The Contribution of Staffing to Medication Administration Errors: A Text Mining Analysis of Incident Report Data

Sustainability challenges concerning the effects of high-priced drugs on the day-to-day operations of community pharmacies in Finland

BACKGROUND

High-priced drugs pose a challenge for health budgets, policies, and patient safety. One of the key roles of community pharmacies is to ensure availability to prescription drugs regardless of their price. This has been identified as challenging in certain situations concerning high-priced drugs.

OBJECTIVES

The aim is to investigate the views of proprietary pharmacists regarding the effects of high-priced drugs on the day-to-day operations of pharmacies.

METHODS

The data collection of the study was performed as a national cross-sectional online survey. The inclusion criteria were being a proprietary pharmacist and a member of the Association of Finnish Pharmacies. The survey contained questions yielding both quantitative and qualitative answers. The study focused on the qualitative data which was analysed by deductive thematic analysis.

RESULTS

In total 604 proprietary pharmacists were sent the survey, and 174 eligible answers were included in the study, giving a response rate of 29%. The result describes the relationships between the economic, social, and environmental dimensions of sustainable development based on a framework by Wanamaker, with respect to high-priced drugs and community pharmacy operations as viewed by proprietary pharmacists. The main findings of the study show that proprietary pharmacists find the implementation of real-time reimbursement payments, a further reform of the pharmacy tax, and the abolishment of return bans to the wholesaler as risk mitigations and means to attain sustainability with respect to high-priced drugs and pharmacy practice. They experience that these changes would diminish high-priced drugs unnecessarily ending up as medical waste and improve the working conditions of the pharmacy staff by alleviating stress.

CONCLUSIONS

According to the respondents, high-priced drugs pose challenges for community pharmacies and the legislation and reimbursement system need to adapt to these challenges. If not, community pharmacies in Finland continue to face severe financial declines based on the study results.

Analysis of dementia research trends in nursing using text mining approach

This research aimed to analyze dementia research trends in nursing using a text mining approach. In this study, text mining approach was used to analyze the studies on dementia in the field of nursing around the world. In this study, summaries of all available publications in English between the years 1990-2023 were extracted from the database and transferred to an Excel table by using the 'Nursing' AND 'Dementia' query from the Thomson Reuters-ISI Web of Science database. According to the results of this research, a total of 21 concept groups were identified, four of which were the most important. It was determined that the most frequently used word in all of the studies obtained from the database was 'cost'. In this direction, scientific research on dementia in the field of nursing can be planned by evaluating the most frequently used concepts.

Assessment of Patient Matters in Healthcare Facilities

BACKGROUND AND OBJECTIVES

Ensuring the sustainability of healthcare facilities requires the evaluation of patient matters with appropriate methods and tools. The objective of this research is to develop a new tool for assessing patient matters as a component of social responsibility requirements that contribute to the sustainability of healthcare facilities.

MATERIALS AND METHODS

We carried out an analytical observational study in which, starting from the domains of the reference framework for the sustainability of health facilities (economic, environmental, social, provision of sustainable medical care services and management processes), we designed indicators that describe patient matters. To achieve this, we extracted from the scientific literature the most recent data and aspects related to patient matters that have been reported by representative hospitals from all over the world. These were organized into the four sequences of the quality cycle. We designed the method of evaluating the indicators based on the information couple achievement degree-importance of the indicator. In the experimental part of the study, we validated the indicators for the evaluation of patient matters and the evaluation method at an emergency hospital with an orthopedic profile.

RESULTS

We developed the patient matters indicator matrix, the content of the 8 indicators that make it up, questions for the evaluation of the indicators, and the evaluation grids of the indicators. They describe five levels for each variable of the achievement degree-importance couple. The practical testing of the indicators at the emergency hospital allowed the calculation of sustainability indicators and the development of a prioritization matrix for improvement measures.

CONCLUSIONS

Indicators designed in this research cover social responsibility requirements that describe patient matters. They are compatible and can be used by health facilities along with other implemented national and international requirements. Their added value consists in promoting social responsibility and sustainable development of healthcare facilities.

Nurses' perspectives on medication errors and prevention strategies in residential aged care facilities through a national survey

BACKGROUND

Medication errors are common in residential aged care facilities (RACFs) due to several factors. Effective medication management is essential to prevent medication errors among older people particularly due to the complexity of co-morbidities they can experience.

OBJECTIVES

This study aimed to examine and quantify the contributing factors of medication errors from nurses' perspectives and the prevention strategies to reduce medication errors among older adults living in RACFs.

METHODS

A survey with 140 completed responses from registered nurses (RNs) and endorsed enrolled nurses (EENs) working in RACFs across Australia were included in the study. The survey had 24 items, related to contributing factors of medication errors, and the prevention strategies. Descriptive statistics and exploratory factor analysis were used in the data analysis process.

RESULTS

The study identified medication errors are caused by contributing factors such as use of agency staffing (70.4%) and delays in receipt of laboratory results (94.3%). However, it also identified suggestions to reduce medication errors in RACFs, for example use of electronic alerts (88.3%), and efficient laboratory communication (91.8%). Our results revealed three key factors for causes (workload, interprofessional involvement and interruptions) and suggestions (medication safety alerts, medication process improvement and effective reporting).

CONCLUSION

Medication errors in RACFs are a global problem being one of the leading causes of morbidity and mortality. The knowledge and awareness of the factors associated with medication errors and the prevention strategies can guide potential quality improvement plans and contribute to minimisation of risk associated with medication safety in RACFs.

IMPLICATIONS FOR PRACTICE

The study recommends strategies for best practices in medication management such as interprofessional collaboration, implementing standardised policies and electronic alerts to reduce medication errors in RACFs.

Regional variation of potentially inappropriate medication use and associated factors among older adults: A nationwide register study

BACKGROUND

Certain medications should be used with caution in older persons, which challenges rational prescribing. Potentially inappropriate medications (PIMs) are defined as medicines whose potential risk of harm typically outweighs the clinical benefits in geriatric population. Earlier studies have found regional differences in PIM use, but the factors underlying this phenomenon are unclear.

OBJECTIVE

To compare prescription PIM prevalence among Finnish hospital districts and determine which population characteristics and factors related to social and health care are associated with regional variation.

METHODS

This nationwide register study was based on the Prescription Centre data on all people aged ≥75 years in 2017-2019. Hospital district (n = 20) characteristics were drawn from the Finnish Institute for Health and Welfare's, Finnish Medical Association's, and Finnish Medicines Agency's publicly open data. PIMs were defined according to the Finnish Meds75+ database. A linear mixed-effect model was used to analyze potential associations of regional characteristics with PIM prevalence.

RESULTS

Prevalence of PIMs varied between 16.4% and 24.8% across regions. The highest prevalence was observed in the southern regions, while the lowest prevalence was on the west coast. Hospital district characteristics associated with higher PIM prevalence were higher share of population living alone, with excessive polypharmacy, or assessed using the Resident Assessment Instrument, shortage of general practitioners in municipal health centers, and low share of home care personnel. Waiting time in health care or share of population with morbidities were not associated with PIM use. Of the total variance in PIM prevalence, 86% was explained by group-level factors related to hospital districts. The regional variables explained 75% of this hospital-district-level variation.

CONCLUSIONS

PIM prevalence varied significantly across hospital districts. Findings suggest that higher PIM prevalence may be related to challenges in the continuity of care rather than differences in health care accessibility or share of the population with morbidities.

'It's good to have the knowledge and the confidence': Mental health student nurses' views of a medication workshop

The administration of medication in a safe manner is a key nursing role and nursing regulatory bodies mandate that it is part of undergraduate training. However, it has been noted that qualified nursing staff are dissatisfied with the knowledge demonstrated by students. As such, a 2-day evidence-based workshop on medication management for final-year nursing students was facilitated to address knowledge deficits. Content was delivered by academics and practicing nurses. The aims of this study were to evaluate internship mental health student nurses' experiences of a 2-day medication management workshop. A qualitative descriptive design was adopted. Three focus group interviews were held with student nurses who partook in the workshop. Data were analysed using reflexive thematic analysis. Three themes were identified: Developing Confidence around Medication Management, Reflections on Learning Gained from the Workshop, and Enhancing Awareness and Vigilance of Medication Errors. Overall, participation in the workshop was identified as having a positive impact on students' knowledge, competence, and confidence in relation to becoming a safe practitioner. Students reported that the timing of the workshop - during internship - was appropriate for their knowledge needs. Findings indicate that the right amount of information was delivered by the right people, at the right time, in the right way. This study has highlighted the positive impact of a 2-day workshop delivered in the final year of mental health student nurse training, on their confidence and competence in the area of medication management. It provides some insight into how a practical collaborative approach to this type of education between academics and clinicians can help students bridge the theory-practice gap.

[The analysis of CIRSmedical.de using Natural Language Processing]

BACKGROUND

CIRSmedical.de is a publicly accessible, cross-institutional reporting and learning system, which is organized by the German Agency for Quality in Medicine (ÄZQ). CIRSmedical.de has existed since 2005 and has published more than 6,000 event reports. Up to now it has been common practice to analyse these reports in detail or carry out systematic evaluations focusing on specific topics. A systematic evaluation of all case reports has not yet been conducted. Natural Language Processing (NLP) is an analysis strategy from the field of Artificial Intelligence for indexing texts. The examination of case reports using NLP was carried out to describe the characteristics of event reports and comments.

MATERIALS AND METHODS

For this analysis 6,480 case reports from CIRSmedical.de (as of December 10, 2019) were provided by the ÄZQ as Excel files. Several free text fields were included in the analysis as well as the feedback of the CIRS team (expert commentary). Text lengths, reporting behaviour, sentiment values and keywords were examined. The algorithms for the analysis were developed with the programming language Python and the corresponding libraries NLTK and SpaCy.

RESULTS

The comparison of report lengths depending on the different subject groups presented a heterogeneous picture, in terms of both the number of reports and the number of words. There are more than 4,000 reports from the field of anaesthesiology, whereby text lengths vary particularly strongly with a right-skewed distribution. There are only a few reports from the field of psychotherapy, and these are also very short. The different professional groups (nurses, doctors, other staff) write reports of about the same length. Reports and expert commentaries also differ in terms of sentiment values. Due to the length of the comments, they are more negative in terms of sentiment. Keywords can be identified but show a high heterogeneity.

DISCUSSION

Systematic analysis using NLP allows for the description of text properties in event reports and comments. It is now possible to draw a conclusion about the reporters' intention, focus and mood when they report in CIRS. The sentiment analysis is an indication of the mood which the texts convey, both as a report and as a commentary. Text length analysis draws attention to different problems and tendencies: event reports are usually much shorter. Texts that are too short, however, run the risk that the information will not be readily usable for analysis. Comments are often longer, but here one faces the opposite problem: texts that are too long may not be read. The examination of texts by means of NLP helps to rethink the reason for and the form of input, both when reporting and when commenting. It is a first step in the automatic, supportive classification of texts and an improvement of the interaction between reporters and the system.

Exploring Nurses' Perceptions of Medication Error Risk Factors: Findings From a Sequential Qualitative Study

A focus group study was conducted to explore nurses’ perceptions of medication administration error associated factors in two medical wards of a tertiary hospital. Nurses were invited to participate in focus group discussions. Thematic analysis was employed and identified four themes: professional practice environment related factors, person-related factors, drug-related factors, and processes and procedures. Staffing, interruptions, system failures, insufficient leadership, and patient acuity were perceived as risk factors for medication errors. The findings of this study complement the findings of an observational study which investigated medication administration errors in the same setting. Although some findings were similar, important risk factors were identified only through focus group discussions with nurses. Nurses’ perceptions of factors influencing medication administration errors provide important considerations in addressing factors that contribute to errors and for improving patient safety.

Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters' Views

The purpose of this study was to describe incident reporters’ views identified by artificial intelligence concerning the prevention of medication incidents that were assessed, causing serious or moderate harm to patients. The information identified the most important risk management areas in these medication incidents. This was a retrospective record review using medication-related incident reports from one university hospital in Finland between January 2017 and December 2019 (n = 3496). Of these, incidents that caused serious or moderate harm to patients (n = 137) were analysed using artificial intelligence. Artificial intelligence classified reporters’ views on preventing incidents under the following main categories: (1) treatment, (2) working, (3) practices, and (4) setting and multiple sub-categories. The following risk management areas were identified: (1) verification, documentation and up-to-date drug doses, drug lists and other medication information, (2) carefulness and accuracy in managing medications, (3) ensuring the flow of information and communication regarding medication information and safeguarding continuity of patient care, (4) availability, update and compliance with instructions and guidelines, (5) multi-professional cooperation, and (6) adequate human resources, competence and suitable workload. Artificial intelligence was found to be useful and effective to classifying text-based data, such as the free text of incident reports.

Natural language processing with deep learning for medical adverse event detection from free-text medical narratives: A case study of detecting total hip replacement dislocation

BACKGROUND

Accurate and timely detection of medical adverse events (AEs) from free-text medical narratives can be challenging. Natural language processing (NLP) with deep learning has already shown great potential for analyzing free-text data, but its application for medical AE detection has been limited.

METHOD

In this study, we developed deep learning based NLP (DL-NLP) models for efficient and accurate hip dislocation AE detection following primary total hip replacement from standard (radiology notes) and non-standard (follow-up telephone notes) free-text medical narratives. We benchmarked these proposed models with traditional machine learning based NLP (ML-NLP) models, and also assessed the accuracy of International Classification of Diseases (ICD) and Current Procedural Terminology (CPT) codes in capturing these hip dislocation AEs in a multi-center orthopaedic registry.

RESULTS

All DL-NLP models outperformed all of the ML-NLP models, with a convolutional neural network (CNN) model achieving the best overall performance (Kappa = 0.97 for radiology notes, and Kappa = 1.00 for follow-up telephone notes). On the other hand, the ICD/CPT codes of the patients who sustained a hip dislocation AE were only 75.24% accurate.

CONCLUSIONS

We demonstrated that a DL-NLP model can be used in largescale orthopaedic registries for accurate and efficient detection of hip dislocation AEs. The NLP model in this study was developed with data from the most frequently used electronic medical record (EMR) system in the U.S., Epic. This NLP model could potentially be implemented in other Epic-based EMR systems to improve AE detection, and consequently, quality of care and patient outcomes.

Factors contributing to reported medication administration incidents in patients' homes - A text mining analysis

AIMS

To describe the characteristics of medication administration (MA) incidents reported to have occurred in patients' own homes (reporters' profession, incident types, contributing factors, patient consequence, and most common medications involved) and to identify the connection terms related to the most common contributing factors based on free text descriptions.

DESIGN

A retrospective study using descriptive statistical analysis and text mining.

METHODS

Medication administration incidents (N = 19,725) reported to have occurred in patients' homes between 2013-2018 in one district in Finland were analysed, describing the data by the reporters' occupation, incident type, contributing factors, and patient consequence. SAS® Text Miner was used to analyse free text descriptions of the MA incidents to understand contributing factors, using concept linking.

RESULTS

Most MA incidents were reported by practical (lower level) nurses (77.8%, N = 15,349). The most common category of harm was 'mild harm' (40.1%, N = 7,915) and the most common error type was omissions of drug doses (47.4%, N = 9,343). The medications most commonly described were Marevan [warfarin] (N = 2,668), insulin (N = 811), Furesis [furosemide] (N = 590), antibiotic (N = 446), and Panadol [paracetamol] (N = 416). The contributing factors most commonly reported were 'communication and flow of information' (25.5%, N = 5,038), 'patient and relatives' (22.6%, N = 4,451), 'practices' (9.9%, N = 1,959), 'education and training' (4.8%, N = 949), and 'work environment and resources' (3.0%, N = 598).

CONCLUSION

There is need for effective communication and clear responsibilities between home care patients and their relatives and health providers, about MA and its challenges in home environments. Knowledge and skills relating to safe MA are also essential.

IMPACT

These findings about MA incidents that have occurred in patients' homes and have been reported by home care professionals demonstrate the need for medication safety improvement in home care.

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

Aim

To examine (a) when medication incidents occur and which type is most frequent; (b) consequences for patients; (c) incident reporters' perceptions of causes; and (d) professional categories reporting the incidents.

Design

A descriptive multicentre register study.

Methods

This study included 775 medication incident reports from 19 Swedish hospitals during 2016-2017. From the 775 reports, 128 were chosen to establish the third aim. Incidents were classified and analysed statistically. Perceived causes of incidents were analysed using content analysis.

Results

Incidents occurred as often in prescribing as in administering. Wrong dose was the most common error, followed by missed dose and lack of prescription. Most incidents did not harm the patients. Errors in administering reached the patients more often than errors in prescribing. The most frequently perceived causes were shortcomings in knowledge, skills and abilities, followed by workload. Most medication incidents were reported by nurses.

Individual Circadian Preference, Shift Work, and Risk of Medication Errors: A Cross-Sectional Web Survey among Italian Midwives

Background: In order to explore the possible association between chronotype and risk of medication errors and chronotype in Italian midwives, we conducted a web-based survey. The questionnaire comprised three main components: (1) demographic information, previous working experience, actual working schedule; (2) individual chronotype, either calculated by Morningness–Eveningness Questionnaire (MEQ); (3) self-perception of risk of medication error. Results: Midwives (n = 401) responded “yes, at least once” to the question dealing with self-perception of risk of medication error in 48.1% of cases. Cluster analysis showed that perception of risk of medication errors was associated with class of age 31–35 years, shift work schedule, working experience 6–10 years, and Intermediate-type MEQ score. Conclusions: Perception of the risk of medication errors is present in near one out of two midwives in Italy. In particular, younger midwives with lower working experience, engaged in shift work, and belonging to an Intermediate chronotype, seem to be at higher risk of potential medication error. Since early morning hours seem to represent highest risk frame for female healthcare workers, shift work is not always aligned with individual circadian preference. Assessment of chronotype could represent a method to identify healthcare personnel at higher risk of circadian disruption.

Characteristics of recovery from near misses in primary health care nursing: A Prospective descriptive study

AIM

To describe the frequency and types of near misses and the recovery strategies employed by nurses in primary health care.

BACKGROUND

Insufficient data are available on the role of nurses in near miss events and related factors in primary health care.

METHOD

A prospective descriptive study was carried out at one Urban Primary Health Care Centre, within the Málaga-Guadalhorce Health District (Malaga, Spain), from January to December 2018. Four of the ten nurses volunteered to take part.

RESULTS

The nurses recovered 185 near misses, prevailing administrative or communication-related errors, followed by medication-related errors. No near misses were reported on the centre's anonymous error information platform.

CONCLUSIONS

A significant number of near misses occurred which could have been avoided with better communication among health care personnel. A striking finding is the failure to inform the health centre, which suggests that improvements in safety culture are needed.

IMPLICATIONS FOR NURSING MANAGEMENT

It is the responsibility and the duty of nursing management to be aware of the characteristics and frequency of near misses in primary health care, to implement strategies for improvement and to foster a culture in which the necessary information on actual or potential errors is supplied.