated considering the scores given by the 4 judges. Errors with a severity index < 3, between 3 and 7, and > 7 were considered minor, moderate, and severe, respectively.

RESULTS

Professionals classified the potential clinical significance of the errors as minor, moderate, and severe in 8.8% (18/203), 82.8% (168/203), and 8.4% (17/203) of the cases, respectively. Most errors considered potentially serious (41%, 7/17) were technical errors. Most potentially serious errors involved insulin. Regarding the administration route, nine (53%) potentially serious errors involved medications administered intravenously.

CONCLUSIONS

Most of the errors were considered as potentially moderated by the expert panel; however, the frequency of potentially serious errors was higher than that in previous studies using the same methodology, which highlights the need for strategies to reduce their occurrence.

Preventing Potential Patient Harm Through Clinical Content Interventions During Oncology Clinical Trial Implementation

OBJECTIVES

Clinical trial documents are complex and may have inconsistencies, leading to potential site implementation errors and may compromise participant safety. This study characterizes the frequency and type of administrative and potential patient safety interventions (PPSIs) made during the review of oncology trial documents for clinical trial implementation by centralized clinical content specialists.

METHODS

A dedicated group of centralized clinical content specialists reviewed trial documents, including the protocol, laboratory manual, and pharmacy/cellular therapy manual, and collected intervention data over a 1-year period. Each trial was categorized by study phase and sponsor type, and multiple interventions could be identified per trial. Interventions were deemed administrative or PPSIs, with PPSIs further subcategorized as medication, laboratory, procedure related, or other.

RESULTS

Of 585 clinical trials reviewed, 269 (46%) required intervention(s). Among 1001 interventions, 171 (17.1%) were PPSIs. Most PPSIs were medication related (45.6%), with drug dosing interventions most frequently identified (53.8%). Phase 1 trials had the highest proportion of PPSIs (0.35:1) and administrative interventions (2:1) per trial compared with all other phases. Investigator-initiated trials saw the highest proportion of PPSIs per trial (0.44:1) of all sponsor types.

CONCLUSIONS

This study demonstrates a gap in patient safety when assessing trial documents for clinical trial implementation. One solution to address this gap is the utilization of a centralized team of clinical specialists to preemptively review trial documents, thereby enhancing patient safety during clinical trial conduct.

Applicability of drug-related problem (DRP) classification system for classifying severe medication errors

BACKGROUND

Several classification systems for medication errors (MEs) have been established over time, but none of them apply optimally for classifying severe MEs. In severe MEs, recognizing the causes of the error is essential for error prevention and risk management. Therefore, this study focuses on exploring the applicability of a cause-based DRP classification system for classifying severe MEs and their causes.

METHODS

This was a retrospective document analysis study on medication-related complaints and authoritative statements investigated by the Finnish National Supervisory Authority for Welfare and Health (Valvira) in 2013-2017. The data was classified by applying a previously developed aggregated DRP classification system by Basger et al. Error setting and harm to the patient were identified using qualitative content analysis to describe the characteristics of the MEs in the data. The systems approach to human error, error prevention, and risk management was used as a theoretical framework.

RESULTS

Fifty-eight of the complaints and authoritative statements concerned MEs, which had occurred in a wide range of social and healthcare settings. More than half of the ME cases (52%, n = 30) had caused the patient's death or severe harm. In total, 100 MEs were identified from the ME case reports. In 53% (n = 31) of the cases, more than one ME was identified, and the mean number of MEs identified was 1.7 per case. It was possible to classify all MEs according to aggregated DRP system, and only a small proportion (8%, n = 8) were classified in the category "Other," indicating that the cause of the ME could not be classified to specific cause-based category. MEs in the "Other" category included dispensing errors, documenting errors, prescribing error, and a near miss.

CONCLUSIONS

Our study provides promising preliminary results for using DRP classification system for classifying and analyzing especially severe MEs. With Basger et al.'s aggregated DRP classification system, we were able to categorize both the ME and its cause. More research is encouraged with other ME incident data from different reporting systems to confirm our results.

Meta-Analysis of Medication Administration Errors in African Hospitals

ABSTRACT

The incidence of medication administration errors (MAEs) and associated patient harm continue to plague hospitals worldwide. Moreover, there is a lack of evidence to address this problem, especially in Africa. This research synthesis was intended to provide current evidence to decrease the incidence of MAEs in Africa. Standardized search criteria were used to identify primary studies that reported the incidence and/or predictors of MAEs in Africa. Included studies met specifications and were validated with a quality-appraisal tool. The pooled incidence of MAEs in African hospitals was estimated to be 0.56 (CI: 0.4324-0.6770) with a 0.13-0.93 prediction interval. The primary estimates were highly heterogeneous. Most MAEs are explained by system failure and patient factors. The contribution of system factors can be minimized through adequate and ongoing training of nurses on the aspects of safe medication administration. In addition, ensuring the availability of drug use guidelines in hospitals, and minimizing disruptions during the medication process can decrease the incidence of MAEs in Africa.

Short- and long-term effects of an electronic medication management system on paediatric prescribing errors

Electronic medication management (eMM) systems are designed to improve safety, but there is little evidence of their effectiveness in paediatrics. This study assesses the short-term (first 70 days of eMM use) and long-term (one-year) effectiveness of an eMM system to reduce prescribing errors, and their potential and actual harm. We use a stepped-wedge cluster randomised controlled trial (SWCRCT) at a paediatric referral hospital, with eight clusters randomised for eMM implementation. We assess long-term effects from an additional random sample of medication orders one-year post-eMM. In the SWCRCT, errors that are potential adverse drug events (ADEs) are assessed for actual harm. The study comprises 35,260 medication orders for 4821 patients. Results show no significant change in overall prescribing error rates in the first 70 days of eMM use (incident rate ratio [IRR] 1.05 [95%CI 0.92-1.21], but a 62% increase (IRR 1.62 [95%CI 1.28-2.04]) in potential ADEs suggesting immediate risks to safety. One-year post-eMM, errors decline by 36% (IRR 0.64 [95%CI 0.56-0.72]) and high-risk medication errors decrease by 33% (IRR 0.67 [95%CI 0.51-0.88]) compared to pre-eMM. In all periods, dose error rates are more than double that of other error types. Few errors are associated with actual harm, but 71% [95%CI 50-86%] of patients with harm experienced a dose error. In the short-term, eMM implementation shows no improvement in error rates, and an increase in some errors. A year after eMM error rates significantly decline suggesting long-term benefits. eMM optimisation should focus on reducing dose errors due to their high frequency and capacity to cause harm.

Patient safety classification, taxonomy and ontology systems: A systematic review on development and evaluation methodologies

INTRODUCTION

Patient safety classifications/ontologies enable patient safety information systems to receive and analyze patient safety data to improve patient safety. Patient safety classifications/ontologies have been developed and evaluated using a variety of methods. The purpose of this review was to discuss and analyze the methodologies for developing and evaluating patient safety classifications/ontologies.

METHODS

Studies that developed or evaluated patient safety classifications, terminologies, taxonomies, or ontologies were searched through Google Scholar, Google search engines, National Center for Biomedical Ontology (NCBO) BioPortal, Open Biological and Biomedical Ontology (OBO) Foundry and World Health Organization (WHO) websites and Scopus, Web of Science, PubMed, and Science Direct. We updated our search on 30 February 2021 and included all studies published until the end of 2020. Studies that developed or evaluated classifications only for patient safety and provided information on how they were developed or evaluated were included. Systems with covered patient safety terms (such as ICD-10) but are not specifically developed for patient safety were excluded. The quality and the risk of bias of studies were not assessed because all methodologies and criteria were intended to be covered. In addition, we analyzed the data through descriptive narrative synthesis and compared and classified the development and evaluation methods and evaluation criteria according to available development and evaluation approaches for biomedical ontologies.

RESULTS

We identified 84 articles that met all of the inclusion criteria, resulting in 70 classifications/ontologies, nine of which were for the general medical domain. The most papers were published in 2010 and 2011, with 8 and 7 papers, respectively. The United States (50) and Australia (23) have the most studies. The most commonly used methods for developing classifications/ontologies included the use of existing systems (for expanding or mapping) (44) and qualitative analysis of event reports (39). The most common evaluation methods were coding or classifying some safety report samples (25), quantitative analysis of incidents based on the developed classification (24), and consensus among physicians (16). The most commonly applied evaluation criteria were reliability (27), content and face validity (9), comprehensiveness (6), usability (5), linguistic clarity (5), and impact (4), respectively.

CONCLUSIONS

Because of the weaknesses and strengths of the development/evaluation methods, it is advised that more than one method for development or evaluation, as well as evaluation criteria, should be used. To organize the processes of developing classification/ontologies, well-established approaches such as Methontology are recommended. The most prevalent evaluation methods applied in this domain are well fitted to the biomedical ontology evaluation methods, but it is also advised to apply some evaluation approaches such as logic, rules, and Natural language processing (NLP) based in combination with other evaluation approaches. This research can assist domain researchers in developing or evaluating domain ontologies using more complete methodologies. There is also a lack of reporting consistency in the literature and same methods or criteria were reported with different terminologies.

Classifying and Disclosing Medical Errors

Medical errors are an unfortunate but common occurrence in health care. It is important to understand what medical errors are and what types of harm can occur to patients. Along with recognition of the error, disclosure is an equally important part of the process. Clinicians should provide open and honest discussion about the events that occurred to patients along with feedback to institutions on ways to prevent such errors in the future.

Validation of a method to assess the severity of medication administration errors in Brazil: a study protocol

BACKGROUND

Medication errors are frequent and have a high economic and social impact and is critical to know their severity. A variety of tools exist to measure and classify the harms associated with medication errors, but few are internationally validated.

DESIGN AND METHODS

It was decided to validate a method proposed by Dean and Barber for assessment of the potential severity of medication administration errors. A number of thirty health care professionals (doctors, nurses and pharmacists) from Brazil will receive an invitation to take part by scoring 50 cases of medication errors gathered from an original UK study regarding their potential harm to the patient on scale 0 to 10. Sixteen cases with known actual harm outcomes will be used to assess the validity of their scoring. By looking at 10 errors (out of the 50 cases) scored twice, reliability shall be assessed; and potential sources of variability in scoring will be evaluated depending on the severity of each of error case, the occasion when the scores were given, the scorer, their profession, and interactions among these variables. Generalizability theory will be used for analysing data. Expected impact of the study for public health: This study was submitted to the evaluation of the Research Ethics Committee of the Complexo Hospitalar Universitário Professor Edgard Santos and approved under no. 3.102.570/2019. This is the first validation of this method for use in Brazil, and will allow researchers to conduct more standardised evaluations of interventions to reduce the impact of medication errors.

Medication errors in inquiries to the Poison Information Center Erfurt - a systematic analysis

INTRODUCTION

Poison Information Centers (PICs) fulfil the legal mandate to provide advice and answer inquiries from healthcare professionals and medical nonprofessionals on measures to be taken in the event of an intoxication. Medication errors might be a frequent cause of intoxication. However, hardly any data on medication errors are available from PICs.

AIM

We aimed to investigate the incoming inquiries of a PIC with regard to medication errors.

METHODS

In the PIC database, we identified and analyzed medication errors in a retrospective analysis of inquiries from 2013 to 2020. We distinguished between medication errors committed by (i) laypersons or by healthcare professionals in (iia) medical care facilities or (iib) home care facilities. We evaluated the estimated potential risk of toxicity to assess the potential harm to the patient.

RESULTS

From 152,149 inquiries in total, 43.5% (n = 66,229) dealt with drug exposures. We identified medication error in 19.1% (n = 12,619) of those inquiries. Of those medication errors, 80.1% (n = 10,113) were committed by (i) laypersons and 19.9% (n = 2506) were committed by healthcare professionals, with nearly equal proportions occurring in medical care and in home care [(iia) 49.6% and (iib) 50.4%, respectively]. A total of 18,718 drugs were involved, with most medication errors found for ibuprofen, acetaminophen, and levothyroxine. The medication errors led to a minor estimated risk of toxicity in 46.6% (5,877/12,619); moderate and severe risk occurred in 7.0% (886/12,619) and 2.6% (329/12,619), respectively. Medication errors caused by laypersons or healthcare professionals in home care were associated with a lower risk compared to those caused by healthcare professionals in medical care (p < 0.001).

CONCLUSION

This study identified medication errors that were committed mainly by laypersons in almost 80% of the medication inquiries to a PIC. Medication errors caused by healthcare professionals in medical care led to a higher risk of harm to the patients.

Characterization of Medication Errors in a Medical Intensive Care Unit of a University Teaching Hospital in South Korea

OBJECTIVES

The objective of this study was to characterize the current status of medication errors (MEs) throughout the medication therapy process from prescribing to use and monitoring in a medical intensive care unit (MICU) in Korea.

METHODS

Four trained research pharmacists collected data through retrospectively reviewing electronic medical records for adults hospitalized in the MICU in 2017. The occurrence of MEs was determined through interprofessional team discussion led by an academic faculty pharmacist and a medical intensivist based on the medication administration records (MARs). The type of MEs and the consequent ME-related outcome severity were categorized according to the Pharmaceutical Care Network Europe and the National Coordinating Council for Medication Error Reporting and Prevention, respectively.

RESULTS

Overall, electronic medical records for 293 patients with 78,761 MARs were reviewed in this study. At least one type of ME occurred in 271 patients (92.5%) in association with 16,203 MARs (21%), primarily caused by inappropriate dose (35.5%), drug (27.8%), and treatment duration (25.1%). Clinically significant harmful events occurred in 24 patients (8%), including life-threatening (n = 5) and death (n = 2) cases. The 2 patients died of enoxaparin-induced fatal hemorrhage and neutropenia associated with ganciclovir and cefepime. Antibiotics were the most common culprit medications leading to clinically significant harmful events.

CONCLUSIONS

In conclusion, MEs are prevalent in the MICU in Korea, most commonly prescribing errors. Although mostly benign, harmful events including deaths may occur due to MEs, mainly associated with antibiotics. Systematic strategies to minimize these potentially fatal MEs are urgently needed.

What Severe Medication Errors Reported to Health Care Supervisory Authority Tell About Medication Safety?

OBJECTIVES

This study investigated severe medication errors (MEs) reported to the National Supervisory Authority for Welfare and Health (Valvira) in Finland and evaluated how the incident documentation applies to learning from errors.

METHODS

This study was a retrospective document analysis consisting of medication-related complaints and authoritative statements investigated by Valvira in 2013 to 2017 (n = 58).

RESULTS

Medication errors caused death or severe harm in 52% (n = 30) of the cases (n = 58). The majority (83%; n = 48) of the incidents concerned patients older than 60 years. Most likely, the errors occurred in prescribing (n = 38; 47%), followed by administration (n = 15; 19%) and monitoring (n = 14; 17%). The error process often included many failures (n = 24; 41%) or more than one health professional (n = 16; 28%). Antithrombotic agents (n = 17; 13%), opioids (n = 10; 8%), and antipsychotics (n = 10; 8%) were the therapeutic groups most commonly involved in the errors. Almost all error cases (91%; n = 53) were assessed as likely or potentially preventable. In 60% (n = 35) of the cases, the organization reported actions taken to improve medication safety after the occurrence of the investigated incident.

CONCLUSIONS

Medication errors reported to the national health care supervisory authority provide a valuable source of risk information and should be used for learning from severe errors at the level of health care systems. High age remains a key risk factor to severe MEs, which may be associated with a wide range of medications including those not typically perceived as high-alert medications or high-risk administration routes. Despite being complex processes, the severe MEs have a great potential to lead to developing systems, processes, resources, and competencies of health care organizations.

Healthcare professionals' perceptions on medication communication challenges and solutions - text mining and manual content analysis - cross-sectional study

BACKGROUND

Communication challenges contribute to medication incidents in hospitals, but it is unclear how communication can be improved. The aims of this study were threefold: firstly, to describe the most common communication challenges related to medication incidents as perceived by healthcare professionals across specialized hospitals for adult patients; secondly, to consider suggestions from healthcare professionals with regard to improving medication communication; and thirdly, to explore how text mining compares to manual analysis when analyzing the free-text content of survey data.

METHODS

This was a cross-sectional, descriptive study. A digital survey was sent to professionals in two university hospital districts in Finland from November 1, 2019, to January 31, 2020. In total, 223 professionals answered the open-ended questions; respondents were primarily registered nurses (77.7 %), physicians (8.6 %), and pharmacists (7.3 %). Text mining and manual inductive content analysis were employed for qualitative data analysis.

RESULTS

The communication challenges were: (1) inconsistent documentation of prescribed and administered medication; (2) failure to document orally given prescriptions; (3) nurses' unawareness of prescriptions (given outside of ward rounds) due to a lack of oral communication from the prescribers; (4) breaks in communication during care transitions to non-communicable software; (5) incomplete home medication reconciliation at admission and discharge; (6) medication lists not being updated during the inpatient period due to a lack of clarity regarding the responsible professional; and (7) work/environmental factors during medication dispensation and the receipt of verbal prescriptions. Suggestions for communication enhancements included: (1) structured digital prescriptions; (2) guidelines and training on how to use documentation systems; (3) timely documentation of verbal prescriptions and digital documentation of administered medication; (4) communicable software within and between organizations; (5) standardized responsibilities for updating inpatients' medication lists; (6) nomination of a responsible person for home medication reconciliation at admission and discharge; and (7) distraction-free work environment for medication communication. Text mining and manual analysis extracted similar primary results.

CONCLUSIONS

Non-communicable software, non-standardized medication communication processes, lack of training on standardized documentation, and unclear responsibilities compromise medication safety in hospitals. Clarification is needed regarding interdisciplinary medication communication processes, techniques, and responsibilities. Text mining shows promise for free-text analysis.

Development of incident severity classification for laboratory animals

An incident reporting system (IRS) prevents possible adverse events by collecting and analyzing incidents that occur. However, few studies are available regarding IRSs in the laboratory animal field. This study aimed to develop an incident severity classification for laboratory animals (ISCLA) to evaluate the usefulness of the IRS in laboratory animal facilities. Twenty-three incidents reported from March 2019 to February 2020 on our IRS were retrospectively reviewed. Three of the 23 incidents failed to obtain some experimental data. Two of these incidents were harmless to animals, but the other caused the animals moderate distress. In addition, two of the three incidents made animals unsuitable for experiments. Since the inconsistent impact of incidents on animals and experiments prevented the comparison of the severity of individual incidents, we developed the ISCLA. According to the ISCLA, the above three incidents were classified into Category 3b and 4a. The others were classified into Category 0 (n=5), 1 (n=6), 2 (n=3), and 3a (n=6) in ascending order of severity. No incident was classified into Category 4b and 5. Furthermore, incidents occurring in the animal housing area were more severe than those occurring in the supporting area (P=0.002). This study showed that incident occurrences had characteristics that were not visible from individual incidents alone. Moreover, the ISCLA was considered useful when conducting the IRS and taking improvement measures in laboratory animal facilities.

Care Coordination Strategies and Barriers during Medication Safety Incidents: a Qualitative, Cognitive Task Analysis

BACKGROUND

Medication errors are prevalent in healthcare institutions worldwide, often arising from difficulties in care coordination among primary care providers, specialists, and pharmacists. Greater knowledge about care coordination surrounding medication safety incidents can inform efforts to improve patient safety.

OBJECTIVES

To identify strategies that hospital and outpatient healthcare professionals (HCPs) use, and barriers encountered, when they coordinate care during a medication safety incident involving an adverse drug reaction, drug-drug interaction, or drug-renal concern.

DESIGN

We asked HCPs to complete a form whenever they encountered these incidents and intervened to prevent or mitigate patient harm. We stratified incidents across HCP roles and incident categories to conduct follow-up cognitive task analysis interviews with HCPs.

PARTICIPANTS

We invited all physicians and pharmacists working in inpatient or outpatient care at a tertiary Veterans Affairs Medical Center. We examined 24 incidents: 12 from physicians and 12 from pharmacists, with a total of 8 incidents per category.

APPROACH

Interviews were transcribed and analyzed via a two-stage inductive, qualitative analysis. In stage 1, we analyzed each incident to identify decision requirements. In stage 2, we analyzed results across incidents to identify emergent themes.

KEY RESULTS

Most incidents (19, 79%) were from outpatient care. HCPs relied on four main strategies to coordinate care: cognitive decentering; collaborative decision-making; back-up behaviors; and contingency planning. HCPs encountered four main barriers: role ambiguity and constraints, breakdowns (e.g., delays) in care, challenges related to the electronic health record, and factors that increased coordination complexity. Each strategy and barrier occurred across all incident categories and HCP groups. Pharmacists went to extra effort to ensure safety plans were implemented.

CONCLUSIONS

Similar strategies and barriers were evident across HCP groups and incident types. Strategies for enhancing patient safety may be strengthened by deliberate organizational support. Some barriers could be addressed by improving work systems.

Potential adverse drug events and its predictors among hospitalized patients at medical center in Ethiopia: a prospective observational study

Potential adverse drug event (PADE) is a medication error with the potential to cause associate degree injury however that does not cause any injury, either due to specific circumstances, chance, or as a result of the error being intercepted and corrected. This study aimed to assess the incidence, contributing factors, predictors, severity, and preventability of PADEs among hospitalized adult patients at Jimma Medical Center. A prospective observational study was conducted among hospitalized adult patients at a tertiary hospital in Ethiopia. Logistic regression was performed to identify factors predicting PADE occurrence. P-value < 0.05 was considered for statistical significance. A total of 319 patients were included. About 50.5% of them were females. The mean ± SD age of the participants was 43 ± 17.6 years. Ninety-four PADEs were identified. Number of medications (adjusted OR = 5.12; 95% CI: 2.01–13.05; p = 0.001), anticoagulants (adjusted OR = 2.51; 95% CI: 1.22–5.19; p = 0.013), anti-seizures (adjusted OR = 21.96; 95% CI: 6.57–73.39; p < 0.0001), anti-tuberculosis (adjusted OR = 2.2; 95% CI: 1.002–4.59, p = 0.049), and Elixhauser comorbidity Index ≤ 15 (adjusted OR = 6.24; 95% CI: 1.48–26.25, p = 0.013) were independent predictors of PADEs occurrence. About one-third of patients admitted to the hospital experienced PADEs.

Medication Without Harm: Developing optimal medication error reporting systems

Medication errors are amongst the most frequently occurring health care related incidents and have the potential to lead to life-threatening harm to patients. An incident reporting system is a traditional approach to improvement of patient safety and entails the retrieval of information from incident reports. This not only provides a better understanding of causes and contributing factors but also enables the collection of data on the severity of incidents, system deficiencies and the role of human factors in safety incidents. Medication error reporting systems are often developed as a part of larger incident reporting systems which deal with other types of incidents. Although a rise in the prevalence of medication errors has led to an increased demand for medication error reporting, little is known about characteristics and limitations of medication error reporting systems. The authors broach the subject of medication error reporting systems and propose a more robust and standardized approach.

Analysis of Dispensing Errors Made by First-Year Pharmacy Students in a Virtual Dispensing Assessment

Pharmacists have a crucial role in the supply of medications and ensuring optimal patient outcomes. However, with the increased use of prescription medications, there is a potential for dispensing errors to occur. Some dispensing errors can result in patient harm, with some leading to death. The development of safe and accurate dispensing skills in pharmacy students is an essential part of the pharmacy curriculum to prevent such dispensing errors from occurring. A retrospective study was conducted on a virtual dispensing assessment completed by first-year pharmacy students using MyDispense at Monash University. Students were assessed on their ability to safely and accurately dispense four prescriptions. The students’ answers in the assessment were then analyzed using qualitative and quantitative methods. Errors in drug quantity, number of repeats, product, patient and prescriber selection were quantitatively analyzed. Through the development of a codebook, frequency of errors was determined for label directions and appropriate use of ancillary labels. In this study, the dispensing errors that were identified depended on the class of medication. Errors in label directions were most common, with the majority of errors displaying incorrect route of administration, drug formulation and/or frequency of dosing. Identified errors were then further categorized into potential severity of harm, ranging from “no harm” to “severe harm”. The findings from this study show the types of errors made by students that are preventable and the potential for first-year pharmacy students to benefit from more comprehensive introductions to dispensing guides and safe environments to practice.

Healthcare Professionals Risk Assessments for Alert Overrides in High-Risk IV Infusions Using Simulated Scenarios

This study aimed to use healthcare professionals' assessments to calculate expected risk of intravenous (IV) infusion harm for simulated high-risk medications that exceed soft limits and to investigate the impact of relevant risk factors. We designed 30 infusion scenarios for four high-risk medications, propofol, morphine, insulin, and heparin, infused in adult intensive care unit (AICU) and adult medical and surgical care unit (AMSU). A total of 20 pharmacists and 5 nurses provided their assessed expected risk of harm in each scenario. Descriptive statistics, analysis of variance with least square mean, and post hoc test were conducted to test the effects of field limit type, soft (SoftMax), and hard maximum drug limit types (HardMax), and care area-medication combination on risk of harm. The results showed that overdosing scenarios with continuous and bolus dose limit types were assessed with significantly higher risks than those of bolus dose rate type. An overdose infusion in AICU over a large SoftMax was assessed to be of higher risk than over a small one, but not in AMSU. For overdose infusions with three levels of drug amount, greater drug amount in AICU and AMSU was assessed to have higher risk, except insignificant risk difference between the infusions with higher and moderate drug amount in AMSU. This study obtained expected risk for simulated high-risk IV infusions and found that different field limit and SoftMax types can affect expected risk based on healthcare professionals' perspectives. The findings will be regarded as benchmarks for validating risk quantification models in future research.

Communication issues contributing to medication incidents: Mixed-method analysis of hospitals' incident reports using indicator phrases based on literature

AIM

To identify the types and frequencies of communication issues (communication pairs, person related, institutional, structural, process and prescription-related issues) detected in medication incident reports and to compare communication issues that caused moderate or serious harm to patients.

BACKGROUND

Communication issues have been found to be among the main contributing factors of medication incidents, thus necessitating communication enhancement.

DESIGN

A sequential exploratory mixed-method design.

METHODS

Medication incident reports from Finland (n = 500) for the year 2015 in which communication was marked as a contributing factor were used as the data source. Indicator phrases were used for searching communication issues from free texts of incident reports. The detected issues were analysed statistically, qualitatively and considering the harm caused to the patient. Citations from free texts were extracted as evidence of issues and were classified following main categories of indicator phrases. The EQUATOR's SRQR checklist was followed in reporting.

RESULTS

Twenty-eight communication pairs were identified, with nurse-nurse (68.2%; n = 341), nurse-physician (41.6%; n = 208) and nurse-patient (9.6%; n = 48) pairs being the most frequent. Communication issues existed mostly within unit (76.6%, n = 383). The most commonly identified issues were digital communication (68.2%; n = 341), lack of communication within a team (39.6%; n = 198), false assumptions about work processes (25.6%; n = 128) and being unaware of guidelines (25.0%; n = 125). Collegial feedback and communication from patients and relatives were the preventing issues. Moderate harm cases were often linked with lack of communication within the unit, digital communication and not following guidelines.

CONCLUSIONS

The interventions should be prioritised to (a) enhancing communication about work-processes, (b) verbal communication about digital prescriptions between professionals, (c) feedback among professionals and (f) encouraging patients to communicate about medication.

RELEVANCE TO CLINICAL PRACTICE

Upon identifying the most harmful and frequent communication issues, interventions to strengthen medication safety can be implemented.

A drug identification model developed using deep learning technologies: experience of a medical center in Taiwan

BACKGROUND

Issuing of correct prescriptions is a foundation of patient safety. Medication errors represent one of the most important problems in health care, with 'look-alike and sound-alike' (LASA) being the lead error. Existing solutions to prevent LASA still have their limitations. Deep learning techniques have revolutionized identification classifiers in many fields. In search of better image-based solutions for blister package identification problem, this study using a baseline deep learning drug identification (DLDI) aims to understand how identification confusion of look-alike images by human occurs through the cognitive counterpart of deep learning solutions and thereof to suggest further solutions to approach them.

METHODS

We collected images of 250 types of blister-packaged drug from the Out-Patient Department (OPD) of a medical center for identification. The deep learning framework of You Only Look Once (YOLO) was adopted for implementation of the proposed deep learning. The commonly-used F1 score, defined by precision and recall for large numbers of identification tests, was used as the performance criterion. This study trained and compared the proposed models based on images of either the front-side or back-side of blister-packaged drugs.

RESULTS

Our results showed that the total training time for the front-side model and back-side model was 5 h 34 min and 7 h 42 min, respectively. The F1 score of the back-side model (95.99%) was better than that of the front-side model (93.72%).

CONCLUSIONS

In conclusion, this study constructed a deep learning-based model for blister-packaged drug identification, with an accuracy greater than 90%. This model outperformed identification using conventional computer vision solutions, and could assist pharmacists in identifying drugs while preventing medication errors caused by look-alike blister packages. By integration into existing prescription systems in hospitals, the results of this study indicated that using this model, drugs dispensed could be verified in order to achieve automated prescription and dispensing.