Cause Of Adverse Drug Events Research Articles

Telemedicine and drug iatrogenesis in nursing homes

Inappropriate drug prescribing is an avoidable cause of adverse drug events, sources of an increase in morbimortality, excess spending and a decrease in quality of life. Many actions exist to improve prescribing quality and to secure the medication circuit in nursing homes. As part of the deployment of telemedicine, the benefit of a medico-pharmaceutical tele-expertise system for medication is evident.

Impact of Computer-Based and Pharmacist-Assisted Medication Review Initiated in the Emergency Department.

Whether early medication reconciliation and integration can reduce polypharmacy and potentially inappropriate medication (PIM) in the emergency department (ED) remains unclear. Polypharmacy and PIM have been recognized as significant causes of adverse drug events in older adults. Therefore, this pilot study was conducted to delineate this issue. An interventional study. A medical center in Taiwan. Older ED patients (aged ≥65 years) awaiting hospitalization between December 1, 2017, and October 31, 2018 were recruited in this study. A multidisciplinary team and a computer-based and pharmacist-assisted medication reconciliation and integration system were implemented. The reduced proportions of major polypharmacy (≥10 medications) and PIM at hospital discharge were compared with those on admission to the ED between pre- and post-intervention periods. A total of 911 patients (pre-intervention = 243 vs post-intervention = 668) were recruited. The proportions of major polypharmacy and PIM were lower in the post-intervention than in the pre-intervention period (-79.4% vs -65.3%; P < .001, and - 67.5% vs -49.1%; P < .001, respectively). The number of medications was reduced from 12.5 ± 2.7 to 6.9 ± 3.0 in the post-intervention period in patients with major polypharmacy (P < .001). Early initiation of computer-based and pharmacist-assisted intervention in the ED for reducing major polypharmacy and PIM is a promising method for improving geriatric care and reducing medical expenditures. J Am Geriatr Soc 67:2298-2304, 2019.

A Retrospective Analysis on 1330 Adverse Event Reports of Qingkailing in China: Further Perception of Its Risks and Rational Use.

Qingkailing (QKL) is a modern preparation exploited according to the traditional Chinese medicine theory. It becomes the second leading cause of adverse drug events (ADEs) in all traditional Chinese medicine injections. The safety evaluation and rational use of QKL are of special importance. This retrospective study used data from Adverse Drug Reaction Monitoring Center of Hubei Province in China from January 2012 to December 2014. ADE cases induced by QKL were collected and analyzed according to patients' demographics, characteristics of drugs involved, characteristics of ADEs, causality, and outcomes. A total of 1330 qualified ADEs were included. Most ADEs occurred within 30 min after administration and the 0-10 years old age group had the highest number of ADEs. The common ADEs included anaphylactic reaction, dyspnea and nausea. Serious reactions accounted for 5.19%. Combination with cephalosporin (74/146, 50.69%) caused more ADEs than other drugs did. Serious attention should be paid when QKL is used for children, and combination with cephalosporin should be avoided.

Prevalence of prescription errors in general practice in Jeddah, Saudi Arabia

Purpose: Prescription errors are a common cause of adverse drug events (ADEs). Recognizing ADEs can significantly contribute to the reduction of morbidity and mortality. This study aims to investigate the type and prevalence of errors in prescription writing, directed toward a needs assessment for developing educational interventions.Materials and methods: A cross-sectional descriptive study was conducted in Jeddah community pharmacies (January–February 2016). A random sample of 117 prescriptions were reviewed and analyzed by community pharmacists for legibility and omission of the information in the prescription.Results: Results revealed that 51% of the prescriptions included diagnosis, in which 62% included the recommended drug dosage. Only 7% of drug interactions were reported between the prescribed drugs, 17% of the physicians prescribed drugs that prevented the adverse effects used for diagnosis. Prescriptions for chronic conditions were scrutinized to be 18%. It was noteworthy that 29% of the pharmacists reported difficulty in reading the handwriting of prescriptions.Conclusions: The quality of prescription writing is deficient in some elements and strategies for improvement are needed. These findings underscore a crucial requirement to upgrade the quality of prescription writing by encouraging continuous medical education programs to facilitate delivery of excellent therapeutic outcomes.

Mixture drug-count response model for the high-dimensional drug combinatory effect on myopathy

Drug-drug interactions (DDIs) are a common cause of adverse drug events (ADEs). The electronic medical record (EMR) database and the FDA's adverse event reporting system (FAERS) database are the major data sources for mining and testing the ADE associated DDI signals. Most DDI data mining methods focus on pair-wise drug interactions, and methods to detect high-dimensional DDIs in medical databases are lacking. In this paper, we propose 2 novel mixture drug-count response models for detecting high-dimensional drug combinations that induce myopathy. The indicates the number of drugs in a combination. One model is called fixed probability mixture drug-count response model with a maximum risk threshold (FMDRM-MRT). The other model is called count-dependent probability mixture drug-count response model with a maximum risk threshold (CMDRM-MRT), in which the mixture probability is count dependent. Compared with the previous mixture drug-count response model (MDRM) developed by our group, these 2 new models show a better likelihood in detecting high-dimensional drug combinatory effects on myopathy. CMDRM-MRT identified and validated (54; 374; 637; 442; 131) 2-way to 6-way drug interactions, respectively, which induce myopathy in both EMR and FAERS databases. We further demonstrate FAERS data capture much higher maximum myopathy risk than EMR data do. The consistency of 2 mixture models' parameters and local false discovery rate estimates are evaluated through statistical simulation studies.

Translational Biomedical Informatics and Pharmacometrics Approaches in the Drug Interactions Research.

Drug interaction is a leading cause of adverse drug events and a major obstacle for current clinical practice. Pharmacovigilance data mining, pharmacokinetic modeling, and text mining are computation and informatic tools on integrating drug interaction knowledge and generating drug interaction hypothesis. We provide a comprehensive overview of these translational biomedical informatics methodologies with related databases. We hope this review illustrates the complementary nature of these informatic approaches and facilitates the translational drug interaction research.

Mixture drug-count response model for the high-dimensional drug combinatory effect on myopathy.

Drug-drug interactions (DDIs) are a common cause of adverse drug events (ADEs). The electronic medical record (EMR) database and the FDA's adverse event reporting system (FAERS) database are the major data sources for mining and testing the ADE associated DDI signals. Most DDI data mining methods focus on pair-wise drug interactions, and methods to detect high-dimensional DDIs in medical databases are lacking. In this paper, we propose 2 novel mixture drug-count response models for detecting high-dimensional drug combinations that induce myopathy. The "count" indicates the number of drugs in a combination. One model is called fixed probability mixture drug-count response model with a maximum risk threshold (FMDRM-MRT). The other model is called count-dependent probability mixture drug-count response model with a maximum risk threshold (CMDRM-MRT), in which the mixture probability is count dependent. Compared with the previous mixture drug-count response model (MDRM) developed by our group, these 2 new models show a better likelihood in detecting high-dimensional drug combinatory effects on myopathy. CMDRM-MRT identified and validated (54; 374; 637; 442; 131) 2-way to 6-way drug interactions, respectively, which induce myopathy in both EMR and FAERS databases. We further demonstrate FAERS data capture much higher maximum myopathy risk than EMR data do. The consistency of 2 mixture models' parameters and local false discovery rate estimates are evaluated through statistical simulation studies.

Non-steroidal anti-inflammatory drug induced acute kidney injury in the community dwelling general population and people with chronic kidney disease: systematic review and meta-analysis

BackgroundNon-steroidal anti-inflammatory drugs (NSAIDs) are a common cause of adverse drug events (ADEs), but renal risks of NSAIDs are less well quantified than gastrointestinal and cardiac risks. This paper reports a systematic review of published population-based observational studies examining the risk of acute kidney injury (AKI) associated with NSAIDs in community-dwelling adults and those with pre-existing chronic kidney disease (CKD).MethodsMEDLINE and EMBASE databases were searched until June 2016, and 3789 papers screened. Ten studies reporting NSAID risk of AKI in the general population were included in random effects meta-analysis, of which five additionally reported NSAID risk in people with CKD.ResultsIn the general population, the pooled odds ratio (OR) of AKI for current NSAID exposure was 1.73 (95%CI 1.44 to 2.07), with somewhat higher risk observed in older people (OR 2.51, 95%CI 1.52 to 2.68). In people with CKD, individual study OR of AKI due to current NSAID exposure ranged from 1.12 to 5.25, with pooled estimate OR 1.63 (95% CI 1.22 to 2.19).ConclusionsNo study reported baseline risk of AKI in different populations meaning absolute risks could not be estimated, but baseline risk and therefore the absolute risk of NSAID exposure is likely to be higher in people with CKD and older people. Large population based studies measuring AKI using current definitions and estimating the absolute risk of harm are needed in order to better inform clinical decision making.

Medication Reconciliation Failures in Children and Young Adults With Chronic Disease During Intensive and Intermediate Care.

Although medication reconciliation has become standard during hospital admission, rates of unintentional medication discrepancies during intensive care of pediatric patients with chronic disease are unknown. Such discrepancies are an important cause of adverse drug events in adults with chronic illness and are associated with unintentional discontinuation of chronic medications. We sought to determine the rate, type, timing, and predictors of potentially harmful unintentional medication discrepancies in children and young adults with chronic disease. Prospective observational cohort study. Patients discharged from the intensive and intermediate care units at a tertiary care children's hospital from September 2013 to May 2014. Consecutive sample of 308 patients less than 25 years old with chronic disease defined by prescription of at least one predetermined class of chronic medication prior to hospitalization. The number of unintentional medication discrepancies with the potential for harm, as well as patient and medication-related factors predisposing patients to these errors were assessed. Two thousand seven hundred thirty-nine medication discrepancies were identified; 284 (10%) were unintentional and had the potential for harm (0.9/patient). Of these, 128 (45%) were due to errors in taking the preadmission medication history, whereas 156 (55%) were due to errors reconciling the medication history with orders. Most events occurred at admission (66%) and were dosing errors (45%). In multivariable negative binomial regression analyses (adjusted rate ratios [95% CI]), each additional preadmission medication (1.07 [1.04-1.10]), chronic respiratory medications (1.51 [1.01-2.28]), and chronic noninvasive ventilation (1.53 [1.07-2.19]) were associated with increased risk of a discrepancy. Unintentional medication discrepancies with the potential for harm are common among children and young adults with chronic disease during critical care admission due to both failure to obtain an accurate medication history and errors in reconciling the history with patient orders. The use of current medication reconciliation processes is insufficient to prevent errors in this high-risk population.

30-Day Potentially Avoidable Readmissions Due to Adverse Drug Events.

To analyze the patterns of potentially avoidable readmissions due to adverse drug events (ADEs) to identify the most appropriate risk reduction interventions. In this observational study, we analyzed a random sample of 534 potentially avoidable 30-day readmissions from 10,275 consecutive discharges from the medical department of an academic hospital. Readmissions due to ADEs were reviewed to identify the causative drugs and the severity and interventions to prevent them. Seventy cases (13.1%) of readmission were partially or predominantly due to ADEs, of which, 58 (82.9%) were serious ADEs. Overall, 65 (92.9%) of the ADEs have been confirmed to be preventable. Inappropriate prescribing was identified as the cause of ADE in 34 cases (48.6%) mainly involving diuretics, analgesics, or antithrombotics: misprescribing n = 19 (27.1%), underprescribing n = 8 (11.4%), and overprescribing n = 7 (10.0%). The remaining half of preventable ADEs (n = 36; 51.4%) were related to suboptimal patient monitoring/education, such as adherence issues (n = 6; 8.6%) or lack of monitoring (n = 31; 44.3%). In 64 cases (91.4%), the readmission could have been potentially prevented by better monitoring for drug efficacy/disease control, or for predictable side effect. Thirty-three (97.1%) of the 34 ADEs due to inappropriate prescribing could have also been prevented by better monitoring. Adverse drug events accounted for approximately 13% of 30-day preventable readmissions. A half were due to prescription errors involving mainly diuretics, analgesics, or antithrombotics, and the other half were due to suboptimal patient monitoring/education, most frequently with antineoplastics. Both these avoidable causes may represent opportunities to reduce the total drug-related adverse events.

Burden of hospitalizations related to adverse drug events in the USA: a retrospective analysis from large inpatient database.

Adverse drug events (ADEs) represent medication-related patient harm, which is associated with significant patient morbidity and mortality. This study was conducted to determine the rate, specific causes, and outcomes of ADE-related hospitalization in the USA. We used the Healthcare Cost and Utilization Project's Nationwide Inpatient Sample dataset for the years 2008 to 2011. We selected patients with ADE based on 537 Classification of Diseases-9 codes. Main outcome measures included yearly prevalence, cost, length of stay, and mortality of ADE-related hospitalizations. Calculations were performed on weighted samples, and statistical significance was set at p-value <0.05 (two-tailed). We estimated the total hospitalizations with ADE to be 9440757 patients (6.28% of total) from 2008 to 2011. Increasing trend was noted from 2008 (5.97%) to 2011 (6.82%) with an annual percentage change rate of 4.37. Patients with ADE were significantly older (2011: mean age 61.42 vs. 48.65years) and had more comorbidities. Steroids (14.49%), antineoplastic drugs (13.06%), anticoagulants (11.33%), nonsteroidal anti-inflammatory drugs (8.78%), and opiates/narcotics (6.48%) were the five most common causes of ADE. Patient with ADE stayed 1.89days [95% confidence interval (CI) (1.79-1.99); p<0.001] longer, incurred $1851.44 [95%CI ($1613.90-$2088.96), p<0.001] higher with higher odds of mortality 1.27 [95%CI (1.24-1.29), p<0.001]. Adverse drug event carries a significant burden of inpatient hospital care, incurs more cost, and leads to increased loss of life. Targeted policies to reduce them could potentially help decrease mortality as well as drive down cost. Copyright © 2017 John Wiley & Sons, Ltd.

Direct oral anticoagulant therapy and drug interactions in patients with atrial fibrillation

Background. Drug-drug interactions (DDIs) are one potential cause of adverse drug events. Very little has been done to study the relationship between potential DDIs in patients (p) with atrial fibrilla-tion (AF) on direct oral anticoagulants (DOACs). Many anticoagulants are elimi-nated by the kidneys, so they can accumu-late if their dose is not adapted to the kid-ney function. DDI is one particular type of drug error that can result in adverse drug events (ADEs) in exposed patients and was the aim of this study.Materials and Methods. A total of 50 pa-tients with AF on DOACs (25 patients on dabigatran and 25 on rivaroxaban) with normal, mildly or moderately decreased (estimated GFR &gt; 30 mlmin-11.73m2) renal function were included (age 69±7 years, 26M/24F, body mass index (BMI) 35.4±5.1 kg/m2, duration of hyperten-sion 11±5 years, duration of AF 5±2 years, eGFR 58±23 mlmin-11.73m2 (was calcu-lated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula).&nbsp;Results. The 12-month administration of DOACs caused a nonsignificant de-crease of eGFR (declined from 58±23 mlmin-11.73m2 to 56±17 mlmin-11.73m2 (p=0.01). All patients have the right dose of DOACs according to eGFR.&nbsp;Patients with AF and DOACs on more than 3 different drugs (20%) such as statins, verapamil and amiodarone were more prone to AE.&nbsp;Conclusion. DDIs are one of the most important problems in every day prac-tice. Coadministration of statins with da-bigatran worsens clinical outcomes and a similar interaction might be seen with ve-rapamil and amiodarone. Patients need to&nbsp;be on the right drug/right dose given the kidney function they have, with special care on DDIs.

Validation par consensus d’un outil d’identification de prescriptions inappropriées en pédiatrie (POPI)

Medication errors including inappropriate prescriptions and drug omissions are one of the causes of adverse drug events in children. Our aim was to develop a preliminary screening tool to detect omissions and inappropriate prescriptions in pediatrics based on French and international guidelines. Disease classification was based on the prevalence rate of pathology and hospital statistics. The criteria were obtained by reviewing many French and international references. The Delphi consensus technique was used to establish the content validity of POPI. The level of agreement and the proposals of healthcare professionals was noted on a nine-point Likert scale. The criteria were categorized according to the main physiological systems (gastroenterology, respiratory infections, pain, neurology, dermatology, and miscellaneous). They were distributed to 16 French pediatric panelists (eight pharmacists, eight pediatricians who were hospital-based [50%] or working in the community [50%]). After two rounds of the Delphi process, 101 of 108 criteria were chosen with strong consensus (76 inappropriate prescriptions and 25 omissions). POPI is the first screening tool to detect inappropriate prescriptions and omissions in pediatrics. It is now necessary to conduct a prospective study to determine inter-rater reliability and the tool's detection capacity.

Barricades and brickwalls--a qualitative study exploring perceptions of medication use and deprescribing in long-term care.

BackgroundThe co-administration of multiple drugs (polypharmacy) is the single most common cause of adverse drug events in the older population, and residents of long-term care facilities (LTCFs) are at particularly high risk of medication harm. ‘Deprescribing’ – the withdrawal of an inappropriate medication with goal of managing polypharmacy and improving outcomes – may improve the quality of life of LTCF residents. The RELEASE study sought to explore perceptions of medication use and the concept of deprescribing in LTCFs.MethodsFocus groups and interviews were conducted with General Practitioners (GPs), pharmacists, nursing staff, residents and their relatives within three LTCFs in the Illawarra-Shoalhaven region of NSW, Australia. Audiotapes were transcribed verbatim and, using the Integrative Model of Behaviour Prediction as a framework, thematic analysis of transcripts was conducted using QSR NVivo 10.ResultsParticipants acknowledged the burden of too many medications (time to administer, physical discomfort, cost), yet displayed passivity towards medication reduction. Residents and relatives lacked understanding of medicine indications or potential harms. Willingness to initiate and accept medication change was dependent on the GP, who emerged as a central trusted figure. GPs preferred ‘the path of least resistance’, signalling systems barriers (poor uniformity of LTCF medical records, limited trained LTCF personnel); time constraints (resident consultations, follow-up with specialists and family); and the organisation of care (collaborating with LTCF staff, pharmacists and prescribing specialists) as obstacles to deprescribing.ConclusionsTargeted engagement is required to raise awareness of the risks of polypharmacy in LTCFs and encourage acceptance of deprescribing amongst residents and their relatives. GPs are integral to the success of deprescribing initiatives within this sector.Electronic supplementary materialThe online version of this article (doi:10.1186/s12877-016-0181-x) contains supplementary material, which is available to authorized users.

A Review on Medication Errors

Role of clinical pharmacist is to provide optimal pharmaceutical care for individual patients and optimal pharmaceutical care is attained when the right drug in the correct dosage and quality reaches the right patients at the right point in time with the right information. Any preventable event that may cause or lead to inappropriate medication use or patient harm during medication to user is called medicational error and is in the control of the health care professional, patient and consumer. In this review on medication errors, prescr-ibing errors (67 %), administration errors (25%), dispensing errors (08%) were found on the basis of review of literature.Prescribing errors are the prime cause of MEs that further leads to subsequent dispensing and administration errors. Medication errors are common cause of adverse drug events or subtherapeutic outcomes of pharmaceutical care.

Frequency and Severity of Adverse Drug Events by Medication Classes: The JADE Study.

Adverse drug events (ADEs) are a significant concern in daily practice; however, the profile of high-risk drugs remains unclear. Our objective was to categorize high-risk medication classes according to frequency and severity of ADEs. The JADE study is a prospective cohort study of 3459 hospitalized adult patients. We investigated the ADEs and medications prescribed to the patients. The rate of ADEs for each medication class was calculated by dividing the number of ADEs by the number of patients who received each medication class on admission. Overall, 14,435 medications were ordered on admission for patients (median 4; interquartile range, 2-6). Electrolytes and fluids were most frequently prescribed (1876 patients, 54%). Sedatives, antibiotics, peptic ulcer drugs, and analgesics were also commonly prescribed. The frequency was similar in both elderly and younger patients. Among 1010 identified ADEs, antibiotics were most frequently associated with ADEs (31 ADEs per 100 prescribed patients on admission). In patients 65 years and older, corticosteroids, anticonvulsants, laxatives, nonsteroidal anti-inflammatory drugs, and antipsychotics were the 5 most frequent medication classes causing ADEs following antibiotics. In patients younger than 65 years, antibiotics were also the most frequent cause of ADEs, followed by laxatives, lipid-lowering agents, anticonvulsants, and corticosteroids. Among cardiovascular agent-associated ADEs, 46% were fatal or life threatening in elderly patients, whereas antihypertensives were most often associated with fatal or life-threatening ADEs (25%) in younger patients. The medication classes frequently associated with ADEs did not necessarily induce severe ADEs.

The effectiveness of computerized drug-lab alerts: A systematic review and meta-analysis

BackgroundInadequate lab monitoring of drugs is a potential cause of ADEs (adverse drug events) which is remediable. ObjectivesTo determine the effectiveness of computerized drug-lab alerts to improve medication-related outcomes. Data sourcesCitations from the Computerized Clinical Decision Support System Systematic Review (CCDSSR) and MMIT (Medications Management through Health Information Technology) databases, which had searched MEDLINE, EMBASE, CINAHL, Cochrane Database of Systematic Reviews, International Pharmaceutical Abstracts from 1974 to March 27, 2013. Study selectionRandomized controlled trials (RCTs) of clinician-targeted computerized drug lab alerts conducted in any healthcare setting. Two reviewers performed full text review to determine study eligibility. Data abstractionA single reviewer abstracted data and evaluated validity of included studies using Cochrane handbook domains. Data synthesisThirty-six studies met the inclusion criteria (25 single drug studies with 22,504 participants, 14 targeting anticoagulation; 11 multi-drug studies with 56,769 participants). ADEs were reported as an outcome in only four trials, all targeting anticoagulants. Computerized drug-lab alerts did not reduce ADEs (OR 0.89, 95% CI 0.79–1.00, p=0.05), length of hospital stay (SMD 0.00, 95%CI −0.93 to 0.93, p=0.055, 1 study), likelihood of hypoglycemia (OR 1.29, 95% CI 0.31–5.37) or likelihood of bleeding, but were associated with increased likelihood of prescribing changes (OR 1.73, 95% CI 1.21–2.47) or lab monitoring (OR 1.47, 95% confidence interval 1.12–1.94) in accordance with the alert. ConclusionsThere is no evidence that computerized drug-lab alerts are associated with important clinical benefits, but there is evidence of improvement in selected clinical surrogate outcomes (time in therapeutic range for vitamin K antagonists), and changes in process outcomes (lab monitoring and prescribing decisions).

Prevalence and Perceived Preventability of Self-Reported Adverse Drug Events – A Population-Based Survey of 7099 Adults

PurposeAdverse drug events (ADEs) are common and often preventable among inpatients, but self-reported ADEs have not been investigated in a representative sample of the general public. The objectives of this study were to estimate the 1-month prevalence of self-reported ADEs among the adult general public, and the perceived preventability of 2 ADE categories: adverse drug reactions (ADRs) and sub-therapeutic effects (STEs).MethodsIn this cross-sectional study, a postal survey was sent in October 2010 to a random sample of 13 931 Swedish residents aged ≥18 years. Self-reported ADEs experienced during the past month included ADRs, STEs, drug dependence, drug intoxications and morbidity due to drug-related untreated indication. ADEs could be associated with prescription, non-prescription or herbal drugs. The respondents estimated whether ADRs and STEs could have been prevented. ADE prevalences in age groups (18–44, 45–64, or ≥65 years) were compared.ResultsOf 7099 respondents (response rate 51.0%), ADEs were reported by 19.4% (95% confidence interval, 18.5–20.3%), and the prevalence did not differ by age group (p>0.05). The prevalences of self-reported ADRs, STEs, and morbidities due to drug-related untreated indications were 7.8% (7.2–8.4%), 7.6% (7.0–8.2%) and 8.1% (7.5–8.7%), respectively. The prevalence of self-reported drug dependence was 2.2% (1.9–2.6%), and drug intoxications 0.2% (0.1–0.3%). The respondents considered 19.2% (14.8–23.6%) of ADRs and STEs preventable. Although reported drugs varied between ADE categories, most ADEs were attributable to commonly dispensed drugs. Drugs reported for all and preventable events were similar.ConclusionsOne-fifth of the adult general public across age groups reported ADEs during the past month, indicating a need for prevention strategies beyond hospitalised patients. For this, the underlying causes of ADEs should increasingly be investigated. The high burden of ADEs and preventable ADEs from widely used drugs across care settings supports redesigning a safer healthcare system to adequately tackle the problem.

Types and severity of medication errors in Iran; a review of the current literature

Medication error (ME) is the most common single preventable cause of adverse drug events which negatively affects patient safety. ME prevalence is a valuable safety indicator in healthcare system. Inadequate studies on ME, shortage of high-quality studies and wide variations in estimations from developing countries including Iran, decreases the reliability of ME evaluations. In order to clarify the status of MEs, we aimed to review current available literature on this subject from Iran. We searched Scopus, Web of Science, PubMed, CINAHL, EBSCOHOST and also Persian databases (IranMedex, and SID) up to October 2012 to find studies on adults and children about prescription, transcription, dispensing, and administration errors. Two authors independently selected and one of them reviewed and extracted data for types, definitions and severity of MEs. The results were classified based on different stages of drug delivery process. Eighteen articles (11 Persian and 7 English) were included in our review. All study designs were cross-sectional and conducted in hospital settings. Nursing staff and students were the most frequent populations under observation (12 studies; 66.7%). Most of studies did not report the overall frequency of MEs aside from ME types. Most of studies (15; 83.3%) reported prevalence of administration errors between 14.3%-70.0%. Prescribing error prevalence ranged from 29.8%-47.8%. The prevalence of dispensing and transcribing errors were from 11.3%-33.6% and 10.0%-51.8% respectively. We did not find any follow up or repeated studies. Only three studies reported findings on severity of MEs. The most reported types of and the highest percentages for any type of ME in Iran were administration errors. Studying ME in Iran is a new area considering the duration and number of publications. Wide ranges of estimations for MEs in different stages may be because of the poor quality of studies with diversity in definitions, methods, and populations. For gaining better insights into ME in Iran, we suggest studying sources, underreporting of, and preventive measures for MEs.

Impact of target-specific oral anticoagulants on transitions of care and outpatient care models

Patients with acute or chronic illness experience transitions of care when they leave one healthcare setting and move to another. Care transitions are points of increased patient risk. Numerous care transition models have been developed that focus on improving the hospital discharge process to prevent adverse events after hospital discharge and to reduce readmission rates. Anticoagulants are a common cause of adverse drug events in hospitals, and of adverse events that lead to patient harm and hospital readmission. Anticoagulation management services improve the outcomes of anticoagulant therapy in both hospitalized and ambulatory patients. The services they provide, including improved communication, medication management, and patient education, are also central tenets of care transition models. These services have traditionally been focused around warfarin and heparin. Recently, new target specific oral anticoagulants have been approved in the US for various indications that traditionally have been treated with warfarin. These new agents are administered in fixed doses without the need for routine laboratory monitoring or frequent dosing adjustments. Yet as high risk drugs, they will require systematic efforts to assure their safety and minimize potential adverse events. These concerns are of particular importance during transitions of care. Anticoagulation management services, must be prepared to establish practices that improve patient outcomes regardless of the anticoagulant prescribed, using the established principals of care transition models.