Medication-related incidents at 19 hospitals: A retrospective register study using incident reports

Analysis of the Incidence and Factors Influencing Medication Administration Errors Among Nurses: A Retrospective Study

AIMS

To explore the incidence and factors influencing medication administration errors (MAEs) among nurses.

BACKGROUND

Medication administration is a global concern for patient safety. Few studies have assessed the incidence of MAEs or explored factors that considered the interplay between behaviour, the individual and the environment.

METHODS

This retrospective study included 342 MAEs reported in the electronic nursing adverse event reporting system between January 2019 and September 2023 at a university-affiliated teaching hospital in China. Data on nurses' demographics and medication administration were extracted from the nursing adverse event reports. The reports were classified according to the severity of patient harm. The causes of the 342 MAEs were retrospectively analysed using content analysis based on Bandura's social cognitive theory. Descriptive statistics were used to calculate the proportion of medication errors and the distribution of subcategories.

RESULTS

In total, 74.3% of MAEs were adverse events owing to mistakes and resulted in no harm or only minor consequences for patients. Nurses aged 26-35 years and those with 6-10 years of experience were the most common groups experiencing MAEs. Factors influencing MAEs included personal ('knowledge and skills' and 'physical state'), environmental ('equipment and infrastructure,' 'work settings' and 'workload and workflow') and behavioural ('task performance' and 'supervision and communication') factors. The study further highlighted the interrelationships among personal, behavioural and environmental factors.

CONCLUSION

Multiple factors influence MAEs among nurses. Nurse-related MAEs and the relationship between behaviours, individual factors and the environment, as well as ways to reduce the occurrence of MAEs, should be considered in depth.

RELEVANCE TO CLINICAL PRACTICE

Understanding the factors influencing MAEs can inform training programs and improve the clinical judgement of healthcare professionals involved in medication administration, ultimately improving patient prognoses and reducing MAEs.

PATIENT OR PUBLIC CONTRIBUTION

The findings can help develop clinical guidelines for preventing MAEs.

Paediatric medication incident reporting: a multicentre comparison study of medication errors identified at audit, detected by staff and reported to an incident system

OBJECTIVES

To compare medication errors identified at audit and via direct observation with medication errors reported to an incident reporting system at paediatric hospitals and to investigate differences in types and severity of errors detected and reported by staff.

METHODS

This is a comparison study at two tertiary referral paediatric hospitals between 2016 and 2020 in Australia. Prescribing errors were identified from a medication chart audit of 7785 patient records. Medication administration errors were identified from a prospective direct observational study of 5137 medication administration doses to 1530 patients. Medication errors reported to the hospitals' incident reporting system were identified and matched with errors identified at audit and observation.

RESULTS

Of 11 302 clinical prescribing errors identified at audit, 3.2 per 1000 errors (95% CI 2.3 to 4.4, n=36) had an incident report. Of 2224 potentially serious prescribing errors from audit, 26.1% (95% CI 24.3 to 27.9, n=580) were detected by staff and 11.2 per 1000 errors (95% CI 7.6 to 16.5, n=25) were reported to the incident system. Although the prescribing error detection rates varied between the two hospitals, there was no difference in incident reporting rates regardless of error severity. Of 40 errors associated with actual patient harm, only 7 (17.5%; 95% CI 8.7% to 31.9%) were detected by staff and 4 (10.0%; 95% CI 4.0% to 23.1%) had an incident report. None of the 2883 clinical medication administration errors observed, including 903 potentially serious errors and 144 errors associated with actual patient harm, had incident reports.

CONCLUSION

Incident reporting data do not provide an accurate reflection of medication errors and related harm to children in hospitals. Failure to detect medication errors is likely to be a significant contributor to low error reporting rates. In an era of electronic health records, new automated approaches to monitor medication safety should be pursued to provide real-time monitoring.

Construction of a Multi-Label Classifier for Extracting Multiple Incident Factors From Medication Incident Reports in Residential Care Facilities: Natural Language Processing Approach

BACKGROUND

Medication safety in residential care facilities is a critical concern, particularly when nonmedical staff provide medication assistance. The complex nature of medication-related incidents in these settings, coupled with the psychological impact on health care providers, underscores the need for effective incident analysis and preventive strategies. A thorough understanding of the root causes, typically through incident-report analysis, is essential for mitigating medication-related incidents.

OBJECTIVE

We aimed to develop and evaluate a multilabel classifier using natural language processing to identify factors contributing to medication-related incidents using incident report descriptions from residential care facilities, with a focus on incidents involving nonmedical staff.

METHODS

We analyzed 2143 incident reports, comprising 7121 sentences, from residential care facilities in Japan between April 1, 2015, and March 31, 2016. The incident factors were annotated using sentences based on an established organizational factor model and previous research findings. The following 9 factors were defined: procedure adherence, medicine, resident, resident family, nonmedical staff, medical staff, team, environment, and organizational management. To assess the label criteria, 2 researchers with relevant medical knowledge annotated a subset of 50 reports; the interannotator agreement was measured using Cohen κ. The entire data set was subsequently annotated by 1 researcher. Multiple labels were assigned to each sentence. A multilabel classifier was developed using deep learning models, including 2 Bidirectional Encoder Representations From Transformers (BERT)-type models (Tohoku-BERT and a University of Tokyo Hospital BERT pretrained with Japanese clinical text: UTH-BERT) and an Efficiently Learning Encoder That Classifies Token Replacements Accurately (ELECTRA), pretrained on Japanese text. Both sentence- and report-level training were performed; the performance was evaluated by the F1-score and exact match accuracy through 5-fold cross-validation.

RESULTS

Among all 7121 sentences, 1167, 694, 2455, 23, 1905, 46, 195, 1104, and 195 included "procedure adherence," "medicine," "resident," "resident family," "nonmedical staff," "medical staff," "team," "environment," and "organizational management," respectively. Owing to limited labels, "resident family" and "medical staff" were omitted from the model development process. The interannotator agreement values were higher than 0.6 for each label. A total of 10, 278, and 1855 reports contained no, 1, and multiple labels, respectively. The models trained using the report data outperformed those trained using sentences, with macro F1-scores of 0.744, 0.675, and 0.735 for Tohoku-BERT, UTH-BERT, and ELECTRA, respectively. The report-trained models also demonstrated better exact match accuracy, with 0.411, 0.389, and 0.399 for Tohoku-BERT, UTH-BERT, and ELECTRA, respectively. Notably, the accuracy was consistent even when the analysis was confined to reports containing multiple labels.

CONCLUSIONS

The multilabel classifier developed in our study demonstrated potential for identifying various factors associated with medication-related incidents using incident reports from residential care facilities. Thus, this classifier can facilitate prompt analysis of incident factors, thereby contributing to risk management and the development of preventive strategies.

A cross-sectional study of the knowledge, skills, and 6 rights on medication administration by nurses at emergency department

Introduction: Medication errors occur when a patient is given the wrong drug or receives incorrect pharmacological therapy. Incorrect drug administration can cause fatal errors resulting in the patient’s death. Approximately 44,000-98,000 patients die each year due to medication errors and this condition is found often in the Emergency Room (ER) due to the complexity. Therefore, this study aims to analyze the relationship between nurses’ knowledge, skills, and 6 rights on medication at Emergency Department. Design and Methods: This is an analytical observational study involving 70 nurses randomly selected using consecutive sampling and working at the ER department of Saiful Anwar Hospital Malang. Data were collected through a questionnaire and analyzed descriptively to determine the knowledge and skills of nurses and the implementation of the correct principles of medication administration. Results: The results showed that most of the emergency room nurses had good knowledge and skills in applying the correct principles of medicine. However, the majority could not calculate the drug dose accurately. The spearman rank results showed that there was a relationship between knowledge and the 6 correct drug principles (p<0.001, α= 0,05; r = 0.491) with a percentage of 44%. This indicates that a higher knowledge results in the correct implementation of the drug. Similarly, there was a significant positive correlation between skills and proper medicine (p<0.001, α= 0,05; r = 0.378). Conclusions: It can be inferred that a higher nurse’s knowledge and skill results in a better administration of medicine.

Medication safety education in nursing research: Text network analysis and topic modeling

OBJECTIVES

This study aimed to identify the knowledge structure of medication safety nursing education literature by developing schematic diagrams of the relationship between keywords from a macro perspective. This study also identifies the research topics and trends over time.

DESIGN

This quantitative content study used text network analysis to explore keywords and research topics using topic modeling within the medication safety nursing education literature.

DATA SOURCES

PubMed, EMBASE, and Cochrane databases were used to search for the medication safety nursing education literature published until December 2021.

METHODS

Keywords from 2085 articles were examined using text network analysis and topic modeling with NetMiner 4.4.3.

RESULTS

The keywords with the most frequency and the highest networking degree in centrality were "patient," "medication," "program," "nurse," and "care." The emerging keywords assessed by time periods were identified; the first phase ("heart failure," "insulin," "chemotherapy," and "infusion"), the second phase ("medication errors," "staff," and "information"), the third phase ("program," "management," and "data"). The results of topic modeling were as follows: safe medication administration, safe medication reconciliation process, medication education for patients, medication errors in nursing practice, and multidisciplinary teamwork for medication safety.

CONCLUSION

These findings will help nursing researchers and educators to understand the trends and insights for medication safety education and educate future nurses to provide safer nursing care.

Negative emotions experienced by healthcare staff following medication administration errors: a descriptive study using text-mining and content analysis of incident data

BACKGROUND

Medication errors regardless of the degree of patient harm can have a negative emotional impact on the healthcare staff involved. The potential for self-victimization of healthcare staff following medication errors can add to the moral distress of healthcare staff. The stigma associated with errors and their disclosure often haunts healthcare professionals, leading them to question their own professional competence. This paper investigates the negative emotions expressed by healthcare staff in their reported medication administration error incidents along with the immediate responses they received from their seniors and colleagues after the incident.

METHOD

This is a retrospective study using a qualitative descriptive design and text mining. This study includes free-text descriptions of medication administration error incidents (n = 72,390) reported to National Reporting & Learning System in 2016 from England and Wales. Text-mining by SAS text miner and content analysis was used to analyse the data.

RESULTS

Analysis of data led to the extraction of 93 initial codes and two categories i.e., 1) negative emotions expressed by healthcare staff which included 4 sub-categories of feelings: (i) fear; (ii) disturbed; (iii) sadness; (iv) guilt and 2) Immediate response from seniors and colleagues which included 2 sub-categories: (i) Reassurance and support and (ii) Guidance on what to do after an error.

CONCLUSION

Negative emotions expressed by healthcare staff when reporting medication errors could be a catalyst for learning and system change. However, negative emotions when internalized as fear, guilt, or self-blame, could have a negative impact on the mental health of individuals concerned, reporting culture, and opportunities for learning from the error. Findings from this study, hence, call for future research to investigate the impact of negative emotions on healthcare staff well-being and identify ways to mitigate these in practice.

Analysis of medication and prescription background risk factors contributing to oral medication administration errors by nurses: A case-control study

Medication errors, including overdose and underdose, have a significant impact on patients and the medical economy. We need to prevent or avoid recurring medication errors. Therefore, we conducted a survey to identify medication and prescription background risk factors contributing to the administration of medication by nurses. This study surveyed cases of medication administration errors. This study was conducted at Higashinagoya National Hospital from April 1, 2018, to October 31, 2019. Patients' backgrounds and medication and prescription background risk factors were investigated. Three control cases were randomly selected for each medication error case. We defined the group of medication error cases as the medication error group and the group of control cases as the no-medication-error group. A logistic regression analysis was performed for factors related to medication errors. A total of 202 patients were included in the medication error group. The median age and number of medications were 78 years and 7, respectively. A total of 606 cases were included in the no-medication-error group. The median age and number of medications were 77 years and 6, respectively. The factors that exhibited a relationship with the medication error group were the number of administrations per day, dosing frequency on indicated days, prescription and start dates were the same, medications from multiple prescriptions, and continuous use of a medication received prior to admission. This study identified existing medication and prescription background risk factors. Overlapping risk factors from these groups might contribute to medication administration errors. Therefore, reviewing these factors is necessary to avoid recurring medication administration errors.

Analysis of contributory factors to incidents related to medication assistance for residents taking medicines in residential care homes for the elderly: a qualitative interview survey with care home staff

Background

In Japan, staff who are not doctors or nurses can assist the elderly in residential care facilities to take their pre-packaged medicines. Therefore, there is a potential risk of incidents specific to staffs. The aim of this study was to clarify the causes of incidents related to medication assistance by staff in residential care facilities.

Method

Semi-structured interviews with staff involved in medication incidents in long-term care facilities, focusing on how and why each incident happened, were conducted. The interview covered basic information about the subject and resident, the circumstances under which the incident had occurred, contributing factors, and countermeasures put in place. Verbatim transcripts of the interviews were prepared. Based on thematic analysis, codes and themes were created.

Results

Twelve subjects participated in this study. All subjects were staffs (not doctors or nurses) in long-term care facilities. All incidents covered in this study were incidents in which the wrong resident was given the medication. The incidents arose because of “not following procedures”, such as lack of “self-check of residents’ faces/residents’ names/residents’ medicine envelopes” or “double-check with other staff” or “using a device for medication intake”. Contributory factors were grouped into four categories: individual resident factor items such as “decreased ability to understand their medication” or “refusal to take medicines”, individual staff factor items such as “lack of knowledge related to medication” or “mental burden” or “experience in medication assistance”, team factor items such as “failure to communicate with other staff”, work environment factor items such as “presence of other residents” or “other work besides medication assistance” or “not enough time” or “little understanding of fostering a safety culture at the facility”.

Conclusion

This study identified four categories of contributory factors that may lead to incidents during medication assistance by caregivers for residents of care homes. These findings should be helpful for risk management in residential care facilities where staff usually provide medication assistance. Separation of meal times and medication assistance, and professional review to stagger the timing of administration of residents’ medication may be effective in reducing incidents.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03016-4.

Associations of person-related, environment-related and communication-related factors on medication errors in public and private hospitals: a retrospective clinical audit

BACKGROUND

Efforts to ensure safe and optimal medication management are crucial in reducing the prevalence of medication errors. The aim of this study was to determine the associations of person-related, environment-related and communication-related factors on the severity of medication errors occurring in two health services.

METHODS

A retrospective clinical audit of medication errors was undertaken over an 18-month period at two Australian health services comprising 16 hospitals. Descriptive statistical analysis, and univariate and multivariable regression analysis were undertaken.

RESULTS

There were 11,540 medication errors reported to the online facility of both health services. Medication errors caused by doctors (Odds Ratio (OR) 0.690, 95% CI 0.618-0.771), or by pharmacists (OR 0.327, 95% CI 0.267-0.401), or by patients or families (OR 0.641, 95% CI 0.472-0.870) compared to those caused by nurses or midwives were significantly associated with reduced odds of possibly or probably harmful medication errors. The presence of double-checking of medication orders compared to single-checking (OR 0.905, 95% CI 0.826-0.991) was significantly associated with reduced odds of possibly or probably harmful medication errors. The presence of electronic systems for prescribing (OR 0.580, 95% CI 0.480-0.705) and dispensing (OR 0.350, 95% CI 0.199-0.618) were significantly associated with reduced odds of possibly or probably harmful medication errors compared to the absence of these systems. Conversely, insufficient counselling of patients (OR 3.511, 95% CI 2.512-4.908), movement across transitions of care (OR 1.461, 95% CI 1.190-1.793), presence of interruptions (OR 1.432, 95% CI 1.012-2.027), presence of covering personnel (OR 1.490, 95% 1.113-1.995), misread or unread orders (OR 2.411, 95% CI 2.162-2.690), informal bedside conversations (OR 1.221, 95% CI 1.085-1.373), and problems with clinical handovers (OR 1.559, 95% CI 1.136-2.139) were associated with increased odds of medication errors causing possible or probable harm. Patients or families were involved in the detection of 1100 (9.5%) medication errors.

CONCLUSIONS

Patients and families need to be engaged in discussions about medications, and health professionals need to provide teachable opportunities during bedside conversations, admission and discharge consultations, and medication administration activities. Patient counselling needs to be more targeted in effort to reduce medication errors associated with possible or probable harm.

Factors causing medication errors in an electronic reporting system

Aim

To analyse medication error data from a hospital's electronic reporting system and identify the factors affecting error types and harmfulness.

Design

A retrospective study.

Methods

The 805 near misses and adverse events reported to the hospital's electronic reporting system between January 2014 and December 2018 were analysed using descriptive statistics, chi‐square tests and logistic regression analyses.

Results

A total of 632 near misses and 173 adverse events were reported. Near misses and adverse events were the most common error type during the dispensing stage and medication administration, respectively. The odds of medication errors reported by nurses with 1–9 years of clinical experience were relatively low. After adjusting for confounders, the odds of medication errors directly observed by nurses were 65% lower than the odds of medication errors not directly detected. In clinical practice, nurses must be educated about errors in reporting depending on their degree of clinical experience.

Threats to Narcotic Safety-A Narrative Review of Narcotic Incidents, Discrepancies and Near-Misses Within a Large Canadian Health System

Background

Canada is currently experiencing an opioid crisis.

Purpose

Nurses are the largest number of frontline healthcare professionals in Canada who administer narcotic pharmacotherapy, hence, they are ideally placed to improve narcotic stewardship in hospitals. Our study aims to understand the characteristics of narcotic incidents and hence recommend interventions for narcotic stewardship.

Methods

Our study was conducted within a 442-bed academic health sciences center in Ontario. We extracted anonymized narcotic incident reports which occurred over a 3-year period from the SAFER System. Descriptive statistics were utilized to analyze narcotic incidents and their contributory factors.

Results

272 narcotic incident reports were submitted to SAFER within the study period. Most incidents (51%) involved hydromorphone and morphine and were primarily categorized as Level I (n = 154) and Level II (n = 60). Incorrect narcotic dosing (44%), and narcotic count discrepancies (27%) were most commonly reported with active failures being the most commonly reported contributory factors such as failure to review medication orders prior to narcotic administration.

Conclusions

Nurses have an important role in narcotic safety as an intermediary between narcotic administration and incident reporting. Further research is needed to understand the enablers, barriers and opportunities for nurses and other healthcare professionals to improve narcotic stewardship.