Incidence, causes, and consequences of preventable adverse drug reactions occurring in inpatients: A systematic review of systematic reviews

Antiviral Use in Mild-to-Moderate SARS-CoV-2 Infections during the Omicron Wave in Geriatric Patients

(1) Background: Geriatric patients are at high risk of complications of Coronavirus disease-2019 (COVID-19) and are good candidates for antiviral drugs. (2) Methods: A retrospective study of electronic health records (EHRs) aiming to describe antiviral (nirmatrelvir and ritonavir (nirmatrelvir/r) or remdesivir) use, drug-drug interactions (DDIs) and adverse drug reactions (ADRs) in elderly patients (75 and over), hospitalized with mild-to-moderate COVID-19 between July 2022 and June 2023. (3) Results: Out of 491 patients (mean age: 86.9 years), 180 (36.7%) received nirmatrelvir/r, 78 (15.9%) received remdesivir, and 233 (47.4%) received no antiviral therapy. No association was found between the choice of antiviral and the demographic or medical data. No serious ADR was observed. Nirmatrelvir/r dosage adjustment was inadequate in 65% of patients with renal impairment. In total, 128 patients (71%) on nirmatrelvir/r had potential pharmacokinetic DDIs, with 43 resulting in a possibly related ADR. In the remdesivir group, pharmacodynamic DDIs were more frequent, with QTc prolongation risk in 56 patients (72%). Only 20 patients underwent follow-up ECG, revealing QTc prolongation in 4. (4) Conclusions: There is an underutilization of antivirals despite their justified indications. Nirmatrelvir/r dosage was rarely adjusted to renal function. Dose adjustments and closer monitoring are needed due to the high risk of drug interactions.

Antiseizure adverse drug reaction and associated factors among epileptic patients at Jimma Medical Center: a prospective observational study

A growing body of evidence suggests that adverse drug reactions (ADRs) are a major cause of morbidity and mortality in the healthcare system. Fifteen to twenty-five percent of patients with epilepsy discontinued antiseizure drugs (ASDs) within 6 months of therapy owing to intolerable adverse drug reactions. In Ethiopia, the prevalence of antiseizure adverse drug reactions and associated factors was not extensively conducted in advanced settings like Jimma Medical Centers. Hence, the objective of this study is to assess patterns of adverse drug reactions and associated factors among ambulatory epileptic patients at tertiary hospitals in Ethiopia. A hospital-based prospective observational study was spanned for 1 year. Two hundred ninety patients were consecutively recruited into the study from all epileptic patients attending the ambulatory clinic. Relevant data were collected through patient interviews and medical chart reviews. The causality assessment was done by using the Naranjo Probability Scale. Epi-Data manager version 4.6.0.4 was used for data entry and statistical analysis was performed by Statistical Package for Social Science version 25.0 (SPSS). Stepwise backward logistic regression analysis was done to identify factors that increase the risk of antiseizure adverse drug reactions. The mean (± SD) age of the participants were 29.91(± 11.26) years. The overall prevalence of ADR was 33.8% (95% CI 29.2-39.9%). A total of 110 adverse drug reactions were identified among 98 patients with an average of 1.12 per patient. ADRs were frequently reported with phenobarbital (52.04%) and phenytoin (34.70%). The commonly identified adverse drug reactions were epigastric pain (27.55%) and central nervous system drowsiness (23.46%). Comorbidity (AOR = 5.91, 95% CI (2.14-16.32), seizure-free period of fewer than 2 years (AOR = 1.94, 95% CI (1.18-3.19), and polytherapy (AOR = 1.35, 95% CI (1.80-2.26) were significantly associated with adverse drug reactions. This trial had a comparatively high percentage of adverse medication reactions. Adverse medication reactions were more common in patients with polytherapy, comorbidities, and seizure-free durations less than two years. Therefore, medical practitioners should advise patients who exhibit these traits on how to reduce or avoid bad drug responses or provide comfort in the event of small incidents.

An innovative method to strengthen evidence for potential drug safety signals using Electronic Health Records

Reports from spontaneous reporting systems (SRS) are hypothesis generating. Additional evidence such as more reports is required to determine whether the generated drug-event associations are in fact safety signals. However, underreporting of adverse drug reactions (ADRs) delays signal detection. Through the use of natural language processing, different sources of real-world data can be used to proactively collect additional evidence for potential safety signals. This study aims to explore the feasibility of using Electronic Health Records (EHRs) to identify additional cases based on initial indications from spontaneous ADR reports, with the goal of strengthening the evidence base for potential safety signals. For two confirmed and two potential signals generated by the SRS of the Netherlands Pharmacovigilance Centre Lareb, targeted searches in the EHR of the Leiden University Medical Centre were performed using a text-mining based tool, CTcue. The search for additional cases was done by constructing and running queries in the structured and free-text fields of the EHRs. We identified at least five additional cases for the confirmed signals and one additional case for each potential safety signal. The majority of the identified cases for the confirmed signals were documented in the EHRs before signal detection by the Dutch Medicines Evaluation Board. The identified cases for the potential signals were reported to Lareb as further evidence for signal detection. Our findings highlight the feasibility of performing targeted searches in the EHR based on an underlying hypothesis to provide further evidence for signal generation.

Effectiveness of interprofessional education for medical and nursing professionals and students on interprofessional educational outcomes: A systematic review

AIM AND BACKGROUND

Patient safety is a global health priority as unsafe care is a principal cause of death and disability. Ineffective interprofessional communication and collaboration among nursing and medical professionals and students contribute to unsafe practices. Interprofessional education provides opportunities to strengthen nurse-physician collaboration and enhance patient care. However, there is inconclusive evidence regarding interprofessional education effectiveness. This review aims to systematically evaluate interprofessional education effectiveness for nursing and medical professionals and students on interprofessional educational outcomes (interprofessional attitudes, perceptions, skills, knowledge, behaviours, and organisational and patient outcomes).

DESIGN AND METHODS

PubMed, Cochrane Library, Embase, Scopus, CINAHL, ERIC, PsycInfo, Web of Science were last searched on 13 January 2022. This review included published and unpublished randomised controlled trials, quasi-experimental and mixed-method studies in English examining interprofessional education outcomes among nursing and medical professionals and students. Two reviewers independently appraised studies using the Joanna Briggs Institute Critical Appraisal Tools and extracted data using a modified Joanna Briggs Institute data extraction form. Narrative synthesis was conducted instead of meta-analysis since majority of the included studies had quasi-experimental design, and various interventions and outcomes. Certainty of evidence was appraised using the Grading of Recommendations, Assessment, Development and Evaluations tool.

RESULTS

This review included 15 studies involving 1185 participants. Improvements were reported in each interprofessional educational outcome after interprofessional education. High-fidelity simulation with multiple scenarios, standardised communication tools, didactic and active learning methods, theoretical frameworks, debriefing sessions and provider training enhanced interprofessional education effectiveness.

CONCLUSIONS

Effectiveness of interprofessional education for nursing and medical professionals and students was demonstrated since improvements were observed for each interprofessional educational outcome. This systematic review addressed literature gaps, demonstrated effectiveness of interprofessional education in clinical practice and academic curricula and provided evidence-based insights that future research can consider to enhance global patient safety standards for optimal patient outcomes and quality of healthcare. Caution is advised in interpreting findings due to 'very low' evidence certainty and limited studies. More high-quality randomised controlled trials with longitudinal designs are needed.

Machine learning as a tool to identify inpatients who are not at risk of adverse drug events in a large dataset of a tertiary care hospital in the USA

AIMS

Adverse drug events (ADEs) are a major threat to inpatients in the United States of America (USA). It is unknown how well machine learning (ML) is able to predict whether or not a patient will suffer from an ADE during hospital stay based on data available at hospital admission for emergency department patients of all ages (binary classification task). It is further unknown whether ML is able to outperform logistic regression (LR) in doing so, and which variables are the most important predictors.

METHODS

In this study, 5 ML models- namely a random forest, gradient boosting machine (GBM), ridge regression, least absolute shrinkage and selection operator (LASSO) regression, and elastic net regression-as well as a LR were trained and tested for the prediction of inpatient ADEs identified using ICD-10-CM codes based on comprehensive previous work in a diverse population. In total, 210 181 observations from patients who were admitted to a large tertiary care hospital after emergency department stay between 2011 and 2019 were included. The area under the receiver operating characteristics curve (AUC) and AUC-precision-recall (AUC-PR) were used as primary performance indicators.

RESULTS

Tree-based models performed best with respect to AUC and AUC-PR. The gradient boosting machine (GBM) reached an AUC of 0.747 (95% confidence interval (CI): 0.735 to 0.759) and an AUC-PR of 0.134 (95% CI: 0.131 to 0.137) on unforeseen test data, while the random forest reached an AUC of 0.743 (95% CI: 0.731 to 0.755) and an AUC-PR of 0.139 (95% CI: 0.135 to 0.142), respectively. ML statistically significantly outperformed LR both on AUC and AUC-PR. Nonetheless, overall, models did not differ much with respect to their performance. Most important predictors were admission type, temperature and chief complaint for the best performing model (GBM).

CONCLUSIONS

The study demonstrated a first application of ML to predict inpatient ADEs based on ICD-10-CM codes, and a comparison with LR. Future research should address concerns arising from low precision and related problems.

Adverse drug reactions in hospitals: population estimates for Portugal and the ICD-9-CM to ICD-10-CM crosswalk

BACKGROUND

Adverse drug reactions (ADR), both preventable and non-preventable, are frequent and pose a significant burden. This study aimed to produce up-to-date estimates for ADR rates in hospitals, in Portugal, from 2010 to 2018. In addition, it explores possible pitfalls when crosswalking between ICD-9-CM and ICD-10-CM code sets for ADR identification.

METHODS

The Portuguese Hospital Morbidity Database was used to identify hospital episodes (outpatient or inpatient) with at least one ICD code of ADR. Since the study period spanned from 2010 to 2018, both ICD-9-CM and ICD-10-CM codes based on previously published studies were used to define episodes. This was an exploratory study, and descriptive statistics were used to provide ADR rates and summarise episode features for the full period (2010-2018) as well as for the ICD-9-CM (2010-2016) and ICD -10-CM (2017-2018) eras.

RESULTS

Between 2010 and 2018, ADR occurred in 162,985 hospital episodes, corresponding to 1.00% of the total number of episodes during the same period. Higher rates were seen in the oldest age groups. In the same period, the mean annual rate of episodes related to ADR was 174.2/100,000 population. The episode rate (per 100,000 population) was generally higher in males, except in young adults (aged '15-20', '25-30' and '30-35' years), although the overall frequency of ADR in hospital episodes was higher in females.

CONCLUSIONS

Despite the ICD-10-CM transition, administrative health data in Portugal remain a feasible source for producing up-to-date estimates on ADR in hospitals. There is a need for future research to identify target recipients for preventive interventions and improve medication safety practices in Portugal.

Pharmacovigilance and Adverse Drug Reactions Reporting: Healthcare Providers' Experiences from Southern Highland Tanzania

Purpose

This exploratory qualitative study aimed to analyze the experiences of healthcare providers (HCPs) in pharmacovigilance (PV) and ADR reporting in the southern highland zone of Tanzania.

Methods

In 2022, an exploratory qualitative case study using in-depth interviews (IDIs) was conducted to explore the experiences of PV and ADR reporting among HCPs (doctors, nurses, and pharmacists). The study was carried out in a zonal referral hospital and a regional referral hospital of the Tanzanian southern highlands zone. Inductive-deductive thematic analysis was adopted for data analysis.

Results

Participants demonstrated adequate knowledge of PV and its related activities including ADR reporting. Knowing the interactions and wrong medication dosage as sources of ADR, signs, and symptoms, stopping the drug, and treating the symptoms following ADR emerged as subthemes linked with adequate knowledge in identifying and managing ADR. Participants perceived reporting ADR as laborious, posing a subjective burden and that not all ADRs needed to be reported. The latter contributed to limited participation in ADR reporting despite that participants were conversant with both physical and online ADR reporting platforms.

Conclusion

Although HCPs are well informed about PV and ADR reporting including the benefits to public health, their involvement in ADR reporting is low. In addition to the ongoing on-the-job training and regular supportive supervision for HCPs to improve the ADR practice, there is still a need to explore other strategies to be used as motives for HCPs to report ADR regularly.

Are Physician Assistants Able to Correctly Identify Prescribing Errors? A Cross-Sectional Study

PURPOSE

(1) To describe how often physician assistant (PA) students correctly identify prescribing errors and (2) examine between-cohort differences on ability to correctly identify prescribing errors.

METHODS

This was a cross-sectional study of 2 cohorts of PA students at one institution. Students were presented with 3 hypothetical prescriptions, 2 of which contained a prescribing error. For each prescription, students were asked to (1) identify whether an error occurred and (2) indicate the type of error. A simple Poisson regression model analyzed the data.

RESULTS

We received responses from 130 students (72.6% response rate). Approximately 12% (12.3%, n = 16) correctly identified whether all 3 prescriptions were correct. The median number of correctly identified prescriptions was 1 (interquartile range = 1). There was not a statistically significant between-cohort difference identifying the correct number of prescriptions (β = 0.27, P = .10).

CONCLUSION

Physician assistant students' prescribing error identification was similar to previous research in medical and nursing students. Efforts to improve prescribing training are critical to ensure patient safety.

Benchmarking of medication incidents reporting and medication error rates in a JCI accredited university teaching hospital at a GCC country

Introduction

The benchmarking for medication incidents rate is not regarded as a recognized key performance measure or indicator in national or international organizations. The absence of benchmarking the medication incidents results in the loss of a self-governing perception of how well we performed compared to other peers.

Methodology and settings

This 600-bed tertiary, Joint Commission International (JCI) accredited hospital retrospective analysis looked at all medication management-related events from January-2018 to December-2021. The study design follows descriptive, cross-sectional, retrospective prevalence research.

Results

The rate of medication incidents that resulted in harm declined from Q3-2019 to Q4-2021. A significant increase in Pharmacy interventions/clarifications was recorded. Additionally, a significant increase in incidents reported with no-harm coupled with a significant reduction in incidences of serious events from 2019 to 2020. Finally, no-harm events were significantly reduced from 2020 to 2021.

Discussion

The Pharmacy's study analyzed every medication incident documented from 2019 to 2021. 99.7% of reported incidents were classified as no-harm (near misses). There was an exponential decrease from Q1-2020 to Q1-202. A significant increase in incidents fell in the category of (near misses) with no-harm and a significant reduction in serious events. Pharmacy interventions/clarifications saw a massive increase and impact from Q3-2018 to Q2-2019, compared to the same period in 2018. By preventing medical incidents, benchmarking, and analyzing incidents and the reporting system, the use of information technology could dramatically reduce the rate of drug incidents.

Conclusion

This study found that benchmarking medication incidents is valuable, as it can help identify areas where improvements can be made, implement strategies to improve safety, and track progress over time. The benchmark was recommended to be below 100 incidents for every 10,000 prescriptions/orders processed, and for E-I categories, below one incident for every 10,000 prescriptions/orders processed. This will help develop a worldwide standard with an absolved culture with non-punitive consequences.

A national survey of knowledge, attitude, practice, and barriers towards pharmacovigilance and adverse drug reaction reporting among hospital pharmacy practitioners in the United Arab Emirates

BACKGROUND

Pharmacovigilance (PV) is an essential component of patient safety and pharmacists are expected to be aware of the PV processes and willing to report ADRs. This study assessed the hospital pharmacists' knowledge, attitude, and practice toward PV, barriers faced by them in ADR reporting, and factors influencing ADR reporting.

METHOD

A cross-sectional nationwide questionnaire survey was conducted among randomly chosen hospital pharmacists across UAE from March to July 2022. The filled questionnaires were assessed both descriptively [median (IQR scores), maximum 5 for Likert type and 1 for knowledge questions] and inferentially using the Mann-Whitney U test (for dichotomous variables) and the Kruskal-Wallis test (for variables with more than two responses) at alpha value = 0.05. Post hoc analyses and correlations were performed wherever applicable.

RESULTS

Of the 342 respondents, the majority were knowledgeable about the concepts of PV (93.3%; n = 319) and ADRs (86.8%; n = 297). The overall median (IQR) knowledge score was 5 (3-7)/9. Knowledge levels within 'qualification groups' varied significantly (p-value < 0.001) and participants 'between 10 and 14 years of experience' had more knowledge than those 'with < 5 years of experience' (p-value < 0.001, Bonferroni test). The overall median (IQR) attitude score was 22 (20-24)/30. Most respondents (90.6%; n = 311) were willing to spare time to review patients' ADR reports. The overall median (IQR) practice score was 17.5 (11-21)/24. Although 71.1% (n = 243) noticed ADRs during the previous year, only 53.2% (n = 182) reported an ADR, the reasons for underreporting being mainly due to a lack of proper training [median IQR score 4(4-5)/5]. The 'clinical pharmacists' engaged themselves more in pharmacovigilance than 'pharmacists' (p-value =  < 0.001), and 'inpatient pharmacists' reported more ADRs than 'pharmacists' (p-value = 0.018); Bonferroni test. The overall median (IQR) barrier score was 26 (23-29)/40 and the common barrier was 'lack of awareness about the national ADR reporting system 4 (4-5)'. The pharmacists in this study suggested incentives for reporting ADRs (69.3%; n = 237).

CONCLUSION

The authors concluded professional training courses for practicing pharmacists and educational curriculums related to PV and ADR reporting processes are to be considered for future pharmacists in order to inculcate ADR reporting culture and practices.

Incidence and Economic Burden of Adverse Drug Reactions in Hospitalization: A Prospective Study in Korea

BACKGROUND

Adverse drug reactions (ADRs) are escalating, and their socioeconomic burden is increasing. However, large-scale prospective studies investigating ADRs during hospitalization are rare in Korea. We prospectively investigated the incidence, characteristics, and economic burden of ADRs in hospitalized patients based on electronic medical records (EMRs).

METHODS

Among patients admitted to three hospitals from October 2016 to October 2017, 5,000 patients were randomly selected and prospectively observed during hospitalization. Research nurses monitored and detected patients who had symptoms, signs, or laboratory findings suspicious for ADRs using an EMR-based detection protocol. Next, allergy and ADR specialists reviewed the medical records to determine the relationship between adverse reactions and drugs. Cases in which a causal relationship was certain, probable/likely, or possible were included in the ADR cases. Clinically meaningful ADR cases or those leading to prolonged hospitalization were defined as significant ADRs.

RESULTS

ADRs occurred in 510 (10.2%) patients. The mean length of hospital stay was approximately 5 days longer in patients with ADRs. Opioids accounted for the highest percentage of total ADRs. Significant ADRs were observed in 148 (3.0%) patients. Antibiotics accounted for the highest percentage of significant ADRs. Drug hypersensitivity reactions (DHRs) occurred in 88 (1.8%) patients. Antibiotics accounted for the highest percentage of DHRs. The average medical expenses for one day of hospitalization per patient were highest in significant ADRs, followed by non-significant ADRs, and non-ADRs.

CONCLUSION

ADRs in hospitalized patients are an important clinical issue, resulting in a substantial socioeconomic burden. EMR-based strategy could be a useful tool for ADR monitoring and early detection.

Adverse drug event detection using natural language processing: A scoping review of supervised learning methods

To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing (NLP), a computerized approach to analyze text data, has shown promising results for the purpose of ADE detection in the context of pharmacovigilance. However, a detailed qualitative assessment and critical appraisal of NLP methods for ADE detection in the context of ADE monitoring in hospitals is lacking. Therefore, we have conducted a scoping review to close this knowledge gap, and to provide directions for future research and practice. We included articles where NLP was applied to detect ADEs in clinical narratives within electronic health records of inpatients. Quantitative and qualitative data items relating to NLP methods were extracted and critically appraised. Out of 1,065 articles screened for eligibility, 29 articles met the inclusion criteria. Most frequent tasks included named entity recognition (n = 17; 58.6%) and relation extraction/classification (n = 15; 51.7%). Clinical involvement was reported in nine studies (31%). Multiple NLP modelling approaches seem suitable, with Long Short Term Memory and Conditional Random Field methods most commonly used. Although reported overall performance of the systems was high, it provides an inflated impression given a steep drop in performance when predicting the ADE entity or ADE relation class. When annotating corpora, treating an ADE as a relation between a drug and non-drug entity seems the best practice. Future research should focus on semi-automated methods to reduce the manual annotation effort, and examine implementation of the NLP methods in practice.

Allopurinol-induced Stevens-Johnson syndrome and toxic epidermal necrolysis: Signal detection and preventability from Vietnam National pharmacovigilance database

WHAT IS KNOWN AND OBJECTIVE

Allopurinol, the first-line medication for hyperuricemia is well-known for its association with severe cutaneous adverse reactions, especially Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). In the current study, we analysed the Vietnamese spontaneous reporting database to identify signals and preventability of allopurinol-induced SJS/TEN in Vietnam from 2010 to 2019.

METHODS

Signal generation was assessed using the case/non-case method. Reporting odds ratios (RORs) and 95% confidence intervals (95% CI) were calculated.

RESULTS

Among 72,822 spontaneous ADR reports submitted to the Vietnam National Drug Information and Adverse Drug Reaction Monitoring Centre, 392 reports were on SJS/TEN, of which, 65 cases (16.6%) were related to allopurinol. The signals of allopurinol-induced SJS/TEN in Vietnam started in 2014 (ROR of 3.531, 95% CI: 1.830-6.810) and annually increased until 2019 (ROR of 11.923, 95% CI: 8.508-16.710). The preventability assessment showed that no allopurinol-induced SJS/TEN case was definitely unpreventable. 61.6% of the SJS/TEN cases were avoidable because they were associated with inappropriate prescribing such as unapproved indications, too high initial dose and even rechallenging in patients with a history of allopurinol allergy.

WHAT IS NEW AND CONCLUSION

The signals of allopurinol-induced SJS/TEN in Vietnam started in 2014 and annually increased until 2019. Our first report specifically focusing on the ADR preventability of allopurinol showed that correction of medical errors relating to prescription could prevent more than 60% of SJS/TEN cases in Vietnamese allopurinol users. This is a feasible and practical solution, provided that there would be a systematic change in both healthcare systems and public awareness.

Prioritisation of Adverse Drug Events Leading to Hospital Admission and Occurring during Hospitalisation: A RAND Survey

(1) Adverse drug events (ADEs) are a common cause of emergency department visits and occur frequently during hospitalisation. Instruments that facilitate the detection of the most relevant ADEs could lead to a more targeted and efficient use of limited resources in research and practice. (2) We conducted two consensus processes based on the RAND/UCLA appropriateness method, in order to prioritise ADEs leading to hospital admission (panel 1) and occurring during hospital stay (panel 2) for inclusion in future ADE measurement instruments. In each panel, the experts were asked to assess the “overall importance” of each ADE on a four-point Likert scale (1 = not important to 4 = very important). ADEs with a median rating of ≥3 without disagreement were defined as “prioritised“. (3) The 13 experts in panel 1 prioritised 38 out of 65 ADEs, while the 12 experts in panel 2 prioritised 34 out of 63 ADEs. The highest rated events were acute kidney injury and hypoglycaemia (both panels), as well as Stevens–Johnson syndrome in panel 1 and rhabdomyolysis in panel 2. (4) The survey led to a set of ADEs for which there was consensus that they were of particular importance as presentations of acute medication-related harm, thereby providing a focus for further medication safety research and clinical practice.

Cost-effectiveness of central automated unit dose dispensing with barcode-assisted medication administration in a hospital setting

BACKGROUND

Central automated unit dose dispensing (cADD) with barcode-assisted medication administration (BCMA) has been shown to reduce medication administration errors (MAEs). Little is known about the cost-effectiveness of this intervention.

OBJECTIVE

To estimate the cost-effectiveness of cADD with BCMA compared to usual care.

METHODS

An economic evaluation was conducted alongside a prospective before-and-after effectiveness study in a Dutch university hospital. The primary effect measure was the difference between the rate of MAEs before and after implementation of cADD with BCMA, obtained by disguised observation in six clinical wards and subsequent extrapolation to the entire hospital. The cost-analysis was conducted from a hospital perspective with a 12-month incremental costing approach. The total costs covered the pharmaceutical service, nurse medication handling, wastage, and materials related to cADD. The primary outcome was the cost-effectiveness ratio expressed as costs per avoided MAE, obtained by dividing the annual incremental costs by the number of avoided MAEs. The secondary outcome was the cost-effectiveness ratio expressed as costs per avoided potentially harmful MAE (i.e. MAEs with the potential to cause harm).

RESULTS

The intervention was associated with an absolute MAE reduction of 4.5% and a reduction of 2.7% for potentially harmful MAEs. Based on 2,260,870 administered medications in the entire hospital annually, a total of 102,210 MAEs and 59,830 potentially harmful MAEs were estimated to be avoided. The intervention was associated with an increased incremental cost of €1,808,600 annually. The cost-effectiveness ratio was €17.69 per avoided MAE and €30.23 per avoided potentially harmful MAE.

CONCLUSIONS

The implementation of cADD with BCMA was associated with a reduced rate of medication errors, including harmful ones, at higher overall costs. The costs per avoided error are relatively low, and therefore, this intervention could be an important strategy to improve patient safety in hospitals.

Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events

Background

Adverse drug events (ADEs) can be prevented by deploying clinical decision support systems (CDSS) that directly assist physicians, via computerized order entry systems, and clinical pharmacists performing medication reviews as part of medical rounds. However, physicians using CDSS are known to be exposed to the alert-fatigue phenomenon. Our study aimed to assess the performance of PharmaCheck—a CDSS to help clinical pharmacists detect high-risk situations with the potential to lead to ADEs—and its impact on clinical pharmacists’ activities.

Methods

Twenty clinical rules, divided into four risk classes, were set for the daily screening of high-risk situations in the electronic health records of patients admitted to our General Internal Medicine Department. Alerts to clinical pharmacists encouraged them to telephone prescribers and suggest any necessary treatment adjustments. PharmaCheck’s performance was assessed using the intervention’s positive predictive value (PPV), which characterizes the proportion of interventions for each alert triggered. PharmaCheck’s impact was assessed by considering clinical pharmacists as a filter for ruling out futile alerts and by comparing the final clinical PPV with a pharmacist (the proportion of interventions that led to a change in the medical regimen) to the final clinical PPV without a pharmacist.

Results

Over 132 days, 447 alerts were triggered for 383 patients, leading to 90 interventions (overall intervention PPV = 20.1%). By risk class, intervention PPVs made up 26.9% (n = 65/242) of abnormal laboratory value alerts, 3.1% (4/127) of alerts for contraindicated medications or medications to be used with caution, 28.2% (20/71) of drug–drug interaction alerts, and 14.3% (1/7) of inadequate mode of administration alerts. Clinical PPVs reached 71.0% (64/90) when pharmacists filtered alerts and 14% (64/242) if they were not doing it.

Conclusion

PharmaCheck enabled clinical pharmacists to improve their traditional processes and broaden their coverage by focusing on 20 high-risk situations. Alert management by pharmacists seemed to be a more effective way of preventing risky situations and alert-fatigue than a model addressing alerts to physicians exclusively. Some fine-tuning could enhance PharmaCheck's performance by considering the information quality of triggers, the variability of clinical settings, and the fact that some prescription processes are already highly secured.

Beta-Blocker-Related Atrioventricular Conduction Disorders—A Single Tertiary Referral Center Experience

Background and Objectives: Drug-related bradyarrhythmia is a well-documented major adverse event among beta-blocker users and a potential cause for hospitalization or additional interventions. Whether beta-blocker use is associated with specific bradyarrhythmia presentations, and how this relates to other predisposing factors, is not well known. We aim to evaluate the association between beta-blocker use and the type of atrioventricular (AV) conduction disorder in patients with symptomatic bradycardia. Materials and Methods: We conducted a retrospective cohort study on 596 patients with a primary diagnosis of symptomatic bradyarrhythmia admitted to a single tertiary referral center. Of the cases analyzed, 253 patients were on beta-blocker treatment at presentation and 343 had no bradycardic treatment. We analyzed demographics, clinical and paraclinical parameters in relation to the identified AV conduction disorder. A multivariate regression analysis was performed to explore factors associated with beta-blocker use. Results: Of the 596 patients (mean age 73.9 ± 8.8 years, 49.2% male), 261 (43.8%) had a third-degree AV block, 92 (15.4%) had a second-degree AV block, 128 (21.5%) had slow atrial fibrillation, 93 (15.6%) had sick sinus syndrome and 21 (3.5%) had sinus bradycardia/sinus pauses. Beta-blocker use was associated with the female gender (p < 0.001), emergency admission (p < 0.001), dilated cardiomyopathy (p = 0.003), the lower left ventricular ejection fraction (p = 0.02), mitral stenosis (p = 0.009), chronic kidney disease (p = 0.02), higher potassium levels (p = 0.04) and QRS duration > 120 ms (p = 0.02). Slow atrial fibrillation (OR = 4.2, p < 0.001), sick sinus syndrome (OR = 2.8, p = 0.001) and sinus bradycardia/pauses (OR = 32.9, p < 0.001) were more likely to be associated with beta-blocker use compared to the most common presentation (third-degree AV block), after adjusting for other patient characteristics. Conclusions: Beta-blocker use is more likely to be associated with slow atrial fibrillation, sick sinus syndrome and sinus bradycardia/pauses, compared to a second- or third-degree AV block, after adjusting for other patient factors such as gender, admission type, ECG, comorbidities, cardiac function and lab testing.

An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events

Aims

We aim to seek expert opinion and gain consensus on the risks associated with a range of prescribing scenarios, preventable using e‐prescribing systems, to inform the development of a simulation tool to evaluate the risk and safety of e‐prescribing systems (ePRaSE).

Methods

We conducted a two‐round e‐Delphi survey where expert participants were asked to score pre‐designed prescribing scenarios using a five‐point Likert scale to ascertain the likelihood of occurrence of the prescribing event, likelihood of occurrence of harm and the severity of the harm.

Results

Twenty‐four experts consented to participate with 15 pand 13 participants completing rounds 1 and 2, respectively. Experts agreed on the level of risk associated with 136 out of 178 clinical scenarios with 131 scenarios categorised as high or extreme risk.

Conclusion

We identified 131 extreme or high‐risk prescribing scenarios that may be prevented using e‐prescribing clinical decision support. The prescribing scenarios represent a variety of categories, with drug–disease contraindications being the most frequent, representing 37 (27%) scenarios, and antimicrobial agents being the most common drug class, representing 28 (21%) of the scenarios. Our e‐Delphi study has achieved expert consensus on the risk associated with a range of clinical scenarios with most of the scenarios categorised as extreme or high risk. These prescribing scenarios represent the breadth of preventable prescribing error categories involving both basic and advanced clinical decision support. We will use the findings of this study to inform the development of the e‐prescribing risk and safety evaluation tool.

Adverse drug reaction management in hospital settings: review on practice variations, quality indicators and education focus

Purpose

Adverse drug reactions (ADRs) contribute significantly to healthcare burden. However, they are largely preventable through appropriate management processes. This narrative review aims to identify the quality indicators that should be considered for routine monitoring of processes within hospital ADR management systems. It also examines the potential reasons behind variation in ADR management practices amongst HCPs, and explores possible solutions, focusing on targeted education programmes, to improve both the quality and quantity indicators of ADR management processes.

Methods

A comprehensive literature review was conducted to explore relevant themes and topics concerning ADR management, quality indicators and educational interventions.

Results

Substantial variability exists in ADR management amongst healthcare professionals (HCPs) with regard to reporting rates, characteristics of ADRs reported, quality of assessment, completeness of reports and, most importantly, risk communication practices. These variable practices not only threaten patient safety but also undermine pharmacovigilance processes. To date, quality indicators to monitor ADR management practices within hospital settings remain ill-defined. Furthermore, evidence behind effective interventions, especially in the form of targeted education strategies, to improve the quality of ADR management remains limited.

Conclusions

The focus of ADR management in hospitals should be to promote patient safety through comprehensive assessment, risk communication and safe prescribing. There is a need to develop a system to define, measure and monitor the quality of ADR management. Educational strategies may help improve the quality of ADR management processes.

A Text Mining Protocol for Predicting Drug-Drug Interaction and Adverse Drug Reactions from PubMed Articles

Drug-drug interactions (DDIs) and adverse drug reactions (ADRs) occur during the pharmacotherapy of multiple comorbidities and in susceptible individuals. DDIs and ADRs limit the therapeutic outcomes in pharmacotherapy. DDIs and ADRs have significant impact on patients' life and health care cost. Hence, knowledge of DDI and ADRs is required for providing better clinical outcomes to patients. Various approaches are developed by the scientific community to document and report the occurrences of DDIs and ADRs through scientific publications. Due to the enormously increasing number of publications and the requirement of updated information on DDIs and ADRs, manual retrieval of data is time consuming and laborious. Various automated techniques are developed to get information on DDIs and ADRs. One such technique is text mining of DDIs and ADRs from published biomedical literature in PubMed. Here, we present a recently developed text mining protocol for predicting DDIs and ADRs from PubMed abstracts.

Prevalence, types and severity of medication errors associated with the use of automated medication use systems in ambulatory and institutionalized care settings: A systematic review protocol

The use of automated systems within the medication use process has significantly reduce the occurrence of medication errors and the associated clinical and financial burden. However, automated systems lull into a false sense of security and increase the risk of medication errors that are often associated with socio-technical interactions, automation bias, workarounds and overrides. The objective of the systematic review is to determine the prevalence, types and severity of medication errors that are associated the use of automated systems in ambulatory and institutionalized care settings. The search strategy will be guided by PRISMA framework. Selected databases and relevant gray literature were searched and screening was done independently by two researchers between 01 April and 29 June 2021. These covered all relevant articles published from the inception of the use of automation in the medication use process (2000) until 2020. De-duplication and screening of all studies were done independently by two researchers with a clear inclusion / exclusion criteria. Data extraction and synthesis are currently on going (started on 06 July 2021) and being conducted independently but the validity and completeness of the processes will be confirmed by the third researcher. The Cochrane Risk of Bias tool and the Hoy et al's quality assessment checklist will be used for the assessment of methodological bias while the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system will be used for the quality of evidence assessment. Detailed qualitative synthesis of key findings will be done with thematic and descriptive analyses. If the number and types of included studies permit, fixed or random effect model meta-analysis will be conducted based on the degree of homogeneity in the sampling frame used in the included studies. Heterogeneity will be assessed with I2 statistics and I2 > 50% will be considered a high statistical heterogeneity. The systematic review may provide new perspective especially from developing settings about the prevalence, types and severity of medication errors associated with the use of automated systems at all the stages of medication use process, and in all categories of patients. This may add to global knowledge in the research area. Systematic review registration: The systematic review was registered and published by PROSPERO (CRD42020212900).

Serious adverse drug reactions in sub-Saharan Africa in the era of antiretroviral treatment: A systematic review

We aimed to summarize and describe the burden of serious adverse drug reactions (ADRs) in sub-Saharan Africa (SSA) in the era of antiretroviral therapy. We searched Medline, CINAHL, Africa-Wide Information, Scopus, and Web of Science, without language restriction up to March 2021. We hand-searched reference lists, conference abstracts, and dissertation databases. We included studies reporting proportions of admissions attributed to ADRs, admissions prolonged by ADRs, or in-hospital deaths attributed to ADRs. Two reviewers independently screened the studies, reviewed the study quality using a previously published tool, and extracted the data. We tested for heterogeneity using I2 -statistics and summarized the study results using medians and interquartile ranges. Subgroup analyses summarized the results by study quality, setting, methodology, and population. From 1005 unique references identified, we included 15 studies. Median study quality was 7/10; heterogeneity was very high. Median [IQR] proportion of admissions attributed to ADRs was 4.8% [1.5% to 7.0%] (14 studies) and 6.4% [4.0% to 8.4%] in nine active surveillance studies in adults. Two pediatric studies reported the proportion of admissions prolonged by ADRs (0.29% and 0.99%). Three studies reported the proportion of in-hospital deaths attributed to ADRs (2.5%, 13%, and 16%). Antiretroviral and antituberculosis drugs were often implicated in serious ADRs. Evidence of the burden of serious ADRs in SSA is patchy and heterogeneous. A few high-quality studies suggest that the burden is considerable, and that it reflects the regional impact of the HIV pandemic. Further characterization of this burden is required, ideally in studies of standardized methodology.

Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review

Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key use cases in which artificial intelligence (AI) could be leveraged to reduce the frequency of ADEs. We focused on modern machine learning techniques and natural language processing. 78 articles were included in the scoping review. Studies were heterogeneous and applied various AI techniques covering a wide range of medications and ADEs. We identified several key use cases in which AI could contribute to reducing the frequency and consequences of ADEs, through prediction to prevent ADEs and early detection to mitigate the effects. Most studies (73 [94%] of 78) assessed technical algorithm performance, and few studies evaluated the use of AI in clinical settings. Most articles (58 [74%] of 78) were published within the past 5 years, highlighting an emerging area of study. Availability of new types of data, such as genetic information, and access to unstructured clinical notes might further advance the field.

Hospitalizations and deaths related to adverse drug events worldwide: Systematic review of studies with national coverage

PURPOSE

Adverse drug events are related to negative outcomes in healthcare, including hospitalization, increased duration of hospital stay and death. The aim of this study was to conduct a systematic review to evaluate hospitalizations and deaths related to adverse drug events worldwide, reported in studies with national coverage.

METHODS

The protocol was registered in PROSPERO (CRD42020157008). We performed a systematic search on Medline, Embase, CINAHL, LILACS, and the Cochrane Library (until March 2020) using pre-specified terms. We included published studies that reported data on hospitalizations and/or deaths related to adverse drug events from a national perspective and the use of secondary data as a source of information. Two reviewers independently extracted and synthesized data. The quality of the studies was assessed using an adapted version of the Joanna Briggs Institute critical appraisal checklist for prevalence studies. Narrative summaries of findings were undertaken.

RESULTS

Among 59,336 citations, 62 studies were included for data extraction and synthesis. Among these studies, 41 studies included the outcome of hospitalization, 16 included the death outcome, and five included both outcomes. Administrative databases regarding discharges and registries of vital statistics were the most common sources of information. The relative frequency of hospitalizations ranged from 0.03% to 7.3%, and from 9.7 to 383.0/100,000 population, whereas mortality rate ranged from 0.1 to 7.88/100,000 population.

CONCLUSION

Our study highlights information about adverse drug events using large administrative databases in a national scenario and provides an overview of databases and methods implemented to detect adverse drug events.

Drug-related deaths among inpatients: a meta-analysis

PURPOSE

To estimate the prevalence of drug-related deaths with regard to total hospital mortality and to explore the heterogeneity in its estimation through subgroup analysis, univariate and multivariate analysis.

METHODS

Two investigators independently searched the PubMed and Google Scholar databases with appropriate key terms to identify observational and randomised studies assessing drug-related problems. The prevalence of drug-related deaths was estimated using a double arcsine method. The heterogeneity was explored through subgroup and univariate analysis for the following study characteristics: study design, age group, study ward, study region, types of drug-related problems, study duration, sample size and study period. The study variables showing significant effects were further explored through a multivariable regression model. The percentage of preventable drug-related deaths was explored as a secondary objective.

RESULTS

Of the 480 full-text articles assessed, 23 studies satisfying the selection criteria were included. The mean percentage of drug-related deaths was 5.6% (95% CI: 3.8-7.6%; I² = 96%). The univariable analysis showed study design (regression coefficient: 4.31) and study wards (regression coefficient: - 6.37) as heterogeneity modifiers. In the multivariable model, only the study ward was considered a significant predictor of drug-related deaths (regression coefficient: - 5.78; p = 0.04). The mean percentage of preventable drug-related deaths was 45.2% (95% CI: 33.6-57.0%; I² = 60%).

CONCLUSION

Drug-related problems are an important cause of mortality. The variability in its estimation could be explained by admission wards.

Medication-related adverse events in health care-what have we learned? A narrative overview of the current knowledge

Purpose

Although medication-related adverse events (MRAEs) in health care are vastly studied, high heterogeneity in study results complicates the interpretations of the current situation. The main objective of this study was to form an up-to-date overview of the current knowledge of the prevalence, risk factors, and surveillance of MRAEs in health care.

Methods

Electronic databases (PubMed, MEDLINE, Web of Science, and Scopus) were searched with applicable search terms to collect information on medication-related adverse events. In order to obtain an up-to-date view of MRAEs, only studies published after 2000 were accepted.

Results

The prevalence rates of different MRAEs vary greatly between individual studies and meta-analyses. Study setting, patient population, and detection methods play an important role in determining detection rates, which should be regarded while interpreting the results. Medication-related adverse events are more common in elderly patients and patients with lowered liver or kidney function, polypharmacy, and a large number of additional comorbidities. However, the risk of MRAEs is also significantly increased by the use of high-risk medicines but also in certain care situations. Preventing MRAEs is important as it will decrease patient mortality and morbidity but also reduce costs and functional challenges related to them.

Conclusions

Medication-related adverse events are highly common and have both immediate and long-term effects to patients and healthcare systems worldwide. Conclusive solutions for prevention of all medication-related harm are impossible to create. In the future, however, the development of efficient real-time detection methods can provide significant improvements for event prevention and forecasting.

Differences in information accessed in a pharmacologic knowledge base using a conversational agent vs traditional search methods

INTRODUCTION

Clinicians rely on pharmacologic knowledge bases to answer medication questions and avoid potential adverse drug events. In late 2018, an artificial intelligence-based conversational agent, Watson Assistant (WA), was made available to online subscribers to the pharmacologic knowledge base, Micromedex®. WA allows users to ask medication-related questions in natural language. This study evaluated search method-dependent differences in the frequency of information accessed by traditional methods (keyword search and heading navigation) vs conversational agent search.

MATERIALS AND METHODS

We compared the proportion of information types accessed through the conversational agent to the proportion of analogous information types accessed by traditional methods during the first 6 months of 2020.

RESULTS

Addition of the conversational agent allowed early adopters to access 22 different information types contained in the 'quick answers' portion of the knowledge base. These information types were accessed 117,550 times with WA during the study period, compared to 33,649,651 times using traditional search methods. The distribution across information types differed by method employed (c² test, P < .0001). Single drug/dosing, FDA/non-FDA uses, adverse effects, and drug administration emerged as 4 of the top 5 information types accessed by either method. Intravenous compatibility was accessed more frequently using the conversational agent (7.7% vs. 0.6% for traditional methods), whereas dose adjustments were accessed more frequently via traditional methods (4.8% vs. 1.4% for WA).

CONCLUSION

In a widely used pharmacologic knowledge base, information accessed through conversational agents versus traditional methods differed. User-centered studies are needed to understand these differences.

Medication safety knowledge, attitude, and practice among hospital pharmacists in tertiary care hospitals in Saudi Arabia: a multi-center study

BACKGROUND

Pharmacovigilance (PV) demarcates all actions involving the detection and prevention of adverse drug reactions (ADR) for marketed drugs. However, ADRs are considerably underreported worldwide and continue to be a major concern to health care systems. This study aims to assess the knowledge, attitude, and perception of hospital pharmacists regarding medication safety concerning PV and ADRs across multiple tertiary care centers around Saudi Arabia.

METHODS

This cross-sectional study was conducted between July 2019 and January 2020. Pharmacists working in the tertiary care centers of Riyadh City, Saudi Arabia were asked to participate in the study. A self-administered questionnaire was used to conduct this study, it consisted of: 63 questions out of which 19 questions were knowledge-based, 15 were attitude-based, and 29 were practice-based questions.

RESULTS

A total of 350 pharmacists were distributed and 289 agreed to participate, giving a response rate of 82.6%. Most pharmacists were aware of the concept of VP and its functions (96.5%) and (87.2%), respectively. Moreover, 90% said that ADR can be preventable and non-preventable. However, the findings revealed inadequate knowledge about the overall PV field, where the majority of the pharmacists failed to correctly answer questions related to independent ADRs treatment, Augmented drug reaction, the international location of ADR, and the World Health Organization "online database" for reporting ADRs. Moreover, incomplete and/or wrong answers were recorded for questions that included single or multiple correct answers. Regarding the participants" attitude, 96.9% were interested in ADR reporting, agreeing that ADR is important to enable safe drug usage. Although a general positive attitude was recorded, pharmacists have stated that the three main barriers that hinder reporting ADRs are: unavailability of information about ADRs, lack of awareness about the need to report ADRs, and lack of time. Concerning practice, 69.2% said they received training in ADRs reporting, and 70% have reported ADRs more than once a week.

CONCLUSION

Surveyed pharmacists from Riyadh hospitals showed narrow knowledge of the PV field. However, a positive attitude and satisfactory practice was observed among pharmacists. These findings warrant the need for educational programs and an encouraging environment for ADR reporting to increase ADR reporting rates and support PV activities in Saudi Arabia.

Optimizing Clinical Monitoring Tools to Enhance Patient Review by Pharmacists

BACKGROUND

The Clinical Monitoring List (CML) is a real-time scoring system and intervention tool used by Mayo Clinic pharmacists caring for hospitalized patients.

OBJECTIVE

The study aimed to describe the iterative development and implementation of pharmacist clinical monitoring tools within the electronic health record at a multicampus health system enterprise.

METHODS

Between October 2018 and January 2019, pharmacists across the enterprise were surveyed to determine opportunities and gaps in CML functionality. Responses were received from 39% (n = 162) of actively staffing inpatient pharmacists. Survey responses identified three main gaps in CML functionality: (1) the desire for automated checklists of tasks, (2) additional rule logic closely aligning with clinical practice guidelines, and (3) the ability to dismiss and defer rules. The failure mode and effect analysis were used to assess risk areas within the CML. To address identified gaps, two A/B testing pilots were undertaken. The first pilot analyzed the effect of updated CML rule logic on pharmacist satisfaction in the domains of automated checklists and guideline alignment. The second pilot assessed the utility of a Clinical Monitoring Navigator (CMN) functioning in conjunction with the CML to display rules with selections to dismiss or defer rules until a user-specified date. The CMN is a workspace to guide clinical end user workflows; permitting the review and actions to be completed within one screen using EHR functionality.

RESULTS

A total of 27 pharmacists across a broad range of practice specialties were selected for two separate two-week pilot tests. Upon pilot completion, participants were surveyed to assess the effect of updates on performance gaps.

CONCLUSION

Findings from the enterprise-wide survey and A/B pilot tests were used to inform final build decisions and planned enterprise-wide updated CML and CMN launch. This project serves as an example of the utility of end-user feedback and pilot testing to inform project decisions, optimize usability, and streamline build activities.

Incidence and Predictors of Severe Adverse Drug Reaction Among Patients on Antiretroviral Therapy in Tigray, Ethiopia: A Retrospective Cohort Study

Background

The aim of the present study was to assess the incidence and predictors of severe adverse drug reactions among patients on antiretroviral therapy (ART) in Tigray, North Ethiopia.

Methods

We employed four years retrospective cohort study using a structured data extraction sheet. The study populations were HIV patients on ART follow-up from January 2017 to February 2020 in the study area. Severe adverse drug reaction (ADR) was an outcome variable and defined as having any one of the complaints related to ARV drug reaction due to regimen change, discontinuation, and/or in-patient care. Data were collected using a structured data extraction sheet. A Cox proportional hazard regression model was used to determine the relationship between the predictors and the outcome variable. The mean survival time of the cohort was estimated using the Kaplan-Meier method.

Results

The incidence rate of ADRs was 3.6 (95%CI: 2.9-4.35) per 100-person years. HIV patients with no formal education (adjusted hazard ratio=1.58, 95%CI: 1.03-2.41), with experience of regimen change (adjusted hazard ratio=1.59, 95%CI: 1.12-2.91), who ever took other medication (adjusted hazard ratio=1.49, 95%CI: 1.05-2.15) and with lower body mass index (adjusted hazard ratio=3.24, 95%CI: 1.18-4.91) were more likely to develop severe adverse drug reaction.

Conclusion

ADRs were diagnosed an inconsiderable number of HIV patients on ART and factors were patient and drug-related. To minimize it, special attention is sought for patients with no formal education, previous regime change, whoever took other medication, and who have lower body mass index levels.

Suspected adverse drug reactions (ADRs) trends in older Italian patients: an analysis from the National Pharmacovigilance Network

BACKGROUND

The clinical management of older populations is a social and clinical challenge. These subjects are more vulnerable to adverse drug reactions (ADRs) due to multi morbidity, polypharmacy, and physio-pathological changes.

METHODS

We performed a study using data from the National Network of Pharmacovigilance of Italy available from 2001 to 2012, which include all spontaneous reports of suspected ADRs.

RESULTS

Our study showed that 29,036 reports of suspected ADRs were recorded in 2012. Those for patients aged ≥ 65 years were 11,426 that correspond to a reporting rate of 923.6 reports per million inhabitants. On the contrary, the reporting rate for total population was of 489 reports per million inhabitants. The evaluation of level of severity showed that 37% of reports of suspected ADRs in patients aged ≥ 65 years were serious compared to 30% in the general population. Furthermore, 27% of reports recorded for older patients showed that they required more hospitalization or long-term care in comparison with the 21% for the general population, with a relevant impact on National Health Service costs.

CONCLUSION

These data suggest the need to optimize the clinical strategy for older patients due to the multiple factors that increase the susceptibility to ADRs. There is a high need to potentiate clinical trials on older patients to adopt new diagnostic-therapeutic pathways in real life.

Prevalence of adverse drug reactions in the primary care setting: A systematic review and meta-analysis

BACKGROUND

Adverse drug reactions (ADRs) represent a major cause of iatrogenic morbidity and mortality in patient care. While a substantial body of work has been undertaken to characterise ADRs in the hospital setting, the overall burden of ADRs in the primary care remains unclear.

OBJECTIVES

To investigate the prevalence of ADRs in the primary care setting and factors affecting the heterogeneity of the estimates.

METHODS

Studies were identified through searching of Medline, Embase, CINAHL and IPA databases. We included observational studies that reported information on the prevalence of ADRs in patients receiving primary care. Disease and treatment specific studies were excluded. Quality of the included studies were assessed using Smyth ADRs adapted scale. A random-effects model was used to calculate the pooled estimate. Potential source of heterogeneity, including age groups, ADRs definitions, ADRs detection methods, study setting, quality of the studies, and sample size, were investigated using sub-group analysis and meta-regression.

RESULTS

Thirty-three studies with a total study population of 1,568,164 individuals were included. The pooled prevalence of ADRs in the primary care setting was 8.32% (95% CI, 7.82, 8.83). The percentage of preventable ADRs ranged from 12.35-37.96%, with the pooled estimate of 22.96% (95% CI, 7.82, 38.09). Cardiovascular system drugs were the most commonly implicated medication class. Methods of ADRs detection, age group, setting, and sample size contributed significantly to the heterogeneity of the estimates.

CONCLUSION

ADRs constitute a significant health problem in the primary care setting. Further research should focus on examining whether ADRs affect subsequent clinical outcomes, particularly in high-risk therapeutic areas. This information may better inform strategies to reduce the burden of ADRs in the primary care setting.

What I have learnt from helping thousands of people taper off antidepressants and other psychotropic medications

Although psychiatric drug withdrawal syndromes have been recognized since the 1950s - recent studies confirm antidepressant withdrawal syndrome incidence upwards of 40% - medical information about how to safely go off the drugs has been lacking. To fill this gap, over the last 25 years, patients have developed a robust Internet-based subculture of peer support for tapering off psychiatric drugs and recovering from withdrawal syndrome. This account from the founder of such an online community covers lessons learned from thousands of patients regarding common experiences with medical providers, identification of adverse drug reactions, risk factors for withdrawal, tapering techniques, withdrawal symptoms, protracted withdrawal syndrome, and strategies to cope with symptoms, in the context of the existing scientific literature.

Did we do everything we could have? Nurses' contributions to medicines optimization: A mixed-methods study

AIM

To explore UK professionals' interpretations of medicines optimization and expansion of nurses' roles.

DESIGN

This mixed-methods study sought professionals' views on nurses' involvement, competency and engagement in monitoring patients for adverse effects of medicines, monitoring adherence, prescribing and patient education.

METHOD

An online survey and interviews were undertaken with nurses, doctors and pharmacists in Wales and England, May 2018 to July 2019.

RESULTS

In all, 220 nurses, 17 doctors and 62 pharmacists responded to the online survey, and 24 professionals were interviewed. Nurses were divided over extending their roles, with 123/220 (55.9%) wishing to extend roles in monitoring patients for possible adverse drug reactions (ADRs), 111/220 (50.5%) in adherence monitoring, 121/220 (55.0%) in prescribing and 122/220 (55.4%) in patient education. The best-qualified nurses were the most willing to increase involvement in monitoring patients for ADRs (aOR 13.00, 1.56-108.01). Interviews revealed that both nurses and doctors assumed the other profession was undertaking this monitoring. Respondents agreed that increasing nurses' involvement in medicines optimization would improve patient care, but expressed reservations about nurses' competencies. Collaboration between nurses and doctors was suboptimal (rated 7/10 at best) and between nurses and pharmacists even more so (6/10 at best).

CONCLUSION

Juxtaposition of datasets identified problems with medicines optimization: although most respondents agreed that increasing nurses' involvement would positively impact practice, their educational preparation was a barrier. Only ~50% of nurses were willing to expand their roles to fill the hiatus in care identified and ensure that at least one profession was taking responsibility for ADR monitoring.

IMPACT

To improve multiprofessional team working and promote patient safety, nurse leaders should ensure patients are monitored for possible ADRs by at least one profession. Initiatives expanding nurses' roles in medicines optimization and prescribing might be best targeted towards the more educated nurses, who have multidisciplinary support.

Scoping review of COVID-19-related systematic reviews and meta-analyses: can we really have confidence in their results?

Aim

The aim of this study was to systematically appraise the quality of a sample of COVID-19-related systematic reviews (SRs) and discuss internal validity threats affecting the COVID-19 body of evidence.

Design

We conducted a scoping review of the literature. SRs with or without meta-analysis (MA) that evaluated clinical data, outcomes or treatments for patients with COVID-19 were included.

Main outcome measures

We extracted quality characteristics guided by A Measurement Tool to Assess Systematic Reviews-2 to calculate a qualitative score. Complementary evaluation of the most prominent published limitations affecting the COVID-19 body of evidence was performed.

Results

A total of 63 SRs were included. The majority were judged as a critically low methodological quality. Most of the studies were not guided by a pre-established protocol (39, 62%). More than half (39, 62%) failed to address risk of bias when interpreting their results. A comprehensive literature search strategy was reported in most SRs (54, 86%). Appropriate use of statistical methods was evident in nearly all SRs with MAs (39, 95%). Only 16 (33%) studies recognised heterogeneity in the definition of severe COVID-19 as a limitation of the study, and 15 (24%) recognised repeated patient populations as a limitation.

Conclusion

The methodological and reporting quality of current COVID-19 SR is far from optimal. In addition, most of the current SRs fail to address relevant threats to their internal validity, including repeated patients and heterogeneity in the definition of severe COVID-19. Adherence to proper study design and peer-review practices must remain to mitigate current limitations.

Root causes of adverse drug events in hospitals and artificial intelligence capabilities for prevention

AIMS

To identify and prioritize the root causes of adverse drug events (ADEs) in hospitals and to assess the ability of artificial intelligence (AI) capabilities to prevent ADEs.

DESIGN

A mixed method design was used.

METHODS

A cross-sectional study for hospitals in Spain was carried out between February and April 2019 to identify and prioritize the root causes of ADEs. A nominal group technique was also used to assess the ability of AI capabilities to prevent ADEs.

RESULTS

The main root cause of ADEs was a lack of adherence to safety protocols (64.8%), followed by identification errors (57.4%), and fragile and polymedicated patients (44.4%). An analysis of the AI capabilities to prevent the root causes of ADEs showed that identification and reading are two potentially useful capabilities.

CONCLUSION

Identification error is one of the main root causes of drug adverse events and AI capabilities could potentially prevent drug adverse events.

IMPACT

This study highlights the role of AI capabilities in safely identifying both patients and drugs, which is a crucial part of the medication administration process, and how this can prevent ADEs in hospitals.

Preventable medication harm across health care settings: a systematic review and meta-analysis

BACKGROUND

Mitigating or reducing the risk of medication harm is a global policy priority. But evidence reflecting preventable medication harm in medical care and the factors that derive this harm remain unknown. Therefore, we aimed to quantify the prevalence, severity and type of preventable medication harm across medical care settings.

METHODS

We performed a systematic review and meta-analysis of observational studies to compare the prevalence of preventable medication harm. Searches were carried out in Medline, Cochrane library, CINAHL, Embase and PsycINFO from 2000 to 27 January 2020. Data extraction and critical appraisal was undertaken by two independent reviewers. Random-effects meta-analysis was employed followed by univariable and multivariable meta-regression. Heterogeneity was quantified using the I² statistic, and publication bias was evaluated.

PROSPERO

CRD42020164156.

RESULTS

Of the 7780 articles, 81 studies involving 285,687 patients were included. The pooled prevalence for preventable medication harm was 3% (95% confidence interval (CI) 2 to 4%, I² = 99%) and for overall medication harm was 9% (95% CI 7 to 11%, I² = 99.5%) of all patient incidence records. The highest rates of preventable medication harm were seen in elderly patient care settings (11%, 95% 7 to 15%, n = 7), intensive care (7%, 4 to 12%, n = 6), highly specialised or surgical care (6%, 3 to 11%, n = 13) and emergency medicine (5%, 2 to 12%, n = 12). The proportion of mild preventable medication harm was 39% (28 to 51%, n = 20, I² = 96.4%), moderate preventable harm 40% (31 to 49%, n = 22, I² = 93.6%) and clinically severe or life-threatening preventable harm 26% (15 to 37%, n = 28, I² = 97%). The source of the highest prevalence rates of preventable harm were at the prescribing (58%, 42 to 73%, n = 9, I² = 94%) and monitoring (47%, 21 to 73%, n = 8, I² = 99%) stages of medication use. Preventable harm was greatest in medicines affecting the 'central nervous system' and 'cardiovascular system'.

CONCLUSIONS

This is the largest meta-analysis to assess preventable medication harm. We conclude that around one in 30 patients are exposed to preventable medication harm in medical care, and more than a quarter of this harm is considered severe or life-threatening. Our results support the World Health Organisation's push for the detection and mitigation of medication-related harm as being a top priority, whilst highlighting other key potential targets for remedial intervention that should be a priority focus for future research.

Adverse Drug Events and Contributing Factors Among Hospitalized Adult Patients at Jimma Medical Center, Southwest Ethiopia: A Prospective Observational Study

Background

Adverse drug events (ADEs) are common complications of clinical care resulting in significant morbidity, mortality, and high clinical expenditure. Population-level estimates of inpatient ADEs are limited in Ethiopia.

Objective

This study aimed to assess the incidence, contributing factors, severity, and preventability of ADEs among hospitalized adult patients at Jimma Medical Center, Ethiopia.

Methods

A prospective observational study design was conducted among hospitalized adult patients at tertiary hospital in Ethiopia. A structured data collection tool was prepared from relevant literatures for data collection. Data were analyzed using statistical software. Logistic regression was performed to identify factors contributing to ADE occurrence. P values < 0.05 were considered statistically significant.

Results

A total of 319 patients were included with follow-up period of 5667 person-days. About 50.5% were women. The mean (SD) age of patients was 43 (17.6) years. One hundred sixteen ADEs were identified with the incidence of 36.4 (95% CI, 30.1-43.6) per 100 admissions and 20.5 (95% CI, 16.9-24.6) per 1000 person-days. Antituberculosis agents (adjusted odds ratio [aOR] = 2.52; 95% CI, 1.06-5.98; P = 0.036), disease of the circulatory system (aOR = 2.67; 95% CI, 1.46-4.89; P = 0.001), disease of the digestive system (aOR = 2.84; 95% CI, 1.45-5.57; P = 0.002), being on medication during admission (aOR = 3.09; 95% CI, 1.77-5.41; P < 0.001), and hospital stay more than 2 weeks (aOR = 3.93; 95% CI, 1.39-11.12; P = 0.010) were independent predictors of ADE occurrence.

Conclusions

One in every 4 patients admitted to the hospital experienced ADEs during their hospital stay. Most ADEs were moderate in severity. About two-thirds of the ADEs identified were deemed probably or definitely preventable. Therefore, it is high time to reinforce large-scale efforts to redesign safer, higher quality health care systems to adequately tackle the problem.

Cohort study on adverse drug reactions in adults admitted to the medical wards of a tertiary hospital in Nigeria: Prevalence, incidence, risk factors and fatality

AIMS

Intensive monitoring of medical patients for adverse drug reactions (ADRs) to assess prevalence, incidence, risk factors and fatality of ADRs leading to hospital admission or occurring in the hospital.

METHODS

Prospective cohort study on 1280 adult patients admitted to the medical wards of a tertiary institution over 12 months. Patients were assessed for ADRs during and throughout admission; causality and preventability of ADRs were assessed.

RESULTS

Sixty-seven (5.2%) patients had ADRs, 51 (3.9%) caused hospitalisation while 17(1.3%) occurred during hospitalisation, and 42 (62.7%) of total ADRs were preventable. Nonsteroidal anti-inflammatory drugs, 14 (20.3%), antidiabetics, 12 (17.4%) and antibacterial, 11 (15.8%) were the most implicated drug classes. Gastrointestinal tract (37%), central nervous system (30.2%), and skin (24.7%) were the most affected organ/systems, while upper gastrointestinal bleeding and hypoglycaemia were the most observed ADRs. ADRs led to deaths in 7 (10.4%) patients, with an overall case fatality rate of 0.5%. The highest number of deaths were among patients with Stevens-Johnson syndrome 2/7 (28.6%) and hepatotoxicity 2/7 (28.6%). Risk factors, adjusted odds ratio (AOR [95% confidence interval, CI]) for ADRs leading to hospitalisation was male sex 3.11 (1.11, 8.73) while for ADRs during hospitalisation were number of drugs used before admission (AOR [95% CI] = 6.67 [1.16, 38.47]) and comorbidities (AOR [95% CI] = 3.0 [1.13, 8.01]). Patients admitted with ADRs had prolonged hospital stay (AOR [95% CI] = 3.37 [1.11, 8.71]).

CONCLUSION

Preventable ADRs are common and important causes of hospitalisation and inpatients' morbidity and mortality among medical patients in Nigeria. Upper gastrointestinal bleeding and hypoglycaemia, resulting from nonsteroidal anti-inflammatory drugs and antidiabetic drugs were the most observed ADRs.

Engineering the Microbiome to Prevent Adverse Events: Challenges and Opportunities

In the past decade of microbiome research, we have learned about numerous adverse interactions between the microbiome and medical interventions such as drugs, radiation, and surgery. What if we could alter our microbiomes to prevent these events? In this review, we discuss potential routes to mitigate microbiome adverse events, including applications from the emerging field of microbiome engineering. We highlight cases where the microbiome acts directly on a treatment, such as via differential drug metabolism, and cases where a treatment directly harms the microbiome, such as in radiation therapy. Understanding and preventing microbiome adverse events is a difficult challenge that will require a data-driven approach involving causal statistics, multiomics techniques, and a personalized means of mitigating adverse events. We propose research considerations to encourage productive work in preventing microbiome adverse events, and we highlight the many challenges and opportunities that await.

Potentially Inappropriate Prescribing and Potential Prescribing Omissions in 82,935 Older Hospitalised Adults: Association with Hospital Readmission and Mortality Within Six Months

Polypharmacy with “potentially inappropriate medications” (PIMs) and “potential prescribing omissions” (PPOs) are frequent among those 65 and older. We assessed PIMs and PPOs in a retrospective study of 82,935 patients ≥ 65 during their first admission in the period March 2013 through February 2018 to the four acute-care Calgary hospitals. We used the American Geriatric Society (AGS) and STOPP/START criteria to assess PIMs and PPOs. We computed odds ratios (ORs) for key outcomes of concern to patients, their families, and physicians, namely readmission and/or mortality within six months of discharge, and controlled for age, sex, numbers of medications, PIMs, and PPOs. For readmission, the adjusted OR for number of medications was 1.09 (1.09–1.09), for AGS PIMs 1.14 (1.13–1.14), for STOPP PIMs 1.15 (1.14–1.15), for START PPOs 1.04 (1.02–1.06), and for START PPOs correctly prescribed 1.16 (1.14–1.17). For mortality within 6 months of discharge, the adjusted OR for the number of medications was 1.02 (1.01–1.02), for STOPP PIMs 1.07 (1.06–1.08), for AGS PIMs 1.11 (1.10–1.12), for START PPOs 1.31 (1.27–1.34), and for START PPOs correctly prescribed 0.97 (0.94–0.99). Algorithm rule mining identified an 8.772 higher likelihood of mortality with the combination of STOPP medications of duplicate drugs from the same class, neuroleptics, and strong opioids compared to a random relationship, and a 2.358 higher likelihood of readmission for this same set of medications. Detailed discussions between patients, physicians, and pharmacists are needed to improve these outcomes.

Prevalence and Nature of Medication Errors and Preventable Adverse Drug Events in Paediatric and Neonatal Intensive Care Settings: A Systematic Review

INTRODUCTION

Children admitted to paediatric and neonatal intensive care units may be at high risk from medication errors and preventable adverse drug events.

OBJECTIVE

The objective of this systematic review was to review empirical studies examining the prevalence and nature of medication errors and preventable adverse drug events in paediatric and neonatal intensive care units.

DATA SOURCES

Seven electronic databases were searched between January 2000 and March 2019.

STUDY SELECTION

Quantitative studies that examined medication errors/preventable adverse drug events using direct observation, medication chart review, or a mixture of methods in children ≤ 18 years of age admitted to paediatric or neonatal intensive care units were included.

DATA EXTRACTION

Data on study design, detection method used, rates and types of medication errors/preventable adverse drug events, and medication classes involved were extracted.

RESULTS

Thirty-five unique studies were identified for inclusion. In paediatric intensive care units, the median rate of medication errors was 14.6 per 100 medication orders (interquartile range 5.7-48.8%, n = 3) and between 6.4 and 9.1 per 1000 patient-days (n = 2). In neonatal intensive care units, medication error rates ranged from 4 to 35.1 per 1000 patient-days (n = 2) and from 5.5 to 77.9 per 100 medication orders (n = 2). In both settings, prescribing and medication administration errors were found to be the most common medication errors, with dosing errors the most frequently reported error subtype. Preventable adverse drug event rates were reported in three paediatric intensive care unit studies as 2.3 per 100 patients (n = 1) and 21-29 per 1000 patient-days (n = 2). In neonatal intensive care units, preventable adverse drug event rates from three studies were 0.86 per 1000 doses (n = 1) and 0.47-14.38 per 1000 patient-days (n = 2). Anti-infective agents were commonly involved with medication errors/preventable adverse drug events in both settings.

CONCLUSIONS

Medication errors occur frequently in critically ill children admitted to paediatric and neonatal intensive care units and may lead to patient harm. Important targets such as dosing errors and anti-infective medications were identified to guide the development of remedial interventions.

The quality of systematic reviews/meta-analyses published in the field of bariatrics: A cross-sectional systematic survey using AMSTAR 2 and ROBIS

High-quality systematic reviews (SR) and meta-analyses (MA) are considered to be reliable sources of information. This study aims to assess the quality of studies published as SR or MA in the field of bariatrics in 2016 and 2017. We identified SR and MA in the field of bariatrics by searching electronic databases (MEDLINE, Embase, and Cochrane Database of Systematic Reviews). Eligible studies were those identified as SR/MA in the title/abstract, which aimed to assess any outcome in patients with morbid obesity undergoing or scheduled to undergo bariatric surgery. Two authors independently reviewed all titles and abstracts, assessed full texts of potentially eligible studies, and assessed the quality of included studies. Any discrepancies were resolved by the third reviewer. We evaluated the quality and risk of bias of each SR/MA using AMSTAR 2 checklist and ROBIS tool, respectively. Seventy-eight of 4236 references met inclusion criteria and were assessed for their quality/risk of bias. The methodological quality of 99% of all papers was classified as "critically low." A total of 6% of the studies were at low risk of bias, and 78% were assessed as being at high risk of bias. The methodological quality of studies published in 2016 and 2017 as SR/MA is highly unsatisfactory.

Artificial intelligence-based conversational agent to support medication prescribing

Objective

This article describes the system architecture, training, initial use, and performance of Watson Assistant (WA), an artificial intelligence-based conversational agent, accessible within Micromedex^®.

Materials and methods

The number and frequency of intents (target of a user’s query) triggered in WA during its initial use were examined; intents triggered over 9 months were compared to the frequency of topics accessed via keyword search of Micromedex. Accuracy of WA intents assigned to 400 queries was compared to assignments by 2 independent subject matter experts (SMEs), with inter-rater reliability measured by Cohen’s kappa.

Results

In over 126 000 conversations with WA, intents most frequently triggered involved dosing (N = 30 239, 23.9%) and administration (N = 14 520, 11.5%). SMEs with substantial inter-rater agreement (kappa = 0.71) agreed with intent mapping in 247 of 400 queries (62%), including 16 queries related to content that WA and SMEs agreed was unavailable in WA. SMEs found 57 (14%) of 400 queries incorrectly mapped by WA; 112 (28%) queries unanswerable by WA included queries that were either ambiguous, contained unrecognized typographical errors, or addressed topics unavailable to WA. Of the queries answerable by WA (288), SMEs determined 231 (80%) were correctly linked to an intent.

Discussion

A conversational agent successfully linked most queries to intents in Micromedex. Ongoing system training seeks to widen the scope of WA and improve matching capabilities.

Conclusion

WA enabled Micromedex users to obtain answers to many medication-related questions using natural language, with the conversational agent facilitating mapping to a broader distribution of topics than standard keyword searches.

The Risks and Outcomes Resulting From Medication Errors Reported in the Finnish Tertiary Care Units:: A Cross-Sectional Retrospective Register Study

Background: Hospital-acquired medication errors (MEs) are common in health care. Although voluntary reporting is criticized for not producing reliable estimates on ME frequency, it provides valuable knowledge on errors occurring in the medication process. Objective: The purpose of this study was to analyze and determine the risks and outcomes resulting from MEs related to the TOP15 medicines in the Finnish tertiary care units from July 2016 to July 2017. Methods: The data consisting of 1,447 ME reports was organized according to ATC classification, after which TOP15 medicines involved in the reports were selected. Inductive content analysis was performed to the reports. After this, the reports were categorized by ME outcome into five categories and further analyzed accordingly. Results: The most common ME outcome in the reports was "omitted medicine" (33.9%). More than a quarter (27.1%) of ME reports were estimated to cause moderate or severe risk to the patient. When compared with each other, none of the outcome groups were more susceptible to high-risk events (p = 0.71). Of the TOP15 medicines, only Norepinephrine had significantly higher risk of being involved in high-risk events (OR 2.43, 95%CI 1.35-4.61). Conclusion: Voluntary reporting has an important role in the development of medication safety and the overall medication process within organizations. Although majority of the TOP15 medicines were involved in MEs resulting in seemingly high-risk outcomes, they were estimated to be insignificant or minor within the reporting unit. In the future, more emphasis will be needed for the assessment and analysis of the reports for more efficient, real-time detection and response to signals from health care units.

Exploring Inpatient Medication Patterns: A Big Data and Multilevel Approach

PURPOSE

Exploratory study to examine inpatient medication administration patterns.

METHODS

Data from multiple sources were utilized for this study. The outcome was time difference between medication schedule and administration. A 3-level hierarchical linear regression approach, both unadjusted and adjusted, was considered for this study where medication administration events are nested within patients nested within nurses or units. Intraclass correlation coefficients (ICCs) were calculated and compared.

RESULTS

On average, medications were delayed by 12 (SD, 48.8) minutes. From the full model, patient ICCs decreased when "unit" replaced "nurse" as the 3rd level (0.541 vs 0.444). Patients who spoke Spanish had a significant 2.3- to 4.2-minute delay in medication administration. Certified nurses significantly give medications earlier compared with noncertified nurses by 1.6 minutes.

DISCUSSION

Optimal medication administration is a multifactorial concern with nurses playing a role. Nursing leaders should also consider patient demographics and unit conditions, such as culture, for medication administration optimization.