Consensus list of signals to detect potential adverse drug reactions in nursing homes.
ABSTRACT: To develop a consensus list of agreed-upon laboratory, pharmacy, and Minimum Data Set signals that a computer system can use in the nursing home to detect potential adverse drug reactions (ADRs).Literature search for potential ADR signals, followed by an internet-based, a two-round, modified Delphi survey.A nationally representative survey of experts in geriatrics.Panel of 13 physicians, 10 pharmacists, and 13 advanced practitioners.Mean score and 95% confidence interval (CI) for each of 80 signals rated on a 5-point Likert scale (5=strong agreement with likelihood of indicating potential ADRs). Consensus agreement indicated by a lower-limit 95% CI of 4.0 or greater.Panelists reached consensus agreement on 40 signals: 15 laboratory and medication combinations, 12 medication concentrations, 10 antidotes, and three Resident Assessment Protocols (RAPs). Highest consensus scores (4.6, 95% CI=4.4-4.9 or 4.4-4.8) were for naloxone when taking opioid analgesics; phytonadione when taking warfarin; dextrose, glucagon, or liquid glucose when taking hypoglycemic agents; medication-induced hypoglycemia; supratherapeutic international normalized ratio when taking warfarin; and triggering the Falls RAP when taking certain medications.A multidisciplinary expert panel was able to reach consensus agreement on a list of signals to detect potential ADRs in nursing home residents. The results of this study can be used to prioritize an initial list of signals to be included in paper- or computer-based methods for potential ADR detection.
Project description:Little is known about the relation of adverse drug reactions (ADRs) to self-use of medications.The aim of this study was to determine the frequency and severity of ADRs related to self-medication (ADR-SM) among emergency department (ED) patients and to describe their main characteristics.A prospective, cross-sectional, observational study was conducted over a period of 8 weeks (1 March to 20 April 2010), in the ED of 11 French academic hospitals. Adult patients presenting to the ED during randomization periods were included, with the exception of cases of self-drug poisoning, inability to complete self-medication questionnaire, or refusal. Clinical outcomes were assessed as well as history of self-medication behaviours and all drugs taken. All doubtful files and those related to ADR-SM were systematically reviewed by an expert committee.A total of 3,027 of 4,661 patients presenting to the ED met the inclusion criteria. Of these, 84.4 % declared a self-medication behaviour, 63.7 % took at least one non-prescribed drug during the previous 2 weeks and 59.9 % took a prescribed medication. A total of 296 patients experienced an ADR (9.78 %), of which 52 (1.72 %) were related to self-medication. Those ADRs related to self-medication included prescribed drugs (n = 19), non-prescribed drugs (n = 17), treatment discontinuation (n = 14), and interactions between non-prescribed and prescribed drugs (n = 2). The ADRs attributed to non-prescribed drugs represented 1 % of all patients taking non-prescribed drugs (n = 1,927). ADR severity was significantly lower for those related to self-medication (p = .032).Self-medication is frequent; its potential toxicity should not be neglected, taking into account the rate of adverse drug reactions in about 1 % of ED patient.
Project description:OBJECTIVES:To examine the effect of interventions to optimize medication use on adverse drug reactions (ADRs) in older adults. DESIGN:Systematic review and meta-analysis. EMBASE, PubMed, OVID, Cochrane Library, Clinicaltrials.gov, and Google Scholar were searched through April 30, 2017. SETTING:Randomized controlled trials. PARTICIPANTS:Older adults (mean age ?65) taking medications. MEASUREMENTS:Two authors independently extracted relevant information and assessed studies for risk of bias. Discrepancies were resolved in consensus meetings. The outcomes were any and serious ADRs. Random-effects models were used to combine the results of multiple studies and create summary estimates. RESULTS:Thirteen randomized controlled trials involving 6,198 older adults were included. The studies employed a number of different interventions that were categorized as pharmacist-led interventions (8 studies), other health professional-led interventions (3 studies), a brief educational session (1 study), and a technology intervention (1 study). The intervention group was 21% less likely than the control group to experience any ADR (odds ratio (OR) = 0.79, 95% confidence interval (CI) = 0.62-0.99). In the six studies that examined serious ADRs, the intervention group was 36% less likely than the control group to experience a serious ADR (OR = 0.64, 95% CI = 0.42-0.98). CONCLUSION:Interventions designed to optimize medication use reduced the risk of any and serious ADRs in older adults. Implementation of these successful interventions in healthcare systems may improve medication safety in older adults.
Project description:Adverse drug reactions (ADRs) are important causes of morbidity and mortality in the healthcare system; however, there are no studies reporting on the magnitude and risk factors associated with ADR-related hospitalisation in Ethiopia.To characterise the reaction types and the drugs implicated in admission to Jimma University Specialized Hospital, Southwest Ethiopia, and to identify risk factors associated with ADR-related hospitalisation.A prospective cross-sectional study was conducted from May 2015 to August 2016 among consenting patients aged ?18 years consecutively admitted to medical wards taking at least one medication prior to admission. ADR-related hospitalisations were determined through expert review of medical records, laboratory tests, patient interviews and physical observation. ADR causality was assessed by the Naranjo algorithm followed by consensus review with internal medicine specialist. ADR preventability was assessed using Schumock and Thornton's criteria. Only definite and probable ADRs that provoked hospitalisation were considered. Binary logistic regression was used to identify independent predictors of ADR-related hospitalisation.Of 1,001 patients, 103 (10.3%) had ADR-related admissions. Common ADRs responsible for hospitalisation were hepatotoxicity (35, 29.4%) and acute kidney injury (27, 22.7%). The drug classes most frequently implicated were antitubercular agents (45, 25.0%) followed by antivirals (22, 12.2%) and diuretics (19, 10.6%). Independent predictors of ADR-related hospitalisation were body mass index (BMI) <18.5 kg/m2 (adjusted odd ratio [AOR] = 1.69; 95% confidence interval [CI] = 1.10-2.62; p = 0.047), pre-existing renal disease (AOR = 2.84; 95%CI = 1.38-5.85, p = 0.004), pre-existing liver disease (AOR = 2.61; 95%CI = 1.38-4.96; p = 0.003), number of comorbidities ?4 (AOR = 2.09; 95%CI = 1.27-3.44; p = 0.004), number of drugs ?6 (AOR = 2.02; 95%CI = 1.26-3.25; p = 0.004) and history of previous ADRs (AOR = 24.27; 95%CI = 11.29-52.17; p<0.001). Most ADRs (106, 89.1%) were preventable.ADRs were a common cause of hospitalisation. The majority of ADRs were preventable, highlighting the need for monitoring and review of patients with lower BMI, ADR history, renal and liver diseases, multiple comorbidities and medications. ADR predictors should be integrated into clinical pathways and pharmacovigilance systems.
Project description:To investigate the incidence and characteristics of hospital admissions related to adverse drug events in the paediatric setting.Prospective single-centre study.A secondary and tertiary paediatric care centre.A total of 683 acutely admitted patients, aged 0-18 year. All acutely admitted patients, using medication before admission, were prospectively screened for possible Adverse Drug Reactions (ADR)-related admission with a trigger list. Included cases were analysed with the Naranjo score for the assessment of causality.This research explored the incidence of ADR-related admissions and investigated the relation between ADR and the licensing status of the medicines, as well as the severity and potential to prevent the ADRs.A total of 683 patients were admitted acutely during the study period, 47 of them were exposed to cancer chemotherapy. Fifteen patients not exposed to chemotherapy (2.4%) were admitted due to an ADR. Five of these 15 ADRs (33%) were caused by unlicensed or off-label used drugs. Thirty-two patients exposed to chemotherapy (68.1%) were admitted due to an ADR; 27 of these (84%) were caused by unlicensed or off-label used drugs.In conclusion, this study shows that ADR-related hospital admissions occur more frequently in the paediatric population compared with adults, and more frequently in patients exposed to cancer chemotherapy. No relation was found between the unlicensed and off-label used drugs and the incidence of ADRs.
Project description:Background:The Protecting Canadians from Unsafe Drugs Act will eventually require institutions to report all serious adverse drug reactions (ADRs), although the proposed regulations do not yet define what will need to be reported and by whom. Knowledge about the occurrence of serious ADRs in the hospital setting is needed to optimize the effectiveness of reporting and to determine the potential implications of mandatory reporting. Objectives:To quantify and characterize suspected serious ADRs in patients admitted to a general medicine service, to assess the likelihood of causality, and to determine inter-rater agreement for identification of ADRs and assessment of their likelihood. Methods:This prospective observational study involved 60 consecutive patients admitted to a general medicine service at a tertiary care teaching centre starting on March 28, 2016. The primary outcome was the number of serious ADRs, defined by Health Canada as ADRs that result in hospital admission, congenital malformation, persistent or significant disability or incapacity, or death; that are life-threatening; or that require significant intervention to prevent one of these outcomes. Medical records were reviewed independently by pairs of pharmacists for serious ADRs, and the likelihood of causality was assessed using the World Health Organization-Uppsala Monitoring Centre system. Inter-rater agreement was calculated using the kappa score, and disagreements were resolved by discussion and consensus. Results:Twenty-three serious ADRs occurred in the sample of 60 patients. The proportion of patients experiencing a serious ADR that contributed to the original hospital admission was 19/60 (32%, 95% confidence interval [CI] 20%-43%), and 4 patients (7%, 95% CI 0%-13%) experienced a serious ADR during their hospital stay. Inter-rater agreement for occurrence of serious ADRs was moderate (kappa 0.58, 95% CI 0.35-0.76). Conclusion:Reportable serious ADRs were common among patients admitted to a general medicine service. Canadian hospitals would face difficulties reporting all serious ADRs because of the frequency of their occurrence and the subjectivity of their identification.
Project description:BACKGROUND: Often unrecognized by providers, adverse drug reactions (ADRs) diminish patients' quality of life, cause preventable admissions and emergency department visits, and increase health care costs. OBJECTIVE: This article evaluates whether an automated system, the Adverse Drug Effect Recognizer (ADER), could assist clinicians in detecting and addressing inpatients' ongoing preadmission ADRs. METHODS: ADER uses natural language processing to extract patients' medications, findings, and past diagnoses from admission notes. It compares excerpted information to a database of known medication adverse effects and promptly warns clinicians about potential ongoing ADRs and potential confounders via alerts placed in patients' electronic health records (EHRs). A 3-month intervention trial evaluated ADER's impact on antihypertensive medication ordering behaviors. At the time of patient admission, ADER warned providers on the Internal Medicine wards of Vanderbilt University Hospital about potential ongoing preadmission antihypertensive medication ADRs. A retrospective control group, comprised similar physicians from a period prior to the intervention, received no alerts. The evaluation compared ordering behaviors for each group to determine if preadmission medications changed during hospitalization or at discharge. The study also analyzed intervention group participants' survey responses and user comments. RESULTS: ADER identified potential preadmission ADRs for 30% of both groups. Compared with controls, intervention providers more often withheld or discontinued suspected ADR-causing medications during the inpatient stay (p < 0.001). Intervention providers who responded to alert-related surveys held or discontinued suspected ADR-causing medications more often at discharge (p < 0.001). CONCLUSION: Results indicate that ADER helped physicians recognize ADRs and reduced ordering of suspected ADR-causing medications. In hospitals using EHRs, ADER-like systems could improve clinicians' recognition and elimination of ongoing ADRs.
Project description:Electronic health records (EHRs) contain information to detect adverse drug reactions (ADRs), as they contain comprehensive clinical information. A major challenge of using comprehensive information involves confounding. We propose a novel data-driven method to identify ADR signals accurately by adjusting for confounders.We focused on two serious ADRs, rhabdomyolysis and pancreatitis, and used information in 264,155 unique patient records. We identified an ADR using established criteria, selected potential confounders, and then used penalized logistic regressions to estimate confounder-adjusted ADR associations. A reference standard was created to evaluate and compare the precision of the proposed method and four others.Precision was 83.3% for rhabdomyolysis and 60.8% for pancreatitis when using the proposed method, and we identified several drug safety signals that are interesting for further clinical review.The proposed method effectively estimated ADR associations after adjusting for confounders. A main cause of error was probably due to the nature of the dataset in that a substantial number of patients had a single visit only and, therefore, it was not possible to determine correctly the appropriate sequence of events for them. It is likely that performance will be improved with use of EHR data that contain more longitudinal records.This data-driven method is effective in controlling for confounding, resulting in either a higher or similar precision when compared with four comparators, has the unique ability to provide insight into confounders for each specific medication-ADR pair, and can be easily adapted to other EHR systems.
Project description:Identifying potential adverse drug reactions (ADRs) is critically important for drug discovery and public health. Here we developed a multiple evidence fusion (MEF) method for the large-scale prediction of drug ADRs that can handle both approved drugs and novel molecules. MEF is based on the similarity reference by collaborative filtering, and integrates multiple similarity measures from various data types, taking advantage of the complementarity in the data. We used MEF to integrate drug-related and ADR-related data from multiple levels, including the network structural data formed by known drug-ADR relationships for predicting likely unknown ADRs. On cross-validation, it obtains high sensitivity and specificity, substantially outperforming existing methods that utilize single or a few data types. We validated our prediction by their overlap with drug-ADR associations that are known in databases. The proposed computational method could be used for complementary hypothesis generation and rapid analysis of potential drug-ADR interactions.
Project description:BACKGROUND:Adverse drug reactions (ADRs) occur in nearly all patients on chemotherapy, causing morbidity and therapy disruptions. Detection of such ADRs is limited in clinical trials, which are underpowered to detect rare events. Early recognition of ADRs in the postmarketing phase could substantially reduce morbidity and decrease societal costs. Internet community health forums provide a mechanism for individuals to discuss real-time health concerns and can enable computational detection of ADRs. OBJECTIVE:The goal of this study is to identify cutaneous ADR signals in social health networks and compare the frequency and timing of these ADRs to clinical reports in the literature. METHODS:We present a natural language processing-based, ADR signal-generation pipeline based on patient posts on Internet social health networks. We identified user posts from the Inspire health forums related to two chemotherapy classes: erlotinib, an epidermal growth factor receptor inhibitor, and nivolumab and pembrolizumab, immune checkpoint inhibitors. We extracted mentions of ADRs from unstructured content of patient posts. We then performed population-level association analyses and time-to-detection analyses. RESULTS:Our system detected cutaneous ADRs from patient reports with high precision (0.90) and at frequencies comparable to those documented in the literature but an average of 7 months ahead of their literature reporting. Known ADRs were associated with higher proportional reporting ratios compared to negative controls, demonstrating the robustness of our analyses. Our named entity recognition system achieved a 0.738 microaveraged F-measure in detecting ADR entities, not limited to cutaneous ADRs, in health forum posts. Additionally, we discovered the novel ADR of hypohidrosis reported by 23 patients in erlotinib-related posts; this ADR was absent from 15 years of literature on this medication and we recently reported the finding in a clinical oncology journal. CONCLUSIONS:Several hundred million patients report health concerns in social health networks, yet this information is markedly underutilized for pharmacosurveillance. We demonstrated the ability of a natural language processing-based signal-generation pipeline to accurately detect patient reports of ADRs months in advance of literature reporting and the robustness of statistical analyses to validate system detections. Our findings suggest the important contributions that social health network data can play in contributing to more comprehensive and timely pharmacovigilance.
Project description:To describe frequency, preventability and seriousness of adverse drug reactions (ADRs) in children as cause of emergency department (ED) admission and to evaluate the association between specific factors and the reporting of ADRs.A retrospective analysis based on reports of suspected ADRs collected between January 1st, 2012 and December 31st, 2016 in the ED of Meyer Children's Hospital (Italy). Demographics, clinical status, suspected drugs, ADR description, and its degree of seriousness were collected. Logistic regression was used to estimate the reporting odds ratios (RORs) with 95% confidence intervals (CIs) of potential predictors of ADR seriousness.Within 5 years, we observed 834 ADRs (1100 drug-ADR pairs), of whom 239 were serious; of them, 224 led to hospitalization. Patients were mostly treated with one drug. Among patients treated with more than one drug, 78 ADRs presented a potential interaction. The most frequently reported ADRs involved gastrointestinal system. The most frequently reported medication class was antinfectives. Risk of serious ADR was significantly lower in children and infants compared to adolescents (ROR 0.41 [95% CI: 0.27-0.61] and 0.47 [0.32-0.71], respectively), and it was significantly increased in subjects exposed to more than one drug (ROR 1.87 [1.33-2.62] and 3.01 [2.07-4.37] for subjects exposed to 2 and 3 or more drugs, respectively). Gender, interactions and off-label drug use did not influence the risk of serious ADRs.Active surveillance in pharmacovigilance might represent the best strategy to estimate and characterize the clinical burden of ADRs in children.