Risk Of Medication Errors Research Articles

Construction and validation of a presenteeism prediction model for ICU nurses in China

BackgroundPresenteeism, also known as impaired health productivity, refers to the condition of impaired productivity of an individual due to physiological or mental health problems. ICU, as a place of intensive care for patients with acute and critical illnesses, nurses have long faced the nature of work with high loads, high pressures, and high intensities, which makes them a high prevalence group of presenteeism. Presenteeism not only affects the physical and mental health and work wellbeing of nurses but also reduces the quality of nursing services and affects the life safety of patients, such as increasing the risk of falls during hospitalization, increasing the risk of medication errors, and prolonging the hospitalization time of patients. Therefore, early identification and targeted interventions are crucial to reduce presenteeism among ICU nurses.ObjectiveThis study aimed to construct and validate a predictive model for presenteeism among ICU nurses.DesignA cross-sectional study.Methods1,225 ICU nurses were convened from January to April 2023 from 25 tertiary and secondary hospitals in Sichuan Province, China. ICU nurses were randomly divided into a development set (n = 859) and a validation set (n = 366) according to a 7:3 ratio. Univariate and multifactorial logistic regression analyses were used to determine the influencing factors for presenteeism, and R software was used to construct a column-line graph prediction model. The differentiation and calibration of the predictive model were evaluated by the area under the curve of subjects’ work characteristics (ROC) and the Hosmer-Leme-show test, and the clinical decision curve evaluated the clinical validity of the predictive model.ResultsThe presenteeism rate of ICU nurses in the development set was 76.8%. Multifactorial logistic regression analysis showed that independent factors affecting ICU nurses’ presenteeism included income per month, physical health status, job satisfaction, perceived work stress, perceived social support, transformational leadership, and occupational coping self-efficacy. In the development set and validation set, the area under the ROC curve was 0.821 and 0.786, respectively; the sensitivity and specificity were 80.6, 69.8 and 80.9%, 65.1%, respectively; the Hosmer-Lemeshow goodness-of-fit was χ2 = 8.076 (p = 0.426) and χ2 = 5.134 (p = 0.743), respectively, and the model had relatively good discrimination and consistency. The clinical decision curve showed that the model had good clinical validity.ConclusionThe predictive model of presenteeism risk for ICU nurses constructed in this study has good predictive ability. The model can effectively identify ICU nurses with high presenteeism and provide a reference basis for developing targeted interventions to reduce presenteeism among ICU nurses.

Towards a national information model for medication orders in Sweden.

Semantic interoperability among health information systems (HISs), in particular electronic health records (EHRs), is crucial for informed healthcare decisions and patient access to vital health data. However, inconsistent medication information and limited health data exchange contribute to medication errors worldwide. While Sweden offers various solutions for health information exchange, there is a limitation in the exchange of medication orders and a lack of understanding the structure of medication orders among EHRs, highlighting the need for further exploration of the structure of medication orders. This study aims to develop a common information model of medication orders for EHRs to be used in the Swedish context. An explorative qualitative design study was conducted. Documents and reference models of how medication orders are structured were collected, and semi-structured interviews were conducted with five purposefully selected participants with insight into how medication orders are structured in Swedish EHRs. The data were analyzed using information needs analysis, information structure analysis, and code systems, classifications, and terminology analysis. The following information areas were identified for a medication order: medication, medication indication, way of administration, medication order details, and dosage. These information areas were conceptualized into a developed Unified Modeling Language Class Diagram information model with defined classes, attributes, and data types. The resulting information model provides a representation of how medication orders are depicted in EHRs in Sweden and is aligned with existing national information models such as the National Medication List, while still providing additional information related to medication order details. The developed information model could potentially provide a national standardized model for medication orders, contributing to enhance semantic interoperability and improving data exchange across various HISs. This could enhance data consistency, reducing the risk of medication errors and thereby improving patient safety.

Criteria for medication reconciliation in major orthopedic surgery in high-risk patients: A consensus based on the Delphi method.

Criteria for medication reconciliation in major orthopedic surgery in high-risk patients: A consensus based on the Delphi method.

Epidural and Intrathecal Magnesium Sulphate Administration Errors: Clinical Features and Contributing Factors

(Br J Anaesth. 2023; 130:435–440. doi:10.1016/j.bja.2022.12.015) Normal extracellular and intracellular magnesium ion (Mg²+) concentrations in the central nervous system are crucial for metabolic processes and cellular activities. Recently, magnesium sulphate (MgSO4) has gained popularity for enhancing the effects of analgesia (through routes such as intravenous, intrathecal, epidural), as an adjunct to opioids or local anesthetics. However, the availability of MgSO4 in various concentrations or as premixed preparations by pharmacies for infusion, increases the risk of medication errors.

Medication-focused telehealth interventions to reduce the hospital readmission rate: a systematic review.

Transition of care from hospital to community is a period that carries significant risk for medication errors, potentially leading to hospital readmission, and causing financial and emotional strain on patients and caregivers. Telehealth technologies offer promising solutions to reduce hospital readmission. Therefore, the goal of this systematic review was to examine the effect of interdisciplinary telehealth post-discharge services that include a medication-focused component on hospital readmissions. Following the PRISMA guidelines, a search was conducted in five scientific databases using keywords related to hospital readmission, medication therapy, and telehealth interventions. The review focused on randomised controlled trials published between 2000 and 2023, written in English. Out of 1,144 papers screened, 23 were included in the review. These studies targeted telehealth service provision to people over 60 years old with chronic illnesses. Various post-discharge telehealth interventions, including medication-focused components, were examined. Most of the interventions were multifaceted, embedded medication-focused interventions with reminders for diet, exercise, symptom check-ups, and education. Among the 23 included papers, 10 studies demonstrated success in reducing readmissions. Seven of these studies targeted patients with heart failure (HF). Overall, this review highlights the potential of telehealth medication-focused interventions in reducing hospital readmission rates in patients with HF.

Tools to improve discharge equity: Protocol for the pilot TIDE trial.

Tools to improve discharge equity: Protocol for the pilot TIDE trial.

A systematic review of outcomes reported in studies to optimise the medication use of patients at hospital discharge

IntroductionCare transitions, specifically hospital discharge, hold a risk for drug-related problems and medication errors. Effective interventions that optimise medication use during and after transitions are needed, yet there is no standardisation of the outcomes. This literature review aimed at collecting outcomes from studies investigating how to optimise medication use of patients following hospital discharge, and to categorise them, as a first step in the development of a core outcome set.MethodsWe systematically reviewed quantitative and qualitative literature using Embase, PubMed, CINAHL and the EU Clinical Trial Register databases. Studies investigating the optimisation of medication use following hospital discharge were eligible. The quantitative literature review specifically included trials and protocols that evaluated the effect of an intervention for patients ≥ 65 years or multimorbid / polypharmacy patients, as they are at high risk of drug-related problems. The qualitative literature review focused on the patients' and healthcare professionals’ views. Outcomes were summarised into unique outcome terms and categorised using an adapted version of the OMERACT filter 2.0.ResultsThe review included 75 quantitative and 20 qualitative studies. The interventions investigated in the quantitative literature mostly had multiple components performed either pre- or post-discharge. Sixty percent of the qualitative studies addressed the views of healthcare professionals, 40% the views of patients, and only one study addressed both. A median of 5 outcomes (range 1–17) were reported in the quantitative studies. In total, 91 unique outcomes were identified from the quantitative or qualitative literature, or both (73, 12 and 6 outcomes, respectively). Outcomes were categorised into five domains: 'medication' (n = 32 outcomes), 'economic impact/resource use' (n = 26), 'life impact' (n = 16), 'pathophysiological manifestations' (n = 15) and 'death' (n = 2). The top 5 most frequently measured outcomes in quantitative studies were number of readmissions (n = 54/75, 72%), mortality (n = 30/75, 40%), number of emergency department visits (n = 26/75, 35%), number of outpatient physician visits (n = 12/75, 16%), and medication adherence (n = 12/75, 16%).Discussion and conclusionThis study identified a large number of different outcomes, especially in the domains medication and economic impact/resource use. This heterogeneity impedes the identification of effective interventions and confirms the need for a core outcome set.

Medication Management of Patients With Cancer Undergoing Surgery From Preadmission to Discharge: A Mixed-Methods Systematic Review.

To identify and synthesise available evidence about regular medication management processes, from preadmission to discharge from hospital, in patients with cancer undergoing surgery. Mixed-methods systematic review. Studies published from inception of each database until February 2023 were screened, utilising four main search concepts. The JBI methodology for mixed-methods systematic review was followed in this review. MEDLINE, CINAHL, EMBASE, APA PsycINFO, Scopus and Web of Science. Eight out of 717 screened studies were included. Two themes related to patients' medication management were identified. Preoperative factors such as polypharmacy, potentially inappropriate medications, delirium-inducing medications and preoperative discontinuation-requiring medications were associated with several postoperative complications in patients with cancer. Additionally, pharmacist-led interventions and collaborative efforts between nurses and patients were shown to improve the medication management process across the perioperative pathway. This systematic review emphasises the necessity of effectively managing regular medication, especially before surgery, to mitigate postoperative complications in patients with cancer. It offers critical insights into how involving pharmacists and nurses enhances medication management outcomes, benefiting health care professionals and institutions aiming to optimise perioperative medication therapy. Enhancing patients' regular medication management through comprehensive reviews before surgery, and improving collaborative practices among pharmacists, nurses and patients via targeted interventions introduced by health care organisations, ensure safe medication use throughout the perioperative pathway. Improving regular medication management process can reduce risk of medication errors and adverse drug events and enhance postoperative outcomes. SWiM reporting guidelines. No patient or public contribution.

The Use of PediSTAT Application by Paramedics Working in Saudi Arabia to Reduce the Risk of Medication Error for Pediatric Patients.

This study aimed to assess and compare the rates of medication error (ME) using the PediSTAT application compared to the conventional method of calculating the correct dose and determining the appropriate route of medication administration for common pediatric emergencies. A prospective cross-sectional study design was used for the study. Data were collected using a questionnaire that was distributed to certified paramedics holding a bachelor's degrees or higher and working in Riyadh City, Saudi Arabia. Alternate simple random sampling was used to recruit the participants into two groups using the same questionnaire: the PediSTAT group and the conventional method group. The questionnaire contained four pediatric emergency vignettes: cardiac arrest, asthma exacerbation, seizures, and hypoglycemia. A total of 63 participants agreed to the study. Almost 80% of them were males, 81% held bachelor's degrees, and 87% were certified in pediatric resuscitation courses. The findings of the study showed that the use of the PediSTAT application increased accuracy and reduced the risk of ME for common pediatric emergencies. This was shown to be statistically significant for asthma medication dose (p-value < 0.001, 95% CI 0.034-0.352), midazolam dose (p-value = 0.012, 95% CI 0.030-0.764), and hypoglycemia medication dose (p-value < 0.001, 95% CI 0.046, 0.452). The study findings supported the use of standardized precalculated applications such as PediSTAT, which was shown to reduce the risk of ME in prehospital care for pediatric emergencies.

Medication safety in Indian critical care: Strategies, challenges, and best practices

Medication safety in intensive care units (ICUs) is of paramount importance due to the complexity of treatments and the vulnerability of critically ill patients. The use of high-risk medications, such as sedatives, anticoagulants, and vasopressors, combined with polypharmacy and rapid decision-making, increases the risk of medication errors. Such errors can lead to severe complications, including increased morbidity, prolonged hospital stays, and higher mortality rates. Ongoing education and simulation-based training for ICU staff further reinforce safe medication practices. However, challenges remain, including system-based errors and the need for continuous protocol evaluation. Promoting a culture of safety through teamwork and transparent communication is essential for sustaining improvements.

Komunikasi Efektif Dalam Keperawatan : Strategi Penggunaan Bahasa Yang Sederhana Edukasi Pasien

This article discusses the importance of effective communication in nursing, especially the use of simple language in patient education. Effective communication, using language that is easy to understand, increases patient satisfaction, reduces anxiety, and increases adherence to treatment. Literature studies show that clear and empathetic communication reduces the risk of medical errors, increases patient participation in care decision making, and results in better care outcomes. This article suggests effective communication strategies such as active listening and the use of visual aids to achieve optimal results. In conclusion, effective communication using simple language is the key to quality and holistic patient care.

A machine learning-based clinical predictive tool to identify patients at high risk of medication errors

A medication error is an inadvertent failure in the drug therapy process that can cause serious harm to patients by increasing morbidity and mortality and are associated with significant economic costs to the healthcare system. Medication reconciliation is the most cost-effective intervention and can result in a 66% reduction in medication errors. To improve patient safety, we developed a machine learning-based tool that prioritizes patients at risk of medication errors upon admission to the hospital to ensure that they undergo medication reconciliation by clinical pharmacists. The data were collected from the electronic health records of patients admitted to Reims University Hospital who underwent medication reconciliation between 2017 and 2023. The data from 7200 patients were used to train four machine learning-based models based on 52 variables in the development dataset. These models were used to prioritize admitted patients according to their likelihood of being exposed to a medication error. Our models, particularly the voting classifier model, demonstrated good performance (a recall of 0.75, precision of 0.65, F1 score of 0.70, AUROC of 0.74 and AUCPR of 0.75). In a retrospective evaluation simulating real-life use, the voting classifier model successfully identified 45% of the total patients selected who were found to have at least one unintended discrepancy compared to 21% when using the existing tool. The positive experimental results of this tool showed a superior improvement of 113% over the existing tool by targeting patients at risk of medication errors upon admission to Reims University Hospital.

Occurrence and associated factors of self-reported medical errors among Chinese physicians and nurses: a cross-sectional survey

Background Medical errors (MEs) significantly threaten patient safety globally. This study aimed to explore multidimensional factors associated with self-reported MEs among Chinese physicians and nurses. Methods A cross-sectional online survey using snowball sampling collected 7197 valid responses from Chinese physicians and nurses between October 2020 and April 2022. A self-reported question assessed MEs within the past three months. Sociodemographic characteristics, work-related factors, and mental distress were collected. Data were analyzed using stepwise logistic regression. Results 1285 (17.9%) physicians and nurses self-reported MEs during the previous 3 months. Factors associated with higher odds of self-reported MEs included male sex (OR: 1.44, 95% CI: 1.23-1.69), physician status (OR: 1.48, 95% CI: 1.26-1.73), history of mental illness (OR: 1.49, 95% CI: 1.16-1.91), longer weekly working hours (OR: 1.20-1.23, 95% CI: 1.03-1.47), workplace violence experience (OR: 1.54-1.75, 95% CI: 1.30-2.17), and dissatisfaction with the medical practice environment (OR: 1.20, 95% CI: 1.05-1.37). Conversely, being married (OR: 0.74, 95% CI: 0.62-0.89), holding a bachelor’s degree or higher (OR: 0.82, 95% CI: 0.70-0.97), and having more years of professional practice (OR: 0.96, 95% CI: 0.95-0.97) were associated with lower odds of self-reported MEs. Self-reported MEs were significantly and positively correlated with burnout (OR: 1.40, 95% CI: 1.20-1.62), depressive symptoms (OR: 1.38-1.45, 95% CI: 1.04-1.84), perceived stress (OR: 1.28-1.62, 95% CI: 1.06-2.02), and excessive daytime sleepiness (OR: 1.27-1.46, 95% CI: 1.10-1.79). Conclusions Self-reported MEs are relatively common among Chinese physicians and nurses, and are associated with various factors. Poor workplace conditions and mental distress are linked to an increased risk of MEs. Implementing effective interventions to improve workplace conditions and mental health is crucial for reducing MEs.

Drug Administration Errors Between Anesthetists: The Burden in Libya

Safe medication preparation and administration is a key part of anaesthesia practice. While anaesthesia practice has become safer, some medication errors can be inevitable leading to devastating complications. There is limited data and research on anaesthesia medication errors in developing economies. This study aims to identify the occurrence of medication errors and examines the associated factors, incident reporting, and preventive measures taken by anaesthetist practitioners in Libya. This was a multicentre; cross-sectional survey study conducted at three tertiary teaching hospitals in Libya from January 1, 2023 to June 30, 2023. An online questionnaire was sent to potential participants. Data was analysed using Statistical Package for Social Science (SPSS). The findings are expressed as absolute numbers and percentages. 185 completed surveys were returned for analysis (response rate = 84.09%). Anaesthesia technician (90.8%) commonly does medication preparation. 37.8% of respondents experienced one medication error and did not cause any harm to patients. Heavy workload/long hours (18.4%) were identified as the most common contributor to medication error in the operating room. Nearly all respondents 151 (81.6%) strongly agreed that double-checking the medication before administration was the most crucial preventive measure against medication errors. No effective reporting systems were identified. The study results are valuable to implementing and disseminating potential medication error risk mitigation or preventive strategies in developing economies. Enhancing medication administration safety in clinical practice should be a priority for policymakers at local and national levels across all healthcare contexts.

Unintentional medication discrepancies at care transitions: prevalence and their impact on post-discharge emergency visits in critically ill older adults

BackgroundUnintentional medication discrepancies during care transitions pose a significant risk for medication errors, particularly in critically ill older patients. This study aimed to investigate the prevalence of such discrepancies during care transitions and their impact on post-discharge emergency department (ED) visits in this patient population.MethodsThis retrospective cross-sectional study included patients aged 65 and older who were on chronic medications and admitted to the intensive care units of emergency departments (ED-ICUs) between 2019 and 2020. We evaluated unintentional medication discrepancies, including omissions or changes in medication type, dose, frequency, formulation, or administration route without clear clinical justification during care transition. The association between these discrepancies and post-discharge ED visits was analyzed using a multivariable Cox-proportional hazard model.ResultsOf the 339 patients analyzed, 68% encountered unintentional medication discrepancies at some point during care transitions, with prevalence of 35% at admission, 20% during transfer, and 49% at discharge. After adjusting for confounding factors, patients with unintentional medication discrepancies had a twofold higher risk of ED visits within 30 days of discharge (HR = 2.13, 95% CI = 1.06–4.30).ConclusionThis study demonstrated a substantial prevalence of unintentional medication discrepancies among critically ill older adults during care transitions, significantly increasing the risk of ED visits within a month of discharge. The findings highlight the crucial need for systematic identification and management of medication discrepancies throughout the care transition process to enhance patient safety.

Statement on medication simplification in long-term care facilities by the Japanese Society of Geriatric Pharmacy: English translation of the Japanese article.

Many older adults who are certified for long-term care services live or stay in long-term care facilities (LTCFs), where they receive medical and nursing care. These individuals often encounter medication-related problems, such as polypharmacy and complex medication regimens, including frequent administration schedules. Although considerable attention has been paid to polypharmacy in the context of optimizing medication use in older adults, little emphasis has been placed on simplifying these regimens. Recently, the Japanese Society of Geriatric Pharmacy issued statements on medication simplification in LTCFs based on a scoping review of the literature and expert opinions. In these statements, medication simplification is defined as the process of reducing the number of medication administration times, ideally to once during lunchtime. The statements outline principles and processes to achieve medication simplification through interprofessional collaboration, including consolidating and reducing the number of medication administration times a day to minimize the risk of medication errors and ensure medical safety. Medication simplification will play a substantial role in alleviating the burden of medication intake for residents, and in reducing and equalizing the workload of medication administration for staff members throughout the day in LTCFs. These statements suggest that administering medication during lunchtime is beneficial when an adequate number of staff members are available in LTCFs. We hope that these statements will help ensure patient safety, and facilitate successful medication optimization for all medical, nursing and social care professionals working in LTCFs. Geriatr Gerontol Int 2025; 25: 14-24.

Decision support systems in the diagnosis of urological diseases

The need to process large amounts of data has led to the creation of software that can improve and facilitate the work of medical staff. Decision support systems (DSS) are now used in many branches of medicine both at the outpatient and inpatient stages of medical care, helping clinicians to choose the tactics of treatment and management of each individual patient. These systems to a certain extent can improve treatment results and diagnostic process. The introduction of DSS in clinical practice has shown many advantages in reducing the frequency of misdiagnosis and, consequently, the risk of medical errors. At the same time, DSS can have a number of disadvantages. For example, physicians may view them as a threat to their “clinical autonomy”, and the implementation and subsequent maintenance of DSS can be quite costly. Artificial intelligence, which is increasingly being used not only for diagnosis, but also for treatment and prediction of outcomes in various diseases, should be considered as a prerequisite for the creation of DSS. Active development of artificial intelligence has been noted in almost all branches of medicine. A non-systematic review of the available literature published in the period between 2012 and 2022 has shown that the application of AI in prostate cancer diagnosis has great potential in clinical practice, as it helps both in the choice of treatment method and in planning the course of further surgery.

Burnout status of Japanese healthcare workers and the association with medical errors: A 1-year follow-up.

Burnout and medical errors are the most prevalent issues affecting health and life outcomes among healthcare professionals. This study aimed to investigate the longitudinal association between burnout and medical errors in healthcare workers in Japan. We conducted a prospective cohort study involving 539 healthcare workers from January 2017 to January 2018. Burnout was evaluated using the Maslach Burnout Inventory-General Survey (MBI-GS), which included exhaustion, cynicism, and professional efficacy dimensions. Medical errors during the previous year were measured by self-assessment at follow-up. Multivariate modified Poisson regressions estimated the association between baseline burnout and follow-up medical errors. In the age and sex-adjusted model, overall burnout was significantly associated with medical errors (p = 0.008). Participants with high burnout levels exhibited a greater risk of medical errors than those with low or moderate levels (RR = 1.19, 95% CI: 1.05-1.35). Exhaustion and cynicism correlated significantly with medical errors (p < 0.05). High or moderate levels of exhaustion and cynicism were associated with elevated risks of medical errors (RR = 1.31 [95% CI: 1.10-1.55]; 1.25 [1.02-1.53]), (RR = 1.31 [95% CI: 1.13-1.53]; 1.20 [1.03-1.41]), compared to low-level counterparts, respectively. Healthcare workers who experience burnout may be at an increased risk for medical errors.

Analysis of Workload and Work Environment on Reducing Medication Errors with the Use of Technology as an Intervening Variable in Inpatient Pharmacy Depots Bogor City Regional Hospital

This study aims to analyze the impact of workload and work environment on reducing medication error through the use of technology as an intervening variable in the Inpatient Pharmacy Depot of RSUD Kota Bogor. Medication error refers to errors in the medication process that can endanger patients, and this research examines how workload, work environment, and technology influence such errors. The research method employed is quantitative, using a survey approach with questionnaires distributed to 30 pharmaceutical staff at the Inpatient Pharmacy Depot of RSUD Kota Bogor. Data analysis was conducted using the Partial Least Square (PLS) method. The results show that workload has a significant effect on medication error. The higher the workload, the greater the risk of medication errors. However, workload does not have a significant impact on the use of technology. On the other hand, the work environment does not significantly affect medication error, but it does have a significant influence on the use of technology. Technology, in turn, does not significantly reduce medication error and does not mediate the relationship between workload or work environment and medication error.Based on these findings, it is recommended that the management of RSUD Kota Bogor improves workload management and optimizes the use of technology by providing better training to pharmaceutical staff. Additionally, efforts should be made to enhance the work environment to better support the implementation of technology in reducing medication errors and improving patient safety.

Criteria for medication reconciliation in major orthopedic surgery in high-risk patients: A consensus based on the Delphi method

Criteria for medication reconciliation in major orthopedic surgery in high-risk patients: A consensus based on the Delphi method