How many potential drug-drug interactions cause adverse drug reactions in hospitalized patients?

Drug-Drug Interactions and Actual Harm to Hospitalized Patients: A Multicentre Study Examining the Prevalence Pre- and Post-Electronic Medication System Implementation

INTRODUCTION

Drug-drug interactions (DDIs) have potential to cause patient harm, including lowering therapeutic efficacy. This study aimed to (i) determine the prevalence of potential DDIs (pDDIs); clinically relevant DDIs (cDDIs), that is, DDIs that could lead to patient harm, taking into account a patient's individual clinical profile, drug effects and severity of potential harmful outcome; and subsequent actual harm among hospitalized patients and (ii) examine the impact of transitioning from paper-based medication charts to electronic medication management (eMM) on DDIs and patient harms.

METHODS

This was a secondary analysis of the control arm of a controlled pre-post study. Patients were randomly selected from three Australian hospitals. Retrospective chart review was conducted before and after the implementation of an eMM system, without accompanying clinical decision support alerts for DDIs. Harm was assessed by an expert panel.

RESULTS

Of 1186 patient admissions, 70.1% (n = 831) experienced a pDDI, 42.6% (n = 505) a cDDI and 0.9% (n = 11) an actual harm in hospital. Of 15,860 pDDIs identified, 27.0% (n = 4285) were classified as cDDIs. The median number of pDDIs and cDDIs per 10 drugs were 6 [interquartile range (IQR) 2-13] and 0 (IQR 0-2), respectively. In cases where a cDDI was identified, both drugs were 44% less likely to be co-administered following eMM (adjusted odds ratio 0.56, 95% confidence interval 0.46-0.73).

CONCLUSION

Although most patients experienced a pDDI during their hospital stay, less than one-third of pDDIs were clinically relevant. The low prevalence of harm identified raises questions about the value of incorporating DDI decision support into systems given the potential negative impacts of DDI alerts.

Are polypharmacy side effects predicted by public data still valid in real-world data?

Background and Objective

Although interest in predicting drug-drug interactions is growing, many predictions are not verified by real-world data. This study aimed to confirm whether predicted polypharmacy side effects using public data also occur in data from actual patients.

Methods

We utilized a deep learning-based polypharmacy side effects prediction model to identify cefpodoxime-chlorpheniramine-lung edema combination with a high prediction score and a significant patient population. The retrospective study analyzed patients over 18 years old who were admitted to the Asan medical center between January 2000 and December 2020 and took cefpodoxime or chlorpheniramine orally. The three groups, cefpodoxime-treated, chlorpheniramine-treated, and cefpodoxime & chlorpheniramine-treated were compared using inverse probability of treatment weighting (IPTW) to balance them. Differences between the three groups were analyzed using the Kaplan-Meier method and Cox proportional hazards model.

Results

The study population comprised 54,043 patients with a history of taking cefpodoxime, 203,897 patients with a history of taking chlorpheniramine, and 1,628 patients with a history of taking cefpodoxime and chlorpheniramine simultaneously. After adjustment, the 1-year cumulative incidence of lung edema in the patient group that took cefpodoxime and chlorpheniramine simultaneously was significantly higher than in the patient groups that took cefpodoxime or chlorpheniramine only (p=0.001). Patients taking cefpodoxime and chlorpheniramine together had an increased risk of lung edema compared to those taking cefpodoxime alone [hazard ratio (HR) 2.10, 95% CI 1.26-3.52, p<0.005] and those taking chlorpheniramine alone, which also increased the risk of lung edema (HR 1.64, 95% CI 0.99-2.69, p=0.05).

Conclusions

Validation of polypharmacy side effect predictions with real-world data can aid patient and clinician decision-making before conducting randomized controlled trials. Simultaneous use of cefpodoxime and chlorpheniramine was associated with a higher long-term risk of lung edema compared to the use of cefpodoxime or chlorpheniramine alone.

A meta-analysis assessing the prevalence of drug-drug interactions among hospitalized patients

PURPOSE

Drug-drug interactions (DDIs), particularly in hospitalized patients can result in adverse drug events and unfavorable health consequences. The aim of this meta-analysis is to provide up-to-date evidence on the prevalence of clinically evident adverse drug events due to DDIs in hospitalized patients.

METHODS

Data from Scopus, PubMed, Cochrane and Web of Science were extracted using these keywords (Drug interaction/drug-drug interactions, Hospital/ hospitals, Adverse drug event, Hospitalized patients, inpatient, Department, Hospital stay, Harm, Mortality, death). The studies that include Observational studies on hospitalized patients, reporting potential DDIs using an electronic database, and reporting the clinically observed adverse drug interactions (ADI) through symptoms, signs or Laboratory tests are included. Using Open meta-Software (version 12.11.14), the incidence of clinically evident DDIs among hospitalized patients was determined and shown in a forest plot.

RESULTS

Only 15 of the 8261 articles found through a literature search met the inclusion criteria and reported the desired outcome. The pooled prevalence of potential drug-drug interactions is 64.9% (CI 95% 0.618-0.736). While clinically evident DDIs have a pooled frequency of 17.17% (CI 95% 0.133-0.256).

CONCLUSION

The issue of DDIs remains a significant concern in hospitalized patients, with a notable rise in their prevalence. This meta-analysis encompassed a greater quantity of studies and demonstrated a heightened proportion of drug-drug interaction prevalence in comparison to the percentages reported in the previously published meta-analysis.

Translation, cultural adaptation and validation of the revised patients' attitudes towards deprescribing (rPATD) questionnaire in Romanian older adults

BACKGROUND

Deprescribing is part of ensuring appropriate medication use and may reduce medication-related harm. Capturing the beliefs and attitudes of patients towards deprescribing by using a validated tool may support optimizing medication use in practice.

OBJECTIVES

To translate, culturally adapt and validate the revised Patients' Attitudes Towards Deprescribing (rPATD) questionnaire in Romanian and to investigate the attitudes and beliefs of older adults towards deprescribing.

METHODS

The rPATD questionnaire was translated using forward-backward translation into Romanian and culturally adapted. The psychometric properties were evaluated in older adults ≥65 years of age. Structural validity was assessed by item load on factors using an exploratory factor analysis (EFA) which was compared to the original English version and the internal consistency by Cronbach's alpha. Construct validity was evaluated by calculating the Spearman's rank correlation coefficients between the factor scores obtained using the revised version of the Romanian rPATD and scores on the Beliefs about Medicines Questionnaire (BMQ) Specific Concerns Romanian version. Floor and ceiling effect were also examined.

RESULTS

We translated the questionnaire and administered it to 224 participants (median age 72 years [interquartile range: 68.0; 77.0]). In the EFA individual items loaded onto 4 factors, grouped similarly to the English version (Involvement, Burden, Appropriateness, Concerns about Stopping factors). Two items from each of the Involvement and Appropriateness factors were removed to improve factor loading and avoid cross-loading. The Cronbach's alpha values for the 4 factors ranged between 0.522 and 0.773. The scores for Burden and Concerns about Stopping factors were found to be positively correlated with BMQ Specific Concerns score. We identified a ceiling effect for one of the four factors (Involvement) and no floor effects.

CONCLUSIONS

The Romanian rPATD was validated in 4 factor structure similar to the original English questionnaire. The Romanian version of the questionnaire may support the health care professionals in Romania to initiate and support patient-centered deprescribing.

Adverse drug reactions in the ambulatory internal patients at the emergency department: Focus on causality assessment and drug-drug interactions

A non-interventional retrospective study in ambulatory patients was conducted at the emergency department of the Division of internal medicine. In 2 months, 266 suspected adverse drug reactions (ADRs) were identified in 224/3453 patients (6.5 %). In 158/3453 patients (4.6 %), an ADR was the reason for emergency department visit and in 49 patients (1.4 %), ADRs led to hospitalisation. A causality assessment algorithm was developed, which included Naranjo algorithm and levels of ADR recognition by the treating physician and the investigators. Using this algorithm, 63/266 ADRs (23.7 %) were classified as "certain", whereas using solely the Naranjo score calculation, only 19/266 ADRs (7.1 %) were assessed as "probable" or "certain", and the rest of ADRs (namely, 247/266 = 92.9 %) were assessed as "possible". There were 116/266 (43.6 %) ADRs related to potential drug-drug interactions (DDIs), stated in at least one of the literature sources used. Based on the causality relationship, the rate of the clinically expressed DDIs was 19.0 %, or 12/63 "certain" ADR cases. Of these, 10 cases presented serious DDI-related ADRs. In summary, ADR causality assessment based exclusively on Naranjo algorithm demonstrated low sensitivity at an ambulatory emergency setting. Additional clinical judgment, including the opinion of the treating physician, proved necessary to avoid under-rating of the causality relationship, and enabled the determination of clinically expressed DDIs.

Assessment of community pharmacists' knowledge about drug-drug interactions in Jeddah, Saudi Arabia

Background: Drug-drug interactions (DDIs) have the potential to result in severe adverse drug events and profoundly affect patient outcomes. The pivotal role community pharmacists assume in recognizing and effectively managing these interactions necessitates a comprehensive understanding and heightened awareness of their implications. Such knowledge and awareness among community pharmacists are fundamental for ensuring the delivery of safe and efficacious care to patients. Aim: This study aimed to assess the knowledge of community pharmacists in Jeddah, Saudi Arabia, regarding drug-drug interactions (DDIs). Method: A cross-sectional survey was administered to a cohort of 147 community pharmacists through the utilization of a self-administered questionnaire. The questionnaire encompassed a comprehensive range of 30 multiple-choice questions, encompassing various facets pertaining to drug-drug interactions (DDIs). Results: A total of 147 community pharmacists working in Jeddah City, Saudi Arabia, completed the survey. The majority of them were male (89.1%, n = 131), and had bachelor's degrees in pharmacy. Results showed that the lowest correct response of DDIs was between Theophylline/Omeprazole, while the highest was between amoxicillin and acetaminophen. Results revealed that among the 28 drug pairs, only six pairs were determined correctly by most participants. The study found that majority of the studied community pharmacist could not determine the correct answer on drug-drug interaction knowledge, as also seen with the measured below half mean DDIs knowledge of 38.22 ± 22.0 (min = 0, max = 89.29, median = 35.71). Conclusion: The study highlights the need for ongoing training and education programs for community pharmacists in Saudi Arabia to enhance their knowledge and understanding of DDIs, ultimately leading to improved patient care and safety.

Adverse Drug Reactions during COVID-19 Treatment: A Comprehensive Analysis Focused on Hospitalized Patients, with the Use of a Survey in Cuba in 2020

Aims

To evaluate the prevalence and type of adverse drug reactions (ADRs), together with associated risk factors, among Cuban COVID-19 patients treated with chloroquine (CQ), lopinavir/ritonavir (LPV/r), or interferon α2b (IFN α2b), according to the Cuban protocol.

Materials and Methods

A prospective descriptive analysis of ADRs was performed on 200 COVID-19 patients who were admitted consecutively to three hospitals in Havana and Pinar del Río from April to July 2020. Information on demographics, ADRs, outcomes, behavioral, and health-related factors was collected using a validated questionnaire and clinical records. Each potential ADR case was assessed for causality based on the WHO-UMC algorithm, concomitant drug influences, and the presence of any drug-drug interactions (DDI).

Results

The total frequency of ADRs was 55%, with predominantly gastrointestinal disorders and general symptoms (23% vs 20%). 95.1% of ADRs occurred within 10 days after treatment and 42 potential DDI in 55.5% of patients (61/110) were observed. The prevalence of ADRs was: 44%, 30.4%, and 26.4% for IFN α2b, LPV/r, and CQ, respectively. Sex (odds ratio (OR): 0.40 (95% confidence interval (CI): 0.211-0.742), age (OR: 2.36 (95% CI: 1.02-5.44)), and underlying diseases (OR: 0.12 (95% CI: 0.06-0.23)) were independently associated factors for ADRs (P < 0.05).

Conclusions

The frequency of ADRs and potential DDI was high compared to their use during nonpandemic times (e.g., for malaria, HIV, or inflammatory diseases). The safety profile of these drugs when used for COVID-19 treatment showed similar characteristics. Comorbidities, age >37 years old, and female sex were associated with ADRs.

Potential Drug-Drug Interactions Among Hospitalised Elderly Patients in Northern Sri Lanka, A Lower Middle-Income Country: A Retrospective Analysis

BACKGROUND AND OBJECTIVES

Elderly individuals are more vulnerable to potential drug-drug interactions (pDDIs) as age-related physiological changes, polypharmacy and hospitalisations are known to increase the risk of pDDIs. The aims of this study were to assess the impact of hospitalisation and other associated factors on pDDIs in elderly patients, in a resource-limited setting.

METHODS

This is a retrospective analysis of data of elderly patients (aged ≥ 65 years) admitted to the medical units of Jaffna Teaching Hospital. Preadmission and post-admission data were collected from clinic and hospital records, respectively. The British National Formulary was used to identify and categorise pDDIs. Point prevalence of pDDIs in elderly patients and the total number of pDDIs before and after hospitalisation were estimated. Factors contributing to pDDIs were determined by univariate and multivariable logistic regression.

RESULTS

Two hundred and eighty-eight hospitalised elderly patients with a median age of 71 years (interquartile range 67-76 years) showed a significant increase in the prevalence of pDDIs post-admission compared with the preadmission values (77.1% vs 61.5%; p < 0.001) associated with an increase in total pDDIs (377 vs 488; p < 0.001) where the majority (> 75%) were potential pharmacodynamic interactions. An unadjusted analysis showed a significant association between pDDI and polypharmacy [taking five or more medications] (odds ratio [OR] = 14.17; 95% confidence interval [CI] 7.41-27.10), the presence of more than three underlying medical conditions (OR 4.14; 95% CI 1.70-10.06), ischaemic heart disease (OR 3.25; 95% CI 1.78-5.94) and asthma (OR 8.14; 95% CI 2.46-26.88). However, when adjusted for confounders only polypharmacy (OR 14.10; 95% CI 6.50-30.60) and the presence of underlying asthma (OR 11.61; 95% CI 2.82-47.85) were associated with pDDIs.

CONCLUSIONS

The prevalence of pDDIs among elderly patients was high and increased with hospital admissions. Polypharmacy and relevant comorbidities were contributory factors. Increased awareness of the potential for pDDIs through appropriate training and simple measures including a proper drug history, creating a bespoke pDDI list and frequent medication reviews by healthcare professionals would help to mitigate pDDIs in resource-limited and technology-limited settings.

A Survey of Medical Residents' Knowledge, Attitude, and Practice about Drug-Drug Interactions, Shiraz, Iran

Rationale, aims and objectives: Medical residents are among the most important and influential members of the medical team and the level of their knowledge regarding potential drug-drug interactions (DDIs) is a good predictor of the ability to prevent the occurrence of DDIs, as well as safe and rational prescribing in inpatient settings. This survey was designed to evaluate internal medicine and cardiology residents' knowledge and opinion toward DDIs and to determine different sources of DDI information used by this population. Method: This cross-sectional knowledge attitude practice (KAP) questionnaire study was conducted in Shiraz, Iran. A 25-question questionnaire was designed and completed by 86 internal medicine and cardiology residents. The questions were related to the participants' demographic information, their practice characteristics, the information sources used by the participants, the residents' opinion regarding DDIs, and their knowledge regarding the interaction between 8 drug pairs. Results: The results showed that when the participants wanted to learn more about DDIs, most of them used software on mobile or tablet (59.3%). Nearly three-fourths of the participants (73.82%) reported that when a patient was about to be exposed to a potential DDI, they were informed by software on mobile or tablet that the interaction may be present. On average, residents answered 44.03% ± 23.79 of drug pair questions correctly.Conclusion: Our results show insufficient practice skills, as well as relatively poor knowledge concerning the participants' answers to questions. It seems that further practical training and education are required to enable prescribers to prevent potential DDIs.

A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection

The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which provides effective and safe co-prescriptions of multiple drugs. Since laboratory researches are often complicated, costly and time-consuming, it's urgent to develop computational approaches to detect drug-drug interactions. In this paper, we conduct a comprehensive review of state-of-the-art computational methods falling into three categories: literature-based extraction methods, machine learning-based prediction methods and pharmacovigilance-based data mining methods. Literature-based extraction methods detect DDIs from published literature using natural language processing techniques; machine learning-based prediction methods build prediction models based on the known DDIs in databases and predict novel ones; pharmacovigilance-based data mining methods usually apply statistical techniques on various electronic data to detect drug-drug interaction signals. We first present the taxonomy of drug-drug interaction detection methods and provide the outlines of three categories of methods. Afterwards, we respectively introduce research backgrounds and data sources of three categories, and illustrate their representative approaches as well as evaluation metrics. Finally, we discuss the current challenges of existing methods and highlight potential opportunities for future directions.

Drug interactions in hospital prescriptions in Denmark: Prevalence and associations with adverse outcomes

Purpose

While the beneficial effects of medications are numerous, drug–drug interactions may lead to adverse drug reactions that are preventable causes of morbidity and mortality. Our goal was to quantify the prevalence of potential drug–drug interactions in drug prescriptions at Danish hospitals, estimate the risk of adverse outcomes associated with discouraged drug combinations, and highlight the patient types (defined by the primary diagnosis of the admission) that appear to be more affected.

Methods

This cross‐sectional (descriptive part) and cohort study (adverse outcomes part) used hospital electronic health records from two Danish regions (~2.5 million people) from January 2008 through June 2016. We included all inpatients receiving two or more medications during their admission and considered concomitant prescriptions of potentially interacting drugs as per the Danish Drug Interaction Database. We measured the prevalence of potential drug–drug interactions in general and discouraged drug pairs in particular during admissions and associations with adverse outcomes: post‐discharge all‐cause mortality rate, readmission rate and length‐of‐stay.

Results

Among 2 886 227 hospital admissions (945 475 patients; median age 62 years [IQR: 41–74]; 54% female; median number of drugs 7 [IQR: 4–11]), patients in 1 836 170 admissions were exposed to at least one potential drug–drug interaction (659 525 patients; median age 65 years [IQR: 49–77]; 54% female; median number of drugs 9 [IQR: 6–13]) and in 27 605 admissions to a discouraged drug pair (18 192 patients; median age 68 years [IQR: 58–77]; female 46%; median number of drugs 16 [IQR: 11–22]). Meropenem‐valproic acid (HR: 1.5, 95% CI: 1.1–1.9), domperidone‐fluconazole (HR: 2.5, 95% CI: 2.1–3.1), imipramine‐terbinafine (HR: 3.8, 95% CI: 1.2–12), agomelatine‐ciprofloxacin (HR: 2.6, 95% CI: 1.3–5.5), clarithromycin‐quetiapine (HR: 1.7, 95% CI: 1.1–2.7) and piroxicam‐warfarin (HR: 3.4, 95% CI: 1–11.4) were associated with elevated mortality. Confidence interval bounds of pairs associated with readmission were close to 1; length‐of‐stay results were inconclusive.

Conclusions

Well‐described potential drug–drug interactions are still missed and alerts at point of prescription may reduce the risk of harming patients; prescribing clinicians should be alert when using strong inhibitor/inducer drugs (i.e. clarithromycin, valproic acid, terbinafine) and prevalent anticoagulants (i.e. warfarin and non‐steroidal anti‐inflammatory drugs ‐ NSAIDs) due to their great potential for dangerous interactions. The most prominent CYP isoenzyme involved in mortality and readmission rates was 3A4.

A retrospective evaluation of drug–drug interactions in patients admitted to Internal Medicine Departments in Palestinian Hospitals

Objective:

To measure the prevalence and identify risk factors associated with drug–drug interactions among patients admitted to internal medicine departments in Palestinian hospitals

Methods:

A retrospective cross-sectional observational study was conducted. Data were obtained from patient files from the internal medicine departments in Palestinian hospitals from 1 September 2017, to 31 March 2018. The data collected included patient gender, age, length of hospitalization, medications prescribed, and the number of medications. The digital clinical decision support system IBM Micromedex® was used to assess potential drug–drug interactions.

Results:

The number of patients included in this study is 513. The total number of potential drug–drug interactions detected in study participants is 1558. The average number of potential drug–drug interactions per patient was found to be 3 ± 3.9. Among study participants, 66.1% (n = 339) were found to have potential drug–drug interactions in their current medications. The most commonly encountered drug–drug interactions type was “major” drug–drug interaction, which was encountered in 43.6% (n = 681) of total detected drug–drug interactions. Other types of drug–drug interactions were encountered in 42% (n = 647), 14% (n = 224), and 0.4% (n = 6) which were moderate, minor, and contraindicated drug–drug interactions, respectively. Patients’ age, number of medications, and length of hospitalization were associated with the increased risk of potential drug–drug interactions.

Conclusion:

The results indicated a high prevalence of potential drug–drug interactions in Palestinian hospitals, associated with polypharmacy, increased age, and increased length of hospitalization. Therefore, managing patient medication by a drug expert such as a clinical pharmacist to identify and resolve potential drug–drug interactions will possibly decrease the high prevalence of drug–drug interactions, prevent patient harm, and decrease the cost of hospitalization.

Drug–drug interactions among hospitalized elderly in patients at medical wards of Northwest Ethiopia’s Comprehensive Specialized Hospitals: A multicenter observational study

Objective:

Drug–drug interactions are of major concern due to links to untoward drug effects, hospitalizations, and serious health impacts. Elderly patients are more predisposed to drug interactions than younger patients. The present study aimed to find out the prevalence of drug–drug interactions at North West Ethiopian compressive specialized hospitals’ Internal Medicine wards.

Methods:

From 30 April to 30 July 2021 GC, a multicenter prospective observational study was conducted at north Ethiopian specialized hospitals. Data was collected by using a structured questionnaire adapted from different literature and medical records at the North West Ethiopian Comprehensive Specialized Hospitals’ Internal Medicine wards during the study period. Thereafter checked the completeness of the collected data was checked drug–drug interactions by using Medscape. Epi data version 4.6.2 software was used as data clearance and STATA version 14.1 was used for further data analysis.

Result:

A total of 389 subjects participated in the study of which more than half (55.53%) of them were female with a mean (SD) age of 68.9 ± 7.46 years. A total of 641 drug–drug interactions were detected in this investigation of which, 225(35.1%) were major, 299(46.6%) were significant interactions, and 117(18.3%) were minor interactions. Hospital stay (AOR = 5.95 CI: 3.49–10.12), retire (AOR = 6.71 CI: 1.26–35.78), 5–9 drugs (AOR = 5.30 CI: 2.91–9.67) and more than 10 drugs (AOR = 8.03 CI: 2.47–26.07) were important risk factors for drug–drug interactions.

Conclusion:

The findings of this study suggest that drug–drug interactions were high among hospitalized elderly patients. The presence of polypharmacy, to be retired, and hospital stayed were all found to be strongly linked with drug–drug interactions.

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.

STOPP-START Medication Review: A Non-Randomized Trial in an Indonesian Tertiary Hospital to Improve Medication Appropriateness and to Reduce the Length of Stay of Older Adults

Background: Inappropriate prescribing may lead to medication errors among older adults. Pharmacists can curb the occurrences of these errors by conducting medication reviews. Screening Tool of Older Person's Prescriptions (STOPP) or Screening Tool to Alert doctors to Right Treatments (START) may curb the incidence of adverse drug reactions and improve medication appropriateness by providing guides about when particular types of medications should be started or stopped. Objective: This study aimed to evaluate the use of STOPP/START to improve the Adapted Medication Appropriateness Index (MAI), to reduce the risk of ADRs (GerontoNet score), and length of stay (LOS). Setting: Geriatric Inpatient Ward, Sanglah General Hospital, Bali, Indonesia. Method: A non-randomized controlled trial was conducted in older adults (>60 years) who were selected consecutively from inpatient units in a tertiary hospital in Bali, Indonesia. The intervention group received medication reviews by pharmacists in collaboration with physicians to assess its appropriateness with STOPP/START criteria on admission and during their stay at the hospital. The control group obtained standard care. Main Outcome Measures: The outcomes were measured using the Adapted MAI, GerontoNet Score, and LOS. Results: Thirty patients in the intervention group and 33 patients in the control group were included in this study. The adapted MAI was 2.97 (2.25) and 9.94 (6.14) with P < .001. The GerontoNet score was 3.33 (2.28) and 5.18 (2.10) with P = .003, LOS was 7.63 (3.00) days and 14.18 (9.97) days with P = .011, respectively. Conclusion: The use of STOPP/START as a tool for medication review improved medication appropriateness and reduced ADR risk and LOS.

Randomized Trial to Improve Primary Care Patient Management and Patient Outcomes Using a Drug-Drug Interaction Test: Confirmation of the DECART Simulated Patient Clinical Utility Trial Results

Drug–drug interactions (DDIs) are a serious problem in the healthcare system, leading to excess healthcare utilization and costs. We conducted a second prospective randomized, controlled trial to further establish the real-world clinical utility of a novel assay that objectively identifies potentially serious DDIs in real-world patients. Re-recruiting primary care physicians (PCPs) from our first randomized, controlled, simulated-patients study on DDIs, we experimentally introduced a definitive, urine-based mass spectrometry test intervention that the physicians could use when caring for their eligible patients. Patients were eligible if taking four or more prescription medications or suspected of taking other non-prescribed substances with potential medication interactions. The primary outcome was whether DDI testing changed clinical care. We explored a secondary outcome to see if the change in practice improved symptoms in patients with potential DDIs. A total of 169 control and 162 intervention patients were enrolled in the study, and their medical records were abstracted. In real-world patients, intervention physicians identified and/or treated a DDI at 3.0x the rate in their patient population compared to controls (21.6% vs. 7.1%, p < 0.001). Intervention physicians were more likely to discontinue or adjust the interacting agent compared to controls (62.9% vs. 8.3%, p = 0.001), and patient-reported symptoms also significantly declined (29.6% vs. 20.1%, p = 0.045). These results were nearly identical to concurrent measurements that used simulated patients, wherein intervention was more likely to both make a DDI diagnosis (56.3% vs. 21.6%, p < 0.001) and stop the interacting medications (58.3% versus 26.6%, p < 0.001). Bringing a new diagnostic test to market, particularly for an under-recognized clinical problem, requires robust data on both clinical validity and clinical utility. The results of this follow-up study showed that the use of DDI testing in real-world patients significantly improved (1) primary care patient management of drug interactions and (2) patient outcomes.

High-priority drug-drug interaction clinical decision support overrides in a newly implemented commercial computerized provider order-entry system: Override appropriateness and adverse drug events

OBJECTIVE

The study sought to determine frequency and appropriateness of overrides of high-priority drug-drug interaction (DDI) alerts and whether adverse drug events (ADEs) were associated with overrides in a newly implemented electronic health record.

MATERIALS AND METHODS

We conducted a retrospective study of overridden high-priority DDI alerts occurring from April 1, 2016, to March 31, 2017, from inpatient and outpatient settings at an academic health center. We studied highest-severity DDIs that were previously designated as "hard stops" and additional high-priority DDIs identified from clinical experience and literature review. All highest-severity alert overrides (n = 193) plus a stratified random sample of additional overrides (n = 371) were evaluated for override appropriateness, using predetermined criteria. Charts were reviewed to identify ADEs for overrides that resulted in medication administration. A chi-square test was used to compare ADE rate by override appropriateness.

RESULTS

Of 16 011 alerts presented to providers, 15 318 (95.7%) were overridden, including 193 (87.3%) of the highest-severity DDIs and 15 125 (95.8%) of additional DDIs. Override appropriateness was 45.4% overall, 0.5% for highest-severity DDIs and 68.7% for additional DDIs. For alerts that resulted in medication administration (n = 423, 75.0%), 29 ADEs were identified (6.9%, 5.1 per 100 overrides). The rate of ADEs was higher with inappropriate vs appropriate overrides (9.4% vs 4.3%; P = .038).

CONCLUSIONS

The override rate was nearly 90% for even the highest-severity DDI alerts, indicating that stronger suggestions should be made for these alerts, while other alerts should be evaluated for potential suppression.

Prevalence and Clinical Significance of Drug-Drug and Drug-Dietary Supplement Interactions among Patients Admitted for Cardiothoracic Surgery in Greece

Background: Drug interactions represent a major issue in clinical settings, especially for critically ill patients such as those with cardiovascular disease (CVD) who require cardiothoracic surgery (CTS) and receive a high number of different medications. Methods: A cross-sectional study aimed at evaluating the exposure and clinical significance of drug–drug (DDIs) and drug–dietary supplement interactions (DDSIs) in patients admitted for CTS in the University Hospital of Crete Greece. DDIs were evaluated regarding underlying pharmacological mechanisms upon admission, preoperation, postoperation, and discharge from CTS clinic. Additionally, upon admission, the use of dietary supplements (DSs) and if patients had informed their treating physician that they were using these were recorded with subsequent analysis of potential DDSIs with prescribed medications. Results: The study employed 76 patients who were admitted for CTS and accepted to participate. Overall, 166 unique DDIs were identified, with 32% of them being related to pharmacokinetic (PK) processes and the rest (68%) were related to possible alterations of pharmacodynamic (PD) action. CVD medications and drugs for central nervous system disorders were the most frequently interacting medications. In total, 12% of the identified DDIs were of serious clinical significance. The frequency of PK-DDIs was higher during admission and discharge, whereas PD-DDIs were mainly recorded during pre- and postoperation periods. Regarding DS usage, 60% of patients were using DSs and perceived them as safe, and the majority had not informed their treating physician of this or sought out medical advice. Analysis of medical records showed 30 potential combinations with prescribed medications that could lead in DDSIs due to modulation of PK or PD processes, and grapefruit juice consumption was involved in 38% of them. Conclusions: An increased burden of DDIs and DDSIs was identified mostly upon admission for patients in CTS clinics in Greece. Healthcare providers, especially prescribing physicians in Greece, should always take into consideration the possibility of DDIs and the likely use of DS products by patients to promote their well-being; this should only be undertaken after receiving medical advice and an evidenced-based evaluation.

Assessment of Potential Drug–Drug Interactions and Their Predictors in Chronic Outpatient Department of Dessie Referral Hospital, Dessie, Northeast Ethiopia

Objective

To assess the prevalence and predictors of Potential drug–drug interactions (DDIs) at the chronic outpatient department of Dessie Referral Hospital, Dessie, Northeast Ethiopia.

Patients and Methods

A cross-sectional study was carried out on the medical records of patients treated in the chronic ambulatory department of Dessie Referral Hospital (DRH), from March 1/2019 to May 30/2019. Ethical clearance was granted from the department of pharmacy, college of medicine, and health sciences, Wollo University. Lexi-comp computer program database was used to detect pDDIs. SPSS version 22 was used to produce a descriptive analysis of the background data and logistic regression to identify predictors of pDDIs.

Results

In this study, the medical record of 300 patients has been reviewed and 489 pDDIs have been identified. The prevalence of pDDIs per patient was 1.63. Of all the identified pDDIs, the moderate severity interactions were the majority, 88.55% (n=433) followed by 8.38% (n=41) of minor, 2.66% (n=13) of major, and 0.41% (n=2) of contraindicated drug interactions. Taking three or more drugs at a time has been found as a statistically significant predictor of the occurrence of pDDIs.

Conclusion

A high rate of moderate severity pDDIs have been recorded. A system of checks and balances should be developed and executed for all those who are involved in prescribing, dispensing, and administration of medications for effective identification and prevention of pDDIs.

Towards The Automated, Empirical Filtering of Drug-Drug Interaction Alerts in Clinical Decision Support Systems: Historical Cohort Study of Vitamin K Antagonists

Background

Drug-drug interactions (DDIs) involving vitamin K antagonists (VKAs) constitute an important cause of in-hospital morbidity and mortality. However, the list of potential DDIs is long; the implementation of all these interactions in a clinical decision support system (CDSS) results in over-alerting and alert fatigue, limiting the benefits provided by the CDSS.

Objective

To estimate the probability of occurrence of international normalized ratio (INR) changes for each DDI rule, via the reuse of electronic health records.

Methods

An 8-year, exhaustive, population-based, historical cohort study including a French community hospital, a group of Danish community hospitals, and a Bulgarian hospital. The study database included 156,893 stays. After filtering against two criteria (at least one VKA administration and at least one INR laboratory result), the final analysis covered 4047 stays. Exposure to any of the 145 drugs known to interact with VKA was tracked and analyzed if at least 3 patients were concerned. The main outcomes are VKA potentiation (defined as an INR≥5) and VKA inhibition (defined as an INR≤1.5). Groups were compared using the Fisher exact test and logistic regression, and the results were expressed as an odds ratio (95% confidence limits).

Results

The drugs known to interact with VKAs either did not have a statistically significant association regarding the outcome (47 drug administrations and 14 discontinuations) or were associated with significant reduction in risk of its occurrence (odds ratio<1 for 18 administrations and 21 discontinuations).

Conclusions

The probabilities of outcomes obtained were not those expected on the basis of our current body of pharmacological knowledge. The results do not cast doubt on our current pharmacological knowledge per se but do challenge the commonly accepted idea whereby this knowledge alone should be used to define when a DDI alert should be displayed. Real-life probabilities should also be considered during the filtration of DDI alerts by CDSSs, as proposed in SPC-CDSS (statistically prioritized and contextualized CDSS). However, these probabilities may differ from one hospital to another and so should probably be calculated locally.

Potential drug-drug interactions in COVID 19 patients in treatment with lopinavir/ritonavir

Objectives

To determine the prevalence of potential interactions in COVID19 patients receiving lopinavir/ritonavir (LPV/r). The secondary objective was to develop recommendations and identify the risk factors associated with presenting potential interactions with LPV/r.

Subjects and methods

Cross-sectional and multicenter study with the participation of 2 hospitals. COVID 19 patients over 18 years of age, admitted to hospital and under treatment with LPV/r were included. A screening of potential interactions related to LPV/r and home and hospital medication was carried out. Lexicomp® (Uptodate), HIV-drug interactions and COVID-drug interactions were used as the query database.

Results

361 patients with a mean age of 62.77 ± 14.64 years were included, where 59.6% (n = 215) were men. 62.3% (n = 225) had 1 or more potential interactions and 26, 87% (n = 97) 2 or more. The independent variables associated with presenting ≥1 potential interactions were age (>65) (OR 1.95; 95% CI 1.06–3.59, P = .033), ICU admission (OR 9.22; CI 95% 1.98–42.93; P = .005), previous respiratory pathology (OR 2.90; 95% CI 1.15–7.36; P = .024), psychiatric (OR 4.14; 95 CI% 1.36–12.61; P = .013), dyslipidemia (OR 3.21; 95% CI 1.63–6.35; P = .001) and the number of drugs prescribed (OR 4.33; 95% CI 2.40–7.81; P = .000).

Conclusion

The prevalence of potential interactions in COVD 19 patient undergoing treatment with LPV/r is high, with age (>65), ICU admission, previous respiratory and psychiatric pathology, dyslipidemia and the number of prescribed drugs acting as risk factors.

Comparing drug interaction frequencies of various hepatitis C treatment regimens among monoinfected patients

INTRODUCTION AND OBJECTIVES

Four regimens are recommended for treating hepatitis C (HCV) genotype 1 infection. Study aims were to (1) compare frequencies of contraindicated drug interactions (XDDIs) when each HCV regimen is added to medication profiles of HCV-monoinfected patients, (2) quantify the proportion of patients with XDDIs to all four regimens and (3) determine covariates independently associated with having a XDDI to all four regimens.

MATERIALS AND METHODS

A cross-sectional study was performed within Upstate New York Veterans Healthcare Administration.

INCLUSION CRITERIA

(1) age ≥18 years, (2) HCV monoinfection and (3) available medication list. Data extracted were: demographics, comorbidities, and medication list. Primary outcome was XDDIs involving patient's home medications and each HCV regimen. University of Liverpool drug interaction website was used to define XDDIs. Two-way comparisons of regimens were performed using McNemar's test where p<0.0083 was considered statistically significant. Multivariate regression analyses were performed to determine predictors.

RESULTS

Of the 4047 subjects, mean±standard deviation age was 59.8±7.6. Median (interquartile range) number of medications used was 7 [4-11]. Frequencies of XDDIs after the addition of each regimen ranged from 2.8% to 17.8% and were mostly statistically different from one another. There were 95 (2.3%) patients with XDDIs to all four regimens. Predictors of having XDDIs to all four regimens were ≥6 medications and HCV infection ≥10 years.

CONCLUSION

The frequencies of XDDIs varied between HCV regimens. Number of medications and duration of HCV infection were predictors of having XDDIs to all four regimens.

[Potential drug-drug interactions in COVID 19 patients in treatment with lopinavir/ritonavir]

Objetivos

Determinar la prevalencia de interacciones potenciales en pacientes COVID-19 en tratamiento con lopinavir/ritonavir (LPV/r). El objetivo secundario fue elaborar recomendaciones e identificar los factores de riesgo asociados a presentar interacciones potenciales con LPV/r.

Sujetos y métodos

Estudio transversal y multicéntrico con la participación de 2 hospitales. Se incluyeron pacientes COVID-19 mayores de 18 años, con ingreso hospitalario y en tratamiento con LPV/r. Se realizó un cribado de las interacciones potenciales relacionadas con LPV/r y la medicación domiciliaria y hospitalaria. Se utilizó como base de datos de consulta Lexicomp® (Uptodate), HIV-drug interacctions y COVID-drug interacctions.

Resultados

Se incluyeron 361 pacientes con una media de edad de 62,77 ± 14,64 años, donde el 59,6% (n=215) fueron hombres. El 62,3% (n=225) tuvieron una o más interacciones potenciales y el 26, 87% (n=97) 2 o más. Las variables independientes asociadas a presentar ≥ 1 interacciones potenciales fueron la edad (> 65) (OR 1,95; IC 95% 1,06-3,59; P=0,033), el ingreso en UCI (OR 9,22; IC 95% 1,98-42,93; P=0,005), la enfermedad previa respiratoria (OR 2,90; IC 95% 1,15-7,36; P=0,024), psiquiátrica (OR 4,14; IC 95% 1,36-12,61; P=0,013), la dislipemia (OR 3,21; IC 95% 1,63-6,35; P=0,001) y el número de fármacos prescrito (OR 4,33; IC 95% 2,40-7,81; P=0,000).

Conclusión

La prevalencia de interacciones potenciales en paciente COVID-19 en tratamiento con LPV/r es elevada, comportándose como factores de riesgo asociados la edad (>65), el ingreso en UCI, la enfermedad previa respiratoria, psiquiátrica y la dislipemia y el número de fármacos prescritos.

Prevalence of clinically manifested drug interactions in hospitalized patients: A systematic review and meta-analysis

AIMS

This review aims to determine the prevalence of clinically manifested drug-drug interactions (DDIs) in hospitalized patients.

METHODS

PubMed, Scopus, Embase, Web of Science, and Lilacs databases were used to identify articles published before June 2019 that met specific inclusion criteria. The search strategy was developed using both controlled and uncontrolled vocabulary related to the following domains: "drug interactions," "clinically relevant," and "hospital." In this review, we discuss original observational studies that detected DDIs in the hospital setting, studies that provided enough data to allow us to calculate the prevalence of clinically manifested DDIs, and studies that described the drugs prescribed or provided DDI adverse reaction reports, published in either English, Portuguese, or Spanish.

RESULTS

From the initial 5,999 articles identified, 10 met the inclusion criteria. The pooled prevalence of clinically manifested DDIs was 9.2% (CI 95% 4.0-19.7). The mean number of medications per patient reported in six studies ranged from 4.0 to 9.0, with an overall average of 5.47 ± 1.77 drugs per patient. The quality of the included studies was moderate. The main methods used to identify clinically manifested DDIs were evaluating medical records and ward visits (n = 7). Micromedex® (27.7%) and Lexi-Comp® (27.7%) online reference databases were commonly used to detect DDIs and none of the studies evaluated used more than one database for this purpose.

CONCLUSIONS

This systematic review showed that, despite the significant prevalence of potential DDIs reported in the literature, less than one in ten patients were exposed to a clinically manifested drug interaction. The use of causality tools to identify clinically manifested DDIs as well as clinical adoption of DDI lists based on actual adverse outcomes that can be identified through the implementation of real DDI notification systems is recommended to reduce the incidence of alert fatigue, enhance decision-making for DDI prevention or resolution, and, consequently, contribute to patient safety.

Polypharmacy and drug-drug interactions among older and younger male prisoners in Switzerland

PURPOSE

The purpose of this paper is to determine the prevalence of polypharmacy and drug-drug interactions (DDIs) in older and younger prisoners, and compared if age group is associated with risks of polypharmacy and DDIs.

DESIGN/METHODOLOGY/APPROACH

For 380 prisoners from Switzerland (190 were 49 years and younger; 190 were 50 years and older), data concerning their medication use were gathered. MediQ identified if interactions of two or more substances could lead to potentially adverse DDI. Data were analysed using descriptive statistics and generalised linear mixed models.

FINDINGS

On average, older prisoners took 3.8 medications, while younger prisoners took 2.1 medications. Number of medications taken on one reference day was higher by a factor of 2.4 for older prisoners when compared to younger prisoners (p = 0.002). The odds of polypharmacy was significantly higher for older than for younger prisoners (>=5 medications: odds ratio = 5.52, p = 0.035). Age group analysis indicated that for potentially adverse DDI there was no significant difference (odds ratio = 0.94; p = 0.879). However, when controlling for the number of medication, the risk of adverse DDI was higher in younger than older prisoners, but the result was not significant.

ORIGINALITY/VALUE

Older prisoners are at a higher risk of polypharmacy but their risk for potentially adverse DDI is not significantly different from that of younger prisoners. Special clinical attention must be given to older prisoners who are at risk for polypharmacy. Careful medication management is also important for younger prisoners who are at risk of very complex drug therapies.

Are patients with a nasally placed feeding tube at risk of potential drug-drug interactions? A multicentre cross-sectional study

Aims

The primary aims were to determine the rate of potential drug-drug interactions (pDDIs) in patients with nasally placed feeding tubes (NPFT) and the factors significantly associated with pDDIs. The secondary aim was to assess the change in pDDIs for patients between admission and discharge.

Material and methods

This multicentre study applied a cross-sectional design and was conducted in six Brazilian hospitals, from October 2016 to July 2018. Data from patients with NPFT were collected through electronic forms. All regular medications prescribed were recorded. Medications were classified according to the World Health Organization (WHO) Anatomical Therapeutic Chemical code. Drug-drug interaction screening software was used to screen patients’ medications for pDDIs. Negative binomial regression was used to account for the over dispersed nature of the pDDI count. Since the number of pDDIs was closely related to the number of prescribed medications, we modelled the rate of pDDIs with the count of pDDIs as the numerator and the number of prescribed medications as the denominator; six variables were considered for inclusion: time (admission or discharge), patient age, patient gender, age-adjusted Charlson Comorbidity Index (CCI) score, type of prescription (electronic or handwritten) and patient care complexity. To account for correlation within the two time points (admission and discharge) for each patient a generalised estimating equations approach was used to adjust the standard error estimates. To test the change in pDDI rate between admission and discharge a full model of six variables was fitted to generate an adjusted estimate.

Results

In this study, 327 patients were included. At least one pDDI was found in more than 91% of patients on admission and discharge and most of these pDDIs were classified as major severity. Three factors were significantly associated with the rate of pDDIs per medication: patient age, patient care complexity and prescription type (handwritten vs electronic). There was no evidence of a difference in pDDI rate between admission and discharge.

Conclusion

Patients with a NPFT are at high risk of pDDIs. Drug interaction screening tools and computerized clinical decision support systems could be effective risk mitigation strategies for this patient group.

Characterization of potential drug-drug interactions in patients hospitalized in the intensive care unit of a tertiary hospital in Bogotá

Introduction: Drug-drug interactions occur more frequently in intensive care units than in other services. However, in Colombia, there are few studies on this problem in critically ill patients. Objectives: To characterize potential drug-drug interactions generated from prescriptions during hospitalization in an intensive care unit and to determine factors associated with their onset. Materials and methods: A retrospective cohort was assembled with patients hospitalized in an intensive care unit for a seven-month period. The daily prescription was assessed for potential drugdrug interactions using the Lexicomp® program. We calculated the incidence of interactions, classified them by type, severity, and level of documentation, and evaluated the factors associated with their onset using logistic regression. Results: The proportion of patients with at least one interaction was 84% while 87% had more than one interaction; the median was six interactions per patient. The most frequent was fentanyl and midazolam (23%). Moderate interactions were the most frequent by severity (77.6%) and by documentation (52.6%). The most common index and precipitating drugs were midazolam (12%) and fentanyl (10.6%), respectively. Age (OR=3.1) and the number of drugs (OR=11.8) were associated with the occurrence of interactions. Conclusions: Given their high frequency and potential negative impact, the systematic monitoring of prescriptions in intensive care units to detect interactions is important. Such monitoring contributes to the rational use of medicines and to improve the quality of care.

Measures of Drug Prescribing at Care Transitions in an Internal Medicine Unit

Care transitions represent a common source of drug errors and confusions. The purpose of our prospective observational study was to assess the prevalence of medication discrepancies at care transitions, along with potentially inappropriate medications and potential drug-drug interactions, in an internal medicine unit of an Italian hospital. Adverse drug reactions that occurred in the 30-day period after the discharge from the hospital were included. A related-samples McNemar test was performed for evaluating the effects of hospitalization on the above-mentioned measures of drug prescribing. Medication discrepancies were frequent both on admission (93.4% [95%CI 0.8749, 0.9713]) and at discharge (78.7% [95%CI 0.7035, 0.8558]), with a significant difference between transition times (-14.7% [95%CI -21.82%, -7.69%]; P < .001)]. A high potentially inappropriate medication use prevalence was revealed without differences between care transitions. Potential drug-drug interactions were more frequent at admission to the hospital, with a significant difference of 8.2% in the distribution of patients with potential drug-drug interactions between care transitions. None of the adverse drug reactions recorded on follow-up was related to unintentional discrepancies, and the prevalence rate of patients with potentially inappropriate medication-related adverse drug reactions ranged between 4.9% and 6.9%, and the prevalence rate of patients with drug-drug interaction-related adverse drug reactions was 4.1% of patients. This study is important to raise awareness of the potential dangers medication discrepancies, potentially inappropriate medications, and potential drug-drug interactions could have on older adults. Clinicians and clinical pharmacologists must collaborate to improve patient care and minimize drug-related clinical outcomes.

Preventable adverse drug events in critically ill HIV patients: Is the detection of potential drug-drug interactions a useful tool?

OBJECTIVES

The aim of this study was to develop a strategy to identify adverse drug events associated with drug-drug interactions by analyzing the prescriptions of critically ill patients.

METHODS

This retrospective study included HIV/AIDS patients who were admitted to an intensive care unit between November 2006 and September 2008. Data were collected in two stages. In the first stage, three prescriptions administered throughout the entire duration of these patients' hospitalization were reviewed, with the Micromedex database used to search for potential drug-drug interactions. In the second stage, a search for adverse drug events in all available medical, nursing and laboratory records was performed. The probability that a drug-drug interaction caused each adverse drug events was assessed using the Naranjo algorithm.

RESULTS

A total of 186 drug prescriptions of 62 HIV/AIDS patients were analyzed. There were 331 potential drug-drug interactions, and 9% of these potential interactions resulted in adverse drug events in 16 patients; these adverse drug events included treatment failure (16.7%) and adverse reactions (83.3%). Most of the adverse drug reactions were classified as possible based on the Naranjo algorithm.

CONCLUSIONS

The approach used in this study allowed for the detection of adverse drug events related to 9% of the potential drug-drug interactions that were identified; these adverse drug events affected 26% of the study population. With the monitoring of adverse drug events based on prescriptions, a combination of the evaluation of potential drug-drug interactions by clinical pharmacy services and the monitoring of critically ill patients is an effective strategy that can be used as a complementary tool for safety assessments and the prevention of adverse drug events.

Drug-drug interactions and their harmful effects in hospitalised patients: a systematic review and meta-analysis

PURPOSE

Drug-drug interactions (DDIs) are often avoidable and, if undetected, can lead to patient harm. This review aimed to determine the prevalence of potential DDIs (pDDIs), clinically relevant DDIs (DDIs that could lead to measurable patient harm, taking into account the patient's individual clinical profile) and DDIs that resulted in actual patient harm during hospitalisation.

METHOD

Four databases were scanned for English papers published from 2000 to 2016. Papers that reported prevalence of DDIs in the outpatient setting, at admission or discharge, involving only specific drugs, or in specific disease populations or age groups were excluded.

RESULTS

Twenty-seven papers met the inclusion criteria and were graded for quality using the Critical Appraisal Skills Programme (CASP) cohort study checklist. Ten papers were rated as 'poor', 14 as 'fair' and only three papers as 'good'. Overall, the meta-analysis revealed that 33% of general patients and 67% of intensive care patients experienced a pDDI during their hospital stay. It was not possible to determine the prevalence of clinically relevant DDIs or DDIs that resulted in actual patient harm as data on these categories were limited. Of the very few studies that reported on harm, only a small proportion of DDIs were found to have resulted in actual patient harm.

CONCLUSIONS

Standardisation of DDI definitions and research methods are required to allow meaningful prevalence rates to be obtained and compared. Studies that go further than measuring pDDIs are critically needed to determine the impact of DDIs on patient safety.

Potential drug-drug interactions in inpatients treated at the Internal Medicine ward of Tikur Anbessa Specialized Hospital

PURPOSE

Although the concomitant use of multiple drugs often increases therapeutic effectiveness, certain combinations result in unwanted drug-drug interactions (DDIs). Most interactions go unnoticed by physicians due to the absence of new clinical signs and symptoms, and because they often produce a worsening of already existing symptoms. Quantification of the occurrence of the potential DDIs is essential to prevent the harmful effects associated with interactions. This study was launched to assess the prevalence of potential DDIs in the Internal Medicine ward of Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia.

PATIENTS AND METHODS

Cross-sectional data were gathered from the medical charts of 252 randomly selected patients who were admitted to the Internal Medicine ward during August 23 to October 23, 2013, and exposed to at least two concomitant drugs. Potential DDIs were identified using Medscape Drug Interaction Checker. The data were analyzed using SPSS software. Logistic regression analysis was used to determine the presence of association between variables and p-value <0.05 was considered statistically significant.

RESULTS

At least one potential DDI was found in 78.2% of the patients. The mean number of potential interactions per patient was 3.7±3.4. Out of the 719 potential interactions identified, 49.8% were pharmacokinetic type, 44.6% were pharmacodynamic and the remaining 5.6% were unknown mechanisms. Major potential DDIs accounted for 13.1% of the whole interactions; 53.5% were moderate interactions; and the remaining 33.4% were minor interactions. Ceftriaxone, cimetidine and heparin were the three most involved drugs in major potential interactions. Prescription of five or more concomitant drugs was associated with high risk of encountering potential DDIs.

CONCLUSION

The findings of this study showed that the prevalence of potential DDIs among inpatients was high. Pharmacists should closely review drugs prescribed for patients and avoid dispensing combinations of drugs that may have serious DDIs.

Effect of Continuity of Care on Drug-Drug Interactions

BACKGROUND

Drug-drug interaction (DDI) is a critical concern in health care systems because it is directly associated with patient outcomes and is generally preventable. However, few studies have been conducted on whether poor continuity of care (COC) is a determinant of DDIs and whether this effect varies by level of comorbidity. Patients with higher comorbidity normally require more complex treatment regimens than other patients, and hence their COC is more critical for ensuring the accuracy of their medication information.

OBJECTIVE

This study investigated the association between COC and DDI, with COC being measured as physician and site COC. The effect of comorbidities on DDI events was also analyzed.

METHODS

The Taiwan National Health Insurance claims data of ∼1,000,000 randomly selected insurance beneficiaries were used. Each person was longitudinally followed from 2005 to 2013. Negative nominal regressions were estimated to determine the effect of COC on DDI.

RESULTS

Higher COC was found to decrease the risk of DDI, and this risk reduction was even greater with physician COC and a higher Charlson comorbidity index. In the 1-year observation interval, patients exhibited a 3% reduction in DDIs for every 0.1 increment in their COC index. The ability of COC to reduce DDIs increased with the level of comorbidity. Similar results were observed when the observation interval was increased.

CONCLUSIONS

Improving COC is critical for reducing DDIs. The effect of high-quality COC on the reduction of DDI is more significant for patients with higher levels of comorbidity; thus, they should be targeted to improve COC.

Drug Prescription Including Interactions with Anticancer Treatments in the Elderly: A Global Approach

BACKGROUND

Consequences of inappropriate prescriptions and polymedication in patients suffering from cancer are beginning to be well documented. However, the methods used to evaluate these consequences are often discussed. Few studies evaluate the risk of interaction with anticancer drugs in elderly patients suffering from cancer.

OBJECTIVES

To describe the prevalence (i) of polypharmacy, (ii) of potentially inappropriate drug prescriptions and (iii) of drug interactions involving anticancer treatments, using a multiple reference tools.

DESIGN

A retrospective, cross-sectional, multicenter study performed from January to December 2012.

PARTICIPANTS

Patients aged 65 years or older suffering from cancer presented at the oncogeriatric multidisciplinary meeting.

MEASUREMENTS

Polymedication (>6 drugs), potentially inappropriate prescriptions and drug interactions involving anticancer treatment were analyzed in combination with explicit and implicit criteria within a global approach.

RESULTS

Among the 106 patients included in this study, polypharmacy was present in 60.4% of cases, potentially inappropriate drug prescription in 63.1% and drug interactions in 16% of case, of which 47% involved anti-cancer treatments. Twenty-seven major drug interactions were identified and eight interactions involved chemotherapy.

CONCLUSION

Polymedication, inappropriate prescribing and drug interactions involving anti-cancer drugs are common and largely underestimated in elderly cancer patients.

Drug-drug interactions in the intensive care unit: Do they really matter?

PURPOSE

To describe prevalence and patterns of potential drug-drug interactions (pDDIs) in the intensive care unit (ICU), occurrence of adverse drug events (ADEs), and agreement between different compendia and intensivists' perceptions.

METHODS

A cross-sectional study. Drug profiles of all adult patients from 2 academic ICUs were screened on day 3 upon admission. We identified pDDIs using 3 compendia (Stockley's, Micromedex, and Epocrates) and documented their mechanism of action, clinical consequences, severity, level of evidence, and management. Medical records were searched to identify ADEs potentially related to major pDDIs. Agreement between information sources (compendia, intensivists) was evaluated.

RESULTS

We identified 1120 pDDIs among 275 patients. Median number of pDDIs per patient was 3.0 (interquartile range, 1-6), with 79% of patients presenting with at least 1 pDDI. Major pDDIs were detected in 18% of patients, with potentially related to ADEs in 4% of patients. Only 13% of all pDDIs were documented simultaneously in all 3 compendia. Different information sources (compendia, clinicians) showed "no" to "fair" agreement.

CONCLUSIONS

Potential drug-drug interactions occurred in most ICU patients, contrasting with low rates of potentially related ADEs, which may have been underestimated. Sources of information are inconsistent, challenging the identification of pDDIs.

Potentially severe drug-drug interactions among older people and associations in assisted living facilities in Finland: a cross-sectional study

OBJECTIVE

This study aims to assess potentially severe class D drug-drug interactions (DDDIs) in residents 65 years or older in assisted living facilities with the use of a Swedish and Finnish drug-drug interaction database (SFINX).

DESIGN

A cross-sectional study of residents in assisted living facilities in Helsinki, Finland.

SETTING

A total of 1327 residents were assessed in this study. Drugs were classified according to the Anatomical Therapeutic Chemical (ATC) classification system and DDDIs were coded according to the SFINX.

MAIN OUTCOME MEASURES

Prevalence of DDDIs, associated factors and 3-year mortality among residents.

RESULTS

Of the participants (mean age was 82.7 years, 78.3% were females), 5.9% (N = 78) are at risk for DDDIs, with a total of 86 interactions. Participants with DDDIs had been prescribed a higher number of drugs (10.8 (SD 3.8) vs. 7.9 (SD 3.7), p < 0.001). A larger proportion of residents with DDDIs suffered from rheumatoid arthritis or osteoarthritis than those not exposed to DDDIs (24.7% vs. 15.4%, p = 0.030). The most frequent DDDIs were related to the concomitant use of potassium with amiloride (N = 12) or spironolactone (N = 12). Carbamazepine (N = 13) and methotrexate (N = 9) treatments were also frequently linked to DDDIs. During the follow-up, no differences in mortality emerged between the participants exposed to DDDIs and the participants not exposed to DDDIs.

CONCLUSIONS

Of the residents in assisted living, 5.9% were exposed to DDDIs associated with the use of a higher number of drugs. Physicians should be trained to find safer alternatives to drugs associated with DDDIs. KEY POINTS   Potentially severe, class D drug-drug interactions (DDDIs) have been defined in the SFINX database as clinically relevant drug interactions that should be avoided.  • Of the residents in assisted living, 5.9% were exposed to DDDIs that were associated with the use of a higher number of drugs.  • The most frequent DDDIs were related to the concomitant use of potassium with amiloride or spironolactone. Carbamazepine and methotrexate were also linked to DDDIs.  • No difference in mortality was observed between residents exposed to DDDIs and residents not exposed to DDDIs.

Potential drug-drug interactions among elderly patients admitted to medical ward of Ayder Referral Hospital, Northern Ethiopia: a cross sectional study

BACKGROUND

The elderly are considered as special population, as they differ from younger adults in terms of comorbidity, polypharmacy, pharmacokinetics, vulnerability to drug-drug interactions and adverse drug reactions. Despite the fact that the elderly patients are at high risk of having drug interaction and potential adverse outcomes, studies in this regard are scarce in resource limited settings like Ethiopia. The aim of this study was to assess the prevalence and determinants of potential drug-drug interaction in elderly patients admitted to medical ward of Ayder Referral Hospital in Northern Ethiopia.

METHODS

A cross sectional study was conducted among elderly inpatients aged 60 years and above. The study was conducted from February to May 2014. Prescribed drugs being taken concurrently for at least 24 h were included and checked for drug-drug interaction using Micromedex® 2.0 online drug reference. Data were analyzed using statistical software, statistical package for social sciences for windows version 20. Logistic regression model was used to analyze factors associated with occurrence of drug interaction. P value of <0.05 was considered statistically significant.

RESULTS

A total of 140 patients were participated in the study. The mean age (±standard deviation) of participants was 68 (±7) years. Majority (61.4 %) of patients were diagnosed with cardiovascular and/or renal diseases. A total of 814 drugs were prescribed with a mean of 6 (±4) medications per patient during a 13 (±9) days of hospital stay. About two-third (62.2 %) of the respondents were exposed to at least one potential drug-drug interaction. Among these 3.6, 32.9 and 25.7 % of patients had taken contraindicated drug combination, at least one major and at least one moderate drug-drug interaction, respectively. Patients with five or more prescribed medications were four times at risk of having drug-drug interaction (P = 0.00; adjusted odds ratio 4.047; 95 % confidence interval 1.867-8.775).

CONCLUSION

Drug-drug interaction in elderly patients was common in this resource limited set-up. Awareness creation and clinical pharmacist involvement in minimizing the risk associated with potentially harmful drug combinations are needed.

The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy

Background

Estimate the expenditure of computer-related worktime resulting from the use of clinical decision support systems (CDSS) to prevent adverse drug reactions (ADR) among patients undergoing chronic pain therapy and compare the employed check systems with respect to performance and practicability.

Methods

Data were collected retrospectively from 113 medical records of patients under chronic pain therapy during 2012/2013. Patient-specific medications were checked for potential drug-drug interactions (DDI) using two publicly available CDSS, Apotheken Umschau (AU) and Medscape (MS), and a commercially available CDSS AiDKlinik® (AID). The time needed to analyze patient pharmacotherapy for DDIs was taken with a stopwatch. Measurements included the time needed for running the analysis and printing the results. CDSS were compared with respect to the expenditure of time and usability. Only patient pharmacotherapies with at least two prescribed drugs and fitting the criteria of the corresponding CDSS were analyzed. Additionally, a qualitative evaluation of the used check systems was performed, employing a questionnaire asking five pain physicians to compare and rate the performance and practicability of the three CDSSs.

Results

The AU tool took a total of 3:55:45 h with an average of 0:02:32 h for 93 analyzed patient regimens and led to the discovery of 261 DDIs. Using the Medscape interaction checker required a total of 1:28:35 h for 38 patients with an average of 0:01:58 h and a yield of 178 interactions. The CDSS AID required a total of 3:12:27 h for 97 patients with an average time of analysis of 0:01:59 h and the discovery of 170 DDIs. According to the pain physicians the CDSS AID was chosen as the preferred tool.

Conclusions

Applying a CDSS to examine a patients drug regimen for potential DDIs causes an average extra expenditure of work time of 2:09 min, which extends patient treatment time by 25 % on average. Nevertheless, the authors believe that the extra expenditure of time employing a CDSS is outweighed by their benefits, including reduced ADR risks and safer clinical drug management.

Impact of specific Beers Criteria medications on associations between drug exposure and unplanned hospitalisation in elderly patients taking high-risk drugs: a case-time-control study in Western Australia

BACKGROUND

Certain broad medication classes have previously been associated with high rates of hospitalisation due to related adverse events in elderly Western Australians, based on clinical coding recorded on inpatient summaries. Similarly, some medications from the Beers Criteria, considered potentially inappropriate in older people, have been linked with an increased risk of unplanned hospitalisation in this population.

OBJECTIVE

Our objective was to determine whether risk estimates of drug-related hospitalisations are altered in elderly patients taking 'high-risk drugs' (HRDs) when specific Beers potentially inappropriate medications (PIMS) are taken into consideration.

METHODS

Using the pharmaceutical claims of 251,305 Western Australians aged ≥65 years (1993-2005) linked with other health data, we applied a case-time-control design to estimate odds ratios (ORs) for unplanned hospitalisations associated with anticoagulants, antirheumatics, opioids, corticosteroids and four major cardiovascular drug groups, from which attributable fractions (AFs), number and proportion of drug-related admissions were derived. The analysis was repeated, taking into account exposure to eight specific PIMs, and results were compared.

RESULTS

A total of 1,899,699 index hospitalisations were involved. Of index subjects, 12-57 % were exposed to each HRD at the time of admission, although the proportions taking both an HRD and one of the selected PIMs were much lower (generally ≤2 %, but as high as 8 % for combinations involving temazepam and for most PIMs combined with hypertension drugs). Included PIMs (indomethacin, naproxen, temazepam, oxazepam, diazepam, digoxin, amiodarone and ferrous sulphate) all tended to increase ORs, AFs and drug-related hospitalisation estimates in HRD combinations, although this was less evident for opioids and corticosteroids. Indomethacin had the greatest overall impact on HRD ORs/AFs. Indomethacin (OR 1.40; 95 % confidence interval [CI] 1.27-1.54) and naproxen (OR 1.22; 1.14-1.31) were associated with higher risks of unplanned hospitalisation than other antirheumatics (overall OR 1.09; 1.06-1.12). Similarly, among cardiac rhythm regulators, amiodarone (OR 1.22; 1.13-1.32) was riskier than digoxin (OR 1.08; 1.04-1.13). For comparisons of drug-related hospitalisation estimates, temazepam yielded the greatest absolute increases, especially with hypertension drugs.

CONCLUSIONS

Indomethacin and temazepam should be prescribed cautiously in elderly patients, especially in drug combinations. Furthermore, it appears other antirheumatics should be favoured over indomethacin/naproxen and, in situations where both drugs may be appropriate, digoxin over amiodarone. Our methodology may help assess the safety of new medications in drug combinations in preliminary pharmacovigilance investigations.

Historical perspective of traditional indigenous medical practices: the current renaissance and conservation of herbal resources

In recent years, increasing numbers of people have been choosing herbal medicines or products to improve their health conditions, either alone or in combination with others. Herbs are staging a comeback and herbal “renaissance” occurs all over the world. According to the World Health Organization, 75% of the world's populations are using herbs for basic healthcare needs. Since the dawn of mankind, in fact, the use of herbs/plants has offered an effective medicine for the treatment of illnesses. Moreover, many conventional/pharmaceutical drugs are derived directly from both nature and traditional remedies distributed around the world. Up to now, the practice of herbal medicine entails the use of more than 53,000 species, and a number of these are facing the threat of extinction due to overexploitation. This paper aims to provide a review of the history and status quo of Chinese, Indian, and Arabic herbal medicines in terms of their significant contribution to the health promotion in present-day over-populated and aging societies. Attention will be focused on the depletion of plant resources on earth in meeting the increasing demand for herbs.

Detection of potential drug-drug interactions for outpatients across hospitals

The National Health Insurance Administration (NHIA) has adopted smart cards (or NHI-IC cards) as health cards to carry patients' medication histories across hospitals in Taiwan. The aims of this study are to enhance a computerized physician order entry system to support drug-drug interaction (DDI) checking based on a patient's medication history stored in his/her NHI-IC card. For performance evaluation, we developed a transaction tracking log to keep track of every operation on NHI-IC cards. Based on analysis of the transaction tracking log from 1 August to 31 October 2007, physicians read patients' NHI-IC cards in 71.01% (8,246) of patient visits; 33.02% (2,723) of the card reads showed at least one medicine currently being taken by the patient, 82.94% of which were prescribed during the last visit. Among 10,036 issued prescriptions, seven prescriptions (0.09%) contained at least one drug item that might interact with the currently-taken medicines stored in NHI-IC cards and triggered pop-up alerts. This study showed that the capacity of an NHI-IC card is adequate to support DDI checking across hospitals. Thus, the enhanced computerized physician order entry (CPOE) system can support better DDI checking when physicians are making prescriptions and provide safer medication care, particularly for patients who receive medication care from different hospitals.