Analysis Of Adverse Drug Events Research Articles

Validating methods used to identify non-adherence adverse drug events in Canadian administrative health data.

Medication non-adherence is a type of adverse drug event that can lead to untreated and exacerbated chronic illness, and that drives healthcare utilization. Research using medication claims data has attempted to identify instances of medication non-adherence using the proportion of days covered or by examining gaps between medication refills. We sought to validate these measures compared to a gold standard diagnosis of non-adherence made in hospital. This was a retrospective analysis of adverse drug events diagnosed during three prospective cohorts in British Columbia between 2008 and 2015 (n = 976). We linked prospectively identified adverse drug events to medication claims data to examine the sensitivity and specificity of typical non-adherence measures. The sensitivity of the non-adherence measures ranged from 22.4% to 37.5%, with a proportion of days covered threshold of 95% performing the best; the non-persistence measures had sensitivities ranging from 10.4% to 58.3%. While a 7-day gap was most sensitive, it classified 61.2% of the sample as non-adherent, whereas only 19.6% were diagnosed as such in hospital. The methods used to identify non-adherence in administrative databases are not accurate when compared to a gold standard diagnosis by healthcare providers. Research that has relied on administrative data to identify non-adherent patients both underestimates the magnitude of the problem and may label patients as non-adherent who were in fact adherent.

High risks adverse events associated with usage of aspirin in chronic obstructive pulmonary disease

ABSTRACT Background Despite potential benefits and widespread prescription of aspirin among chronic obstructive pulmonary disease (COPD) patients, limited research has investigated its adverse effects (AEs) in COPD population. Methods We conducted a retrospective analysis of adverse drug events (ADEs) reported in the US Food and Drug Administration Adverse Event Reporting System (FAERS) between Q1 2013 and Q2 2022. COPD patients were categorized into two groups based on aspirin use. ADEs related to aspirin use were identified using combined reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC) methods. Results A total of 56,660 ADEs reports associated with COPD patients were included in the study. Among these reports, 144 adverse events were linked to aspirin use in COPD patients, including fatigue (4.12%), diarrhea (3.13%), dyspnea exertional (2.03%), rhinorrhea (1.99%), weight increased (1.89%) and vomiting (1.84%), muscle spasms (1.79%), cardiac disorder (1.74%), heart rate increased (1.69%) and peripheral swelling (1.59%). Subgroup analysis indicates that age and gender might affect the AEs frequency in COPD patients using aspirin. Conclusions Our findings identify 10 most frequently reported ADEs associated with aspirin use in COPD patients, thus offer valuable insights into the AEs of aspirin for safer clinical utilization in COPD management.

Prescription Error

Objective: This research study aimed to investigate prescription errors and their intervention outcomes at Zewditu Memorial Hospital in Addis Ababa, Ethiopia, during the year 2023. The study assessed the prevalence of prescription errors, identified contributing factors, evaluated the effectiveness of medication safety interventions, and examined the impact of adverse drug events on patient outcomes and healthcare costs. Methods: A cross-sectional study design was employed, and data were collected from the hospital's prescription files. Prescription errors were classified into various categories, and the frequency and proportion of errors were calculated. The study also evaluated different medication safety interventions' effectiveness in reducing prescription errors and assessed healthcare professionals' adherence to medication safety protocols. Additionally, the study conducted a cost analysis of adverse drug events to assess their financial implications. Results: The study revealed a prescription error rate of 25.1%, with wrong dosage, drug omission, drug-drug interactions, and illegible prescriptions being the most common error categories. Adverse drug events resulting from prescription errors affected 12.2% of patients, leading to patient harm and increased healthcare utilization. The electronic prescribing system emerged as the most effective intervention, reducing prescription errors by 60.1%. High adherence rates were observed for double-checking high-risk medications and conducting medication safety huddles. However, there was room for improvement in implementing barcoding technology and tall man lettering. Conclusion: Prescription errors and adverse drug events pose significant challenges to medication safety at Zewditu Memorial Hospital. Implementing electronic prescribing systems and enhancing medication reconciliation processes can significantly reduce prescription errors and improve patient outcomes. Furthermore, fostering a culture of safety, promoting interprofessional collaboration, and investing in education and training programs are essential to enhance medication safety practices. Continuous quality improvement initiatives and regular audits should be conducted to address medication safety challenges and support a culture of learning from errors. Policymakers should be engaged to support medication safety initiatives, and multi-center studies are recommended to enhance generalizability.

Analysis of adverse drug events collected through active surveillance in pediatric patients of a tertiary care teaching hospital of Anand district

Background: Pediatric population is vulnerable to the development of adverse drug events (ADEs). Despite that, ADEs are less reported through passive surveillance methods. Less data are available to establish the effectiveness of active surveillance methods. Aims and Objectives: The aims of this study were to analyze the ADEs collected through active surveillance in pediatric patients. Materials and Methods: Prospective and observational study of 1 year was conducted in pediatric wards of Shree Krishna Hospital, Anand. The patients of age ranging from 1 month to 18 years (and caregivers) were asked about the development of new symptom which was unintended and harmful after the administration of medicines. The patients who developed the ADEs after admission or who were admitted with ADEs were included in the study. Data were entered into Microsoft Excel for descriptive analysis. Results: Out of total 550 admissions, 35 ADEs (6.36%) were captured in 29 patients through active surveillance, whereas during the previous 4 years 17 ADEs (0.35%), out of 4846 admissions were reported through passive reporting. Out of 35 ADEs, the most common suspected drug group was antimicrobial agents (12, 34.29%) and the most common system affected was skin (15, 42.86%). Causality assessment by the World Health Organization – Uppsala Monitoring Center scale suggested that 62.86% ADEs were of possible type and by Naranjo’s scale 68.57% ADEs were of possible type. Based on the Hartwig and Siegel adverse drug reaction severity assessment scale, 71.43% ADEs were mild and 77.14% ADEs were of not preventable category by modified Schumock and Thornton criteria. Conclusion: Active surveillance method is better at identifying ADEs than passive reporting. Strengthening of pharmacovigilance systems will help in the medication safety in the long run.

Analysis of adverse drug events in patients with bipolar disorders using the Japanese Adverse Drug Event Report database.

The aim of the present study was to survey adverse drug events (ADEs) in patients with bipolar disorders and identify risk factors using the Japanese Adverse Drug Event Report (JADER) database, a spontaneous reporting system. Data on patients with bipolar disorders were extracted from the JADER database. The Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PT) and standardized MedDRA queries (SMQ) were used to define ADEs. A multiple logistic regression analysis was performed to identify risk factors for ADEs. A total of 8653 reports of 1108 types of ADEs (PT) were registered in data collected on 3521 patients with bipolar disorders. Rash (PT) was the most frequently reported in 549 patients, followed by drug eruption (PT) in 387, fever (PT) in 364, toxicity to various agents (PT) in 291, and Stevens-Johnson syndrome (PT) in 261. Among 24 ADEs (PT) that were reported in more than 50 patients, lamotrigine was associated with increased risks of 13 ADEs (PT), followed by carbamazepine with increased risks of 8 ADEs (PT). The majority of these ADEs belonged to hypersensitivity (SMQ) or hepatic disorder (SMQ). Lithium carbonate was associated with increased risks of rash (PT), drug interaction (PT), and tubulointerstitial diseases (SMQ). All antipsychotics increased the adjusted odds ratio for neuroleptic malignant syndrome (PT). The risk of hyperglycemia/new onset diabetes mellitus (SMQ) was increased by olanzapine, quetiapine fumarate, and risperidone. We are presenting the profiles of ADEs in patients with bipolar disorders using the JADER database, and propose risk factors for 19 ADEs (PT) and 4 ADEs (SMQ).

Analysis of adverse drug events in pulmonary Mycobacterium avium complex disease using spontaneous reporting system

BackgroundIn Japan, Mycobacterium avium complex lung disease (MAC-LD) is the most common in nontuberculous mycobacterial lung disease. Patients often experience adverse events, resulting in the discontinuation of treatment, which causes treatment failure. The JADER (Japanese Adverse Drug Event Report) database is a database of adverse events that allows us to collect real-world data on adverse events. We can collect large-scale data cost-effectively and detect signals of potential adverse events such as reporting odds ratio (ROR) by using spontaneous reporting systems. In this study, we aimed to elucidate the adverse events of clarithromycin (CAM), ethambutol (EB), and rifampicin (RFP) using the JADER database.MethodsWe included cases of MAC-LD between April 2004 and June 2017. We investigated sex, age, and medications that may have caused the adverse events, outcomes, and time of onset. We calculated the safety signal index as the ROR. Time-to-event analysis was performed using the Weibull distribution.ResultsThe total number of adverse events of CAM, EB, and RFP was 2780, with 806 patients. In the overall adverse events, hematologic and lymphatic disorders were the most common adverse events, with 17.3%, followed by eye disorders (16.6%), and hepatobiliary disorders (14.0%). The outcomes were as follows: recovery, 40.0%; remission, 27.1%; non-recovery, 11.2%; and death, 7.1%. Regarding the most common onset time of CAM, EB, and RFP was within 120 days at 40%, 181–300 days at 43.6%, and within 120 days at 88.5%. For CAM, the RORs of infections and infestations, hepatobiliary system disorders, and immune system disorders were 4.13 (95% confidence interval [CI], 2.3–7.44), 2.61 (95% CI, 1.39–4.91), and 2.38 (95% CI, 1.04–5.44). For EB, the ROR of eye disorders was 215.79 (95% CI, 132.62–351.12). For RFP, the RORs of renal and urinary tract disorders and investigations were 7.03 (95% CI, 3.35–14.77) and 6.99 (95% CI, 3.22–15.18). The β value of EB was 2.07 (95% CI, 1.48–2.76), which was classified as a wear-out failure type.ConclusionsFor MAC-LD, the adverse event which has the highest ROR is infections and infestations in CAM, eye disorders in EB, renal and urinary tract disorders in RFP. Adverse events of EB occur after 180 days, whereas the adverse events of CAM and RFP occur early in the course of treatment.

Analysis of adverse drug events as a way to improve cancer patient care

PurposeTo define the signals that a new artificial intelligence (AI) system must emit to improve adverse drug events (ADEs) management in oral antineoplastic agents (OAA).MethodsA multidisciplinary group of experts in...

Analysis of adverse drug events and adherence rates with newer diabetes medications in a Humana commercial, MAPD, Medicaid, and PDP member population

Analysis of adverse drug events and adherence rates with newer diabetes medications in a Humana commercial, MAPD, Medicaid, and PDP member population

Comparative Analysis of Adverse Drug Events between Geriatric and Common Wards

Comparative Analysis of Adverse Drug Events between Geriatric and Common Wards

Social Media Analytics for Smart Health

This special section of "Trends aamp; Controversies" focuses on social media analytics for smart health. The introduction, called "Social Media Analytics for Smart Health," is provided by Ahmed Abbasi and Donald Adjeroh. Then Mark Dredze and Michael J. Paul have written "Natural Language Processing for Health and Social Media." Next, Fatemeh "Mariam" Zahedi, Huimin Zhao, Nitin Walia, Hemant Jain, Patrick Sanvanson, and Reza Shaker discuss "Treating Patients Real Avatars in the Virtual Medical Office." The fourth selection, by Marco D. Huesch, is "Social Media versus Privacy and Credibility," The last piece, written by Donald Adjeroh, Richard Beal, Ahmed Abbasi, Wanhong Zheng, Marie Abate, and Arun Ross, is "Signal Fusion for Social Media Analysis of Adverse Drug Events."

Enhancing Adverse Drug Event Detection in Electronic Health Records Using Molecular Structure Similarity: Application to Pancreatitis

BackgroundAdverse drug events (ADEs) detection and assessment is at the center of pharmacovigilance. Data mining of systems, such as FDA’s Adverse Event Reporting System (AERS) and more recently, Electronic Health Records (EHRs), can aid in the automatic detection and analysis of ADEs. Although different data mining approaches have been shown to be valuable, it is still crucial to improve the quality of the generated signals.ObjectiveTo leverage structural similarity by developing molecular fingerprint-based models (MFBMs) to strengthen ADE signals generated from EHR data.MethodsA reference standard of drugs known to be causally associated with the adverse event pancreatitis was used to create a MFBM. Electronic Health Records (EHRs) from the New York Presbyterian Hospital were mined to generate structured data. Disproportionality Analysis (DPA) was applied to the data, and 278 possible signals related to the ADE pancreatitis were detected. Candidate drugs associated with these signals were then assessed using the MFBM to find the most promising candidates based on structural similarity.ResultsThe use of MFBM as a means to strengthen or prioritize signals generated from the EHR significantly improved the detection accuracy of ADEs related to pancreatitis. MFBM also highlights the etiology of the ADE by identifying structurally similar drugs, which could follow a similar mechanism of action.ConclusionThe method proposed in this paper provides evidence of being a promising adjunct to existing automated ADE detection and analysis approaches.

Reports and analysis of adverse drug events of compound vitamin injection

Reports and analysis of adverse drug events of compound vitamin injection

Direct costs and hospital morbimortality impact from preventable adverse drug events

Implementing pharmacovigilance activities consists of monitoring and assessment of activities related to medical attention. However, additional data are necessary to identify conditions where care quality can be improved. Therefore, a focus on adverse drug events analysis from a prevention and economic perspective is needed, with emphasis on its local impact. Preventable adverse drug events were summarized to establishing their impact on morbidity and mortality, as well as to estimate the ensuing economic burden. The data were gathered from a level 3 hospital (high complexity), located in Bogotá, Colombia, where specific pharmacovigilance activities were recorded in 2007. Patient charts were reviewed to characterize adverse drug events according to their causality, severity and preventability. Direct costs were estimated by grouping diagnostic tests, length of hospitalization, procedures and additional drugs required. The charts of 283 patients and 448 reports were analyzed. These data indicated that 24.8% of adverse drug events were preventable and that an associated mortality of 1.1% had occurred. The associated direct costs were between USD $16,687 and $18,739. Factors more commonly associated with preventability were drug-drug interactions, as well as inappropriate doses and unsuitable frequencies at which the drugs were administrated. The data recommended that actions be taken to decrease preventable adverse drug events, because of negative impact on patient´s health, and unnecessary consumption of healthcare resources.

Can Pharmacists Afford not to Champion Medication Safety?

Journal of Pharmacy Practice and ResearchVolume 40, Issue 3 p. 176-177 EditorialFree Access Can Pharmacists Afford not to Champion Medication Safety? Tuck Seng Wu BPharm (Hons), MHSM, MRPharmS, AMIChemE, Tuck Seng Wu BPharm (Hons), MHSM, MRPharmS, AMIChemE Editorial Advisory Board Member Journal of Pharmacy Practice and Research, and Deputy Director of Pharmacy [email protected] National University Hospital, Singapore, 119074Search for more papers by this author Tuck Seng Wu BPharm (Hons), MHSM, MRPharmS, AMIChemE, Tuck Seng Wu BPharm (Hons), MHSM, MRPharmS, AMIChemE Editorial Advisory Board Member Journal of Pharmacy Practice and Research, and Deputy Director of Pharmacy [email protected] National University Hospital, Singapore, 119074Search for more papers by this author First published: 13 April 2015 https://doi.org/10.1002/j.2055-2335.2010.tb00531.xCitations: 1AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. References 1 LT Kohn, JM Corrigan, MS Donaldson, editors. To err is human – building a safer health system. Washington: National Academy Press; 2000. 2Rinehart JR. Conundrums within a culture of safety. Am J Health Syst Pharm 2010; 67: 1206– 7. 3Leape LL, Bates DW, Cullen DJ, Cooper J, Demonaco HJ, Gallivan T, et al. Systems analysis of adverse drug events. ADE Prevention Study Group. JAMA 1995; 274: 35– 43. 4Bates DW. Frequency, consequences and prevention of adverse drug events. J Qual Clin Pract 1999; 19: 13– 17. 5Ernst FR, Grizzle AJ. Drug-related morbidity and mortality – updating the cost-of-illness model. J Am Pharm Assoc 2001; 41: 192– 9. Citing Literature Volume40, Issue3September 2010Pages 176-177 ReferencesRelatedInformation

4243 Descriptive analysis of adverse drug events registered in a computerised information system

4243 Descriptive analysis of adverse drug events registered in a computerised information system

8. Drug allergy

Drug reactions can be considered as being either predictable or unpredictable. A predictable reaction would be the result of the pharmacologic action of the medication. An unpredictable reaction might be idiosyncratic, might be drug intolerance, or might have or imply an immunologic basis, such as being IgE mediated. Immediate reactions that are not IgE mediated can be considered as pseudoallergic (non-IgE-mediated mast cell activation). This review will discuss allergic and immunologic reactions to immunomodulators, penicillins and cephalosporins, sulfonamides, aspirin, and nonselective nonsteroidal anti-inflammatory drugs and consider the serious drug-related conditions of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). The field of drug "allergy" has expanded to include adverse reactions associated with immunosuppressive medications, anticytokine therapies, and mAbs. The cytokine release reaction that occurs with anti-CD20 antibody infusions in patients with leukemia and white blood cell counts of greater than 50 x 10(9)/L is associated with high concentrations of TNF, IL-6, and IL-8. Because of the findings of fever, dyspnea, rigors, and hypotension, this reaction resembles the Jarisch-Herxheimer reaction that occurs 60 to 90 minutes after penicillin administration in patients with secondary syphilis. Furthermore, the care of the patient with penicillin allergy has been made more difficult in the absence of the major determinant, penicilloyl-polylysine, in that from 34% to 84% of patients who have positive skin test reactions to penicillin have exclusively positive reactions to the major determinant. SJS and TEN typically are caused by medications within 1 to 8 weeks of initiation of therapy. Evidence for death of the keratinocytes through (1) drug-specific cytotoxicity with the perforin-granzyme B-mediated killing and (2) activation of Fas on keratinocytes have provided explanations for the sloughing of skin. Unfortunately, intravenous immunoglobulin therapy for SJS and TEN has been disappointing.

Quality and Safety Revolution in Health Care

Quality and Safety Revolution in Health Care

Systematic Root Cause Analysis of Adverse Drug Events in a Tertiary Referral Hospital

Adverse drug events (ADEs) occur frequently, and serious ADEs are associated with mortality or prolonged morbidity. As many ADEs are preventable, identification and modification of systems and processes that permit ADEs has the potential to reduce the rate of ADEs. Root cause analysis was systematically employed in a blame-free fashion to investigate the patterns of serious ADEs that occurred during a 29-month period at Hermann Hospital (Houston), and process improvements were implemented on the basis of these findings. The consistently nonpunitive responses to the results of the initial and subsequent root cause analyses was gradually seen, accepted, and ultimately embraced by the hospital staff. The most commonly identified root causes were environmental factors (for example, increased census, increased acuity, change of shift) and staffing issues (for example, personnel new to a unit). Policy changes that led to increased use of forcing or constraining functions (for example, removal of concentrated intravenous potassium solutions from floor stocks) and better personnel support (for example, early awareness and response to localized increases in census and acuity) were particularly effective. Although limited by our lack of active surveillance and not necessarily directly due to the process changes that we implemented, the rate of voluntarily reported serious ADEs/100,000 patient days decreased during this time from 7.2 to 4.0, a decline of 45% (p < 0.001). Systematic application of root cause analysis followed by implementation of process changes that target the underlying cause(s) of each event can be successfully implemented in a large hospital.

Adverse drug events in hospitalized patients

To the Editor. —The articles by Dr Classen et al, 1 Dr Bates et al, 2 and Dr Lesar et al 3 are all excellent in their own right. The problem is that they appear at all. If we look back to 1995, we find an article by Leape et al 4 that outlines a systems analysis of adverse drug events (ADEs). Clearly it is one thing to analyze a problem and quite another to put acceptable solutions to work. I strongly agree that quality improvement teams and simplified systems are part of the answer, yet I believe that the extreme care needed to make certain that patients understand their condition and its treatment is not being taken. Placing the financial burden at $136 billion should open some eyes, and, of course, the human toll is unconscionable. At our clinic, we now take the time to develop a printed schedule detailing when and

Systems Analysis of Adverse Drug Events

To the Editor. —Groundbreaking though their work is, Dr Bates and colleagues1and Dr Leape and colleagues2may have collectively oversimplified the management tasks for reducing adverse drug events (ADEs). By launching into computerized systems changes without a deeper understanding of medication delivery process stability, they also encourage management decision making that appears contrary to knowledge-based approaches to such matters. Deming's3knowledge-based management theory is grounded in the predictability of organizational systems. Prediction requires stable processes. Neither Bates et al nor Leape et al demonstrated that what was observed was in a Upper Control Limit Average per Week 1989 Weekly Control Chart 1990 Weekly Control Chart Actual weekly process control charts of a corporation's Occupational Safety and Health Administration—reportable injuries for 1989 and 1990. The left side of the Figure shows an unstable system in which nonrandom, assignable causes of variation produced a spike of injuries after