Prevalence of drug-drug interactions at hospital entry and during hospital stay of patients in internal medicine

Improving thiamine prescribing in alcohol use disorder using electronic decision support in a large urban academic medical center: A pre-post intervention study

INTRODUCTION

Thiamine is the only therapy for prevention and treatment of Wernicke Encephalopathy among patients with Alcohol Use Disorder (AUD). Despite this fact, up to 75 % of inpatients with AUD are not prescribed thiamine during hospitalization. Even fewer patients are prescribed high-dose thiamine which many experts recommend should be standard of care. Previous attempts to improve thiamine prescribing for inpatients have had limited success.

METHODS

We conducted an evaluation of thiamine prescribing in the year before and year after an intervention to increase high-dose thiamine prescribing. Pre-post study analysis occurred on two distinct study cohorts: those with alcohol-related diagnoses and those with elevated alcohol levels. The intervention was new electronic health record-based decision support which encouraged high-dose thiamine when any thiamine order was sought. No educational support was provided. The primary outcome was prescription of high-dose thiamine before versus after intervention. Of those with alcohol-related diagnoses, the monthly percentage of thiamine treatment courses including high-dose thiamine were graphed on a control chart.

RESULTS

We examined 5307 admissions with alcohol-related diagnoses (2285 pre- and 3022 post-intervention) and 698 admissions with elevated alcohol levels (319 pre- and 379 post-intervention). Among admissions with alcohol-related diagnoses, the intervention was associated with a higher proportion of admissions receiving high-dose thiamine prescriptions in the first 24 h (4.7 % vs. 1.1 %, adjusted odds ratio 4.50, CI 2.93 to 6.89, p < 0.001). A similar difference in high-dose thiamine was seen post-intervention among admissions with elevated alcohol levels (14.3 % vs. 2.5 %, adjusted odds ratio 6.43, CI 3.05 to 13.53, p < 0.001). The control chart among those with an alcohol-related diagnosis demonstrated special cause variation: the median percentage of thiamine treatment courses including high-dose thiamine improved from 8.2 % to 13.0 %.

CONCLUSIONS

Electronic decision support without educational interventions increased the use of high-dose thiamine among patients with alcohol-related diagnoses and with elevated alcohol levels during hospitalization. This increase occurred immediately in the month after the intervention and was sustained in the year-long study period after.

A descriptive analysis of drug-drug interactions and corresponding adverse drug reactions in multimorbid older inpatients: findings from the SENATOR trial

PURPOSE

Drug-drug interactions (DDIs) are prevalent among multimorbid and polymedicated older adults and can increase the risk of adverse drug reactions (ADRs), hospital admissions, and mortality. This study describes the incidence and prevalence of 66 clinically relevant DDIs and analyses the occurrence of 12 corresponding predefined ADRs in older inpatients enrolled in the SENATOR trial.

METHODS

The sub-study of the SENATOR trial that involved 1537 multimorbid older inpatients, recruited from 2016 to 2018 in six academic teaching hospitals in Belgium, Iceland, Ireland, Italy, Scotland, and Spain respectively, and analysed 66 potentially clinically significant DDIs. Descriptive analysis determined DDI and corresponding ADR prevalence/incidence.

RESULTS

At baseline (median age: 78 [72, 84], 52.8% male), the prevalence of patients with DDIs was high (50.9%), increased during hospitalisation (55.2%) and reduced to 49.7% after 12 weeks. The most common DDIs were: ≥ 2 potassium reducing drugs (17.1%), ≥ 3 centrally acting drugs (9.0%), and SSRI + loop/thiazide diuretic (7.2%). Of all participants, one-third experienced a prevalent (36.6%)/incident (35.8%) ADR. Major serum electrolyte disturbance had the highest incidence (10.7%)/prevalence (11.5%). Incident ADRs were more common in patients with DDIs (p = 0.013). A higher prevalence of new onset falls (p = 0.013), major constipation (p = 0.004), and major serum electrolyte disturbances (p = 0.006) was observed in patients with related and thus potentially causal DDIs.

CONCLUSIONS

Clinicians should, be aware of DDIs and the involved drug classes that can lead to an increased rate of ADRs in older multimorbid inpatients. Regularly reevaluating the appropriateness of the frequently prescribed drug classes and initiating judicious deprescribing is recommended.

Drug-Drug Interactions in Hospitalized Urological Patients: A Retrospective Cohort Study

INTRODUCTION

Exposure to potential drug-drug interactions (pDDIs) can be a notable source of avoidable drug-related harm that requires adequate management to prevent medical errors. We aimed to evaluate pDDIs and associated factors in hospitalized urological patients on admission, during hospitalization, and on discharge.

METHODS

A retrospective cohort study was conducted at the Clinic of Urology of the University Clinical Centre Kragujevac, Serbia. To detect pDDIs, we used Lexicomp, which categorizes pDDIs as follows: X (avoid combination), D (consider therapy modification), C (monitor therapy), B (no action needed), and A (no known interaction). Multiple linear regression analysis was used to identify factors associated with the number of pDDIs.

RESULTS

More than half of the 220 included patients had at least one pDDI on admission and discharge (57.3% and 63.6%, respectively), whereas 95.0% had at least one pDDI during hospitalization. The total number and number of X, D, C, and B categories of pDDIs were the highest during hospitalization and the lowest on admission. Duration of hospitalization, arrhythmias, dementia, renal failure, cancer, surgery during hospitalization, number of prescribed drugs, and various pharmacological drug classes were risk factors for a higher number of pDDIs, while age, ischemic heart disease, hypertension, and development of infection during hospitalization were protective factors in at least one of the stages. The impact of renal colic depended on the stage and category of pDDI.

CONCLUSION

More than half of the urological patients were exposed to at least one pDDIs at all stages. Medical professionals should regularly screen for pDDIs, particularly in patients with risk factors.

Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship

Introduction

Digital clinical decision support (CDS) tools are of growing importance in supporting healthcare professionals in understanding complex clinical problems and arriving at decisions that improve patient outcomes. CDS tools are also increasingly used to improve antimicrobial stewardship (AMS) practices in healthcare settings. However, far fewer CDS tools are available in lowerand middle-income countries (LMICs) and in animal health settings, where their use in improving diagnostic and treatment decision-making is likely to have the greatest impact. The aim of this study was to evaluate digital CDS tools designed as a direct aid to support diagnosis and/or treatment decisionmaking, by reviewing their scope, functions, methodologies, and quality. Recommendations for the development of veterinary CDS tools in LMICs are then provided.

Methods

The review considered studies and reports published between January 2017 and October 2023 in the English language in peer-reviewed and gray literature.

Results

A total of 41 studies and reports detailing CDS tools were included in the final review, with 35 CDS tools designed for human healthcare settings and six tools for animal healthcare settings. Of the tools reviewed, the majority were deployed in high-income countries (80.5%). Support for AMS programs was a feature in 12 (29.3%) of the tools, with 10 tools in human healthcare settings. The capabilities of the CDS tools varied when reviewed against the GUIDES checklist.

Discussion

We recommend a methodological approach for the development of veterinary CDS tools in LMICs predicated on securing sufficient and sustainable funding. Employing a multidisciplinary development team is an important first step. Developing standalone CDS tools using Bayesian algorithms based on local expert knowledge will provide users with rapid and reliable access to quality guidance on diagnoses and treatments. Such tools are likely to contribute to improved disease management on farms and reduce inappropriate antimicrobial use, thus supporting AMS practices in areas of high need.

The Prevalence and Severity of Potential Drug-Drug Interactions in Internal Medicine Ward at Soba Teaching Hospital

Background

Multiple drug therapies are commonly used to achieve a desired therapeutic goal, especially in hospitalized patients. However, drug-drug interactions might occur and threaten the patients' safety.

Objective

This study aims to assess the prevalence and severity of potential drug-drug interactions (PDDIs) in the internal medicine ward at Soba Teaching Hospital.

Methods

A retrospective cross-sectional hospital-based study was carried out in the internal medicine ward at Soba Teaching Hospital from June 2021 to December 2021. The data was collected from patients' medical records. PDDIs were identified using Lexicomp® drug interaction software.

Results

A total of 377 patients were included in this study, and overall prevalence of PDDIs was 62.9%. We have identified 989 potential DDIs and 345 pairs of interacting drugs, the mean of the PDDIs per patient was 4.17 ± 4.079. Among 345 PDDIs most were of moderate interactions 70.1% (n=242) followed by Minor interactions 19.1% (n=66). The most common type of interaction was of category C representing 63.5% (n=219). A significant association was observed between the occurrence of PDDIs with patients' age, presence of chronic diseases, length of hospital stay, and number of medications received by the patients.

Conclusion

Drug-drug interactions were highly prevalent in the internal medicine ward. Therefore, certain attempts are required to increase the awareness of the physicians about these interactions and minimize their occurrence.

Barriers to Adoption of Tailored Drug-Drug Interaction Clinical Decision Support

OBJECTIVE

Despite the benefits of the tailored drug-drug interaction (DDI) alerts and the broad dissemination strategy, the uptake of our tailored DDI alert algorithms that are enhanced with patient-specific and context-specific factors has been limited. The goal of the study was to examine barriers and health care system dynamics related to implementing tailored DDI alerts and identify the factors that would drive optimization and improvement of DDI alerts.

METHODS

We employed a qualitative research approach, conducting interviews with a participant interview guide framed based on Proctor's taxonomy of implementation outcomes and informed by the Theoretical Domains Framework. Participants included pharmacists with informatics roles within hospitals, chief medical informatics officers, and associate medical informatics directors/officers. Our data analysis was informed by the technique used in grounded theory analysis, and the reporting of open coding results was based on a modified version of the Safety-Related Electronic Health Record Research Reporting Framework.

RESULTS

Our analysis generated 15 barriers, and we mapped the interconnections of these barriers, which clustered around three entities (i.e., users, organizations, and technical stakeholders). Our findings revealed that misaligned interests regarding DDI alert performance and misaligned expectations regarding DDI alert optimizations among these entities within health care organizations could result in system inertia in implementing tailored DDI alerts.

CONCLUSION

Health care organizations primarily determine the implementation and optimization of DDI alerts, and it is essential to identify and demonstrate value metrics that health care organizations prioritize to enable tailored DDI alert implementation. This could be achieved via a multifaceted approach, such as partnering with health care organizations that have the capacity to adopt tailored DDI alerts and identifying specialists who know users' needs, liaise with organizations and vendors, and facilitate technical stakeholders' work. In the future, researchers can adopt the systematic approach to study tailored DDI implementation problems from other system perspectives (e.g., the vendors' system).

The importance of graph databases and graph learning for clinical applications

The increasing amount and complexity of clinical data require an appropriate way of storing and analyzing those data. Traditional approaches use a tabular structure (relational databases) for storing data and thereby complicate storing and retrieving interlinked data from the clinical domain. Graph databases provide a great solution for this by storing data in a graph as nodes (vertices) that are connected by edges (links). The underlying graph structure can be used for the subsequent data analysis (graph learning). Graph learning consists of two parts: graph representation learning and graph analytics. Graph representation learning aims to reduce high-dimensional input graphs to low-dimensional representations. Then, graph analytics uses the obtained representations for analytical tasks like visualization, classification, link prediction and clustering which can be used to solve domain-specific problems. In this survey, we review current state-of-the-art graph database management systems, graph learning algorithms and a variety of graph applications in the clinical domain. Furthermore, we provide a comprehensive use case for a clearer understanding of complex graph learning algorithms. Graphical abstract.

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.

Factors associated with a basic common drug-drug interaction knowledge among emergency department medical personnel

Background

Drug-drug interactions (DDIs) are common but less concerning in clinical practice of time-sensitive situations. We aimed to identify factors associated with a basic common DDI knowledge among an emergency physician (EP), an emergency medicine resident (EMR), and an emergency care nurse (ECN).

Methods

This was a prospective cross-sectional study. EP, EMR, and ECN did the examination (multiple-choice questions, 40 points) about common DDI. Prespecified factors associated with examination scores were profession, longer emergency medicine experience, pharmacological training, last advanced cardiovascular life support (ACLS) training, DDI checker book, and application user experience. The outcome was an examination score to evaluate the ability of DDI knowledge. Univariable and multivariable means regressions were used.

Results

A total of 244 participants were enrolled. Factors associated with high examination score were EP (unadjusted mean difference 3.3 points, 95% confidence interval [CI] 2.1 to 4.5, p < 0.001), EMR (2.1, 95% CI 0.7 to 3.5, p 0.005) compared to ECN. Last ACLS training within 2 years (3.7, 95% CI 0.7 to 6.6, p 0.015), 2–4 years (3.4, 95% CI 0.4 to 6.5, p 0.027), and ≥4 years (4.4, 95% CI 1.2 to 7.6, p 0.007) were higher score than no ACLS training. Moreover, the DDI checker application experience user (1.7, 95% CI 0.6 to 2.8, p 0.003) also had a high score compared to the non-experienced user. After adjustment for all factors, EP (adjusted mean difference 3.3 points, 95% CI 1.8 to 4.7, p < 0.001), EMR (2.5, 95% CI 0.6 to 4.3, p 0.010) were higher scores compared to ECN. Meanwhile, the last ACLS training ≥4 years (3.3, 95% CI 0.1 to 6.6, p 0.042) was a higher score than no ACLS training.

Conclusion

EP, EMR, and the last ACLS training ≥4 years were associated with higher DDI knowledge than ECN and no ACLS training, respectively.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40360-022-00623-0.

Contextualized Drug-Drug Interaction Management Improves Clinical Utility Compared With Basic Drug-Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context‐dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI‐CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P < 0.01), with 4.0 PIs/1,000 MOs (P < 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management.

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.

Risk Factors for the Occurrence of Potential Drug-Drug Interactions in Surgical Patients

Background: Drug-drug interactions are defined as modifications of the drug action that result from the simultaneous administration of another individual drug or several drugs. Nowadays, potential drug-drug interactions (DDIs) are most frequently detected and analyzed using personal digital assistant software programs (online interaction checker tools).

Objective: To determine the risk factors for the emergence of all drug-drug interactions in surgical patients with particular emphasis on clinically significant interactions.

Patients and methods: This was a retrospective cohort analysis of patients treated at the Surgical Clinic of the Clinical Center Kragujevac. Three interaction checkers were used to reveal drug-drug interactions: Medscape, Epocrates and Micromedex.

Results: The study included total of 200 patients, aged 58.54±17.08 years. Average number of drug-drug interactions per patient was between 10.50±9.10 (Micromedex) and 18.75±17.14 (Epocrates). Number of prescribed drugs, antidepressive therapy, antiarrhythmic therapy, number of pharmacological/therapeutic subgroups (2nd level of ATC classification) prescribed, delirium or dementia, diabetes, heart failure, and number of physicians who prescribed drugs to single patient were identified as risk factors for drug-drug interactions while length of hospitalization in days and age of patient in years emerged as protective factors.

Conclusion: Drug-drug interactions are relatively common in surgical patients and predisposed by factors such as number of prescribed drugs or drug group per patient, number of physicians who prescribed drugs, antidepressive therapy, antiarrhythmic therapy, presence of delirium or dementia, diabetes and heart failure. On the other hand, prolonged hospitalization and higher age are factors that reduce the risk of interactions in surgical patients.

Assessing Knowledge of Pharmacokinetics in an Integrated Medical Curriculum

Pharmacokinetics is the branch of pharmacology that describes how the body processes drugs. As most physicians will prescribe drugs during their career, knowledge of pharmacokinetics is indispensable for medical students. Students, however, experience pharmacokinetics as difficult, probably due to its abstract and mathematical nature. In many medical curricula, pharmacokinetic topics are taught and examined as a part of integrated medical courses. As pharmacokinetics is a relatively small subject, unit examinations contain only few questions on the topic. The combination of a difficult subject and a few questions has raised concerns that students could perform poorly in pharmacokinetics and still pass the examinations and, hence, end up with insufficient knowledge of pharmacokinetics. In this study, we investigate this issue by contrasting students' performance on pharmacokinetics questions with their performance on the rest of the examinations (all non-pharmacokinetics questions lumped together). The results expressed as pass-fail scores showed that students failed more often on the pharmacokinetics part of the test than on the other questions, in two consecutive academic years. Despite the suboptimal knowledge in pharmacokinetics, students can still acquire their bachelor's degree. These results show that poor knowledge in pharmacokinetics could be a side effect of curricular integration. Attention should therefore be paid to provide insight into one's own performance in individual disciplines. This would avoid knowledge deficiency and incompetence in the future.

Clinical Decision Support Systems

BACKGROUND

By combining up-to-date medical knowledge and steadily increasing patient data, a new level of medical care can emerge.

SUMMARY AND KEY MESSAGES

Clinical decision support systems (CDSSs) are an arising solution to handling rich data and providing them to health care providers in order to improve diagnosis and treatment. However, despite promising examples in many areas, substantial evidence for a thorough benefit of these support solutions is lacking. This may be due to a lack of general frameworks and diverse health systems around the globe. We therefore summarize the current status of CDSSs in medicine but also discuss potential limitations that need to be overcome in order to further foster future development and acceptance.

Prevalence of drug-drug interactions in older people before and after hospital admission: analysis from the OPERAM trial

Background

Drug-drug interactions (DDIs) are highly prevalent in older patients but little is known about prevalence of DDIs over time. Our main objective was to assess changes in the prevalence and characteristics of drug-drug interactions (DDIs) during a one-year period after hospital admission in older people, and associated risk factors.

Methods

We conducted a sub-study of the European OPERAM trial (OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people), which assessed the effects of a structured medication review (experimental arm) compared to usual care (control arm) on reducing drug-related hospital readmissions. All OPERAM patients (≥70 years, with multimorbidity and polypharmacy, hospitalized in four centers in Bern, Brussels, Cork and Utrecht between December 2016 and October 2018, followed over 1 year) who were alive at hospital discharge and had full medication data during the index hospitalization (at baseline i.e., enrolment at admission, and at discharge) were included. DDIs were assessed using an international consensus list of potentially clinically significant DDIs in older people. The point-prevalence of DDIs was evaluated at baseline, discharge, and at 2, 6 and 12 months after hospitalization. Logistic regression models were performed to assess independent variables associated with changes in DDIs 2 months after baseline.

Results

Of the 1950 patients (median age 79 years) included, 1045 (54%) had at least one potentially clinically significant DDI at baseline; point-prevalence rates were 58, 57, 56 and 57% at discharge, and 2, 6 and 12 months, respectively. The prevalence increased significantly from baseline to discharge (P < .001 [significant only in the control group]), then remained stable over time (P for trend .31). The five most common DDIs –all pharmacodynamic in nature– accounted for 80% of all DDIs and involved drugs that affect potassium concentrations, centrally-acting drugs and antithrombotics. At 2 months, DDIs had increased in 459 (27%) patients and decreased in 331 (19%). The main factor predictive of a change in the prevalence of DDIs was hyperpolypharmacy (≥10 medications).

Conclusions

DDIs were very common; their prevalence increased during hospitalization and tended to remain stable thereafter. Medication review may help control this increase and minimize the risk of adverse drug events.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02532-z.

Prescription of Potentially Inappropriate Medication in Older Inpatients of an Internal Medicine Ward: Concordance and Overlap Among the EU(7)-PIM List and Beers and STOPP Criteria

Background: Age-related comorbidities prone older adults to polypharmacy and to an increased risk of potentially inappropriate medication (PIM) use. This work aims to analyze the concordance and overlap among the EU(7)-PIM list, 2019 Beers criteria, and Screening Tool of Older Person’s Prescriptions (STOPP) version 2 criteria and also to analyze the prevalence of PIM.

Methods: A retrospective cohort study was conducted on older inpatients of an internal medicine ward. Demographic, clinical, and pharmacological data were collected, during March 2020. After PIM identification by the EU(7)-PIM list, Beers criteria, and STOPP v2 criteria, the concordance and overlap between criteria were analyzed. A descriptive analysis was performed, and all the results with a p-value lower than 0.05 were considered statistically significant.

Results: A total of 616 older patients were included in the study whose median age was 85 (Q1–Q3) (78–89) years. Most of the older patients were male (51.6%), and the median (Q1–Q3) number of days of hospitalization was 17 (13–22) days. According to the EU(7)-PIM list, Beers criteria, and STOPP criteria, 79.7, 92.0, and 76.5% of older adults, respectively, used at least one PIM. A poor concordance (<63.4%) among criteria was observed. An association between PIM and the number of prescribed medicines was found in all applied criteria. Moreover, an association between the number of PIMs and diagnoses of endocrine, nutritional, and metabolic diseases, mental, behavioral, and neurodevelopmental disorders, and circulatory system diseases and days of hospitalization was observed according to Beers criteria, and that with diseases of the circulatory system and musculoskeletal system and connective tissue was observed according to STOPP criteria.

Conclusion: Despite the poor concordance between the EU(7)-PIM list, 2019 Beers, and STOPP v2 criteria, this work highlights the need for more studies in inpatients to develop strategies to facilitate the identification of PIM to decrease the high prevalence of PIM in hospitalized patients. The poor concordance among criteria also highlights the need to develop new tools adapting the existing criteria to medical ward inpatients.

Potentially inappropriate medications and medication combinations before, during and after hospitalizations: an analysis of pathways and determinants in the Swiss healthcare setting

Background

A hospitalization phase represents a challenge to medication safety especially for multimorbid patients as acute medical needs might interact with pre-existing medications or evoke adverse drug effects. This project aimed to examine the prevalence and risk factors of potentially inappropriate medications (PIMs) and medication combinations (PIMCs) in the context of hospitalizations.

Methods

Analyses are based on claims data of patients (≥65 years) with basic mandatory health insurance at the Helsana Group, and on data from the Hirslanden Swiss Hospital Group. We assessed PIMs and PIMCs of patients who were hospitalized in 2013 at three different time points (quarter prior, during, after hospitalization). PIMs were identified using the PRISCUS list, whereas PIMCs were derived from compendium.ch. Zero-inflated Poisson regression models were applied to determine risk factors of PIMs and PIMCs.

Results

Throughout the observation period, more than 80% of patients had at least one PIM, ranging from 49.7% in the pre-hospitalization, 53.6% in the hospitalization to 48.2% in the post-hospitalization period. PIMCs were found in 46.6% of patients prior to hospitalization, in 21.3% during hospitalization, and in 25.0% of patients after discharge. Additional medication prescriptions compared to the preceding period and increasing age were the main risk factors, whereas managed care was associated with a decrease in PIMs and PIMCs.

Conclusion

We conclude that a patient’s hospitalization offers the possibility to increase medication safety. Nevertheless, the prevalence of PIMs and PIMCs is relatively high in the study population. Therefore, our results indicate a need for interventions to increase medication safety in the Swiss healthcare setting.

Drug safety in hospitalized patients with tuberculosis: Drug interactions and adverse drug effects

BACKGROUND

Hospitalized patients with tuberculosis (TB) are prescribed with drugs having high risk of potential drug-drug interactions (pDDIs) and adverse drug effects (ADEs).

OBJECTIVES

To explore the adverse effects of anti-tuberculosis (anti-TB) drugs and the prevalence and predictors of pDDIs in hospitalized patients with TB.

METHODS

Clinical profiles of 436 TB patients were reviewed for adverse effects induced by anti-TB drugs and screened for pDDIs using Micromedex-DrugReax. Prevalence and severity levels of pDDIs were reported. Odds ratios for predictors were calculated using logistic regression analysis.

RESULTS

Of total 436 patients, adverse effects of anti-TB drugs were found in 36%. ADEs were highly prevalent in patients with high doses of anti-TB drugs. Hepatotoxicity, neuropathy, insomnia, arthralgia, psychosis, hematological alterations, skin rashes, red color stool, diplopia, and photophobia were the identified ADEs. All drugs types- and anti-TB drugs-pDDIs were reported in 78.2% and 55.7%, respectively. Major-pDDIs of anti-TB drugs were identified in 55.5%. Total 1090 anti-TB drugs pDDIs were found, among them, 55.6% were of major- and 40.5% were of moderate-severity. Significant association was observed for the pDDIs with ≥7 prescribed medicines (P < 0.001). Potential adverse outcomes of the most frequent interactions were hepatotoxicity, decreased drug's effectiveness, QT-interval prolongation, nephrotoxicity, and gastrointestinal ulceration.

CONCLUSIONS

Patients with TB present with a considerable number of clinically important pDDIs and ADEs (particularly hepatotoxicity). TB patients should be monitored for adverse effects of anti-TB drugs. Attention should be given to major-pDDIs. Patients more at risk to interactions should be identified and monitored for related adverse outcomes.

Redefining Medication Management in Dialysis: A Kidney Pharmacy Quality Pyramid

Patients with end-stage renal disease treated with dialysis are often prescribed complex medication regimens, placing them at risk for drug-drug interactions and other medication-related problems. Particularly in the context of a broader interest in more patient-centered value-based care, improving medication management is an increasingly important focus area. However, current medication management metrics, designed for the broader patient population, may not be well suited to the specific needs of patients with kidney disease, especially given the complexity of medication regimens used by dialysis patients. We propose a kidney pharmacy-focused quality pyramid that is intended to provide a framework to guide dialysis organizations, health care providers, and/or clinicians with respect to an optimal medication management approach for dialysis patients. Incorporation of core programs in medication management, including medication reconciliation, safety programs, and medication therapy management for patients at high risk for medication-related problems, may result in improved outcomes. Although a growing body of evidence supports the concept that active medication management can improve medication adherence and reduce medication-related problems, these strategies are viewed as costly and are not widely deployed. However, if done effectively, pharmacy-led medication management has the potential to be one of the more cost-effective disease management strategies and may greatly improve outcomes for these complex patients.

Evaluation of potential drug-drug interactions in a pediatric population

Aim:

A large number of medications are prescribed in pediatric clinics and this leads to the development of drug–drug interactions (DDI) that may complicate the course of the disease. The aim of the study was to identify the prevalence of potential drug–drug interactions, to categorize main drug classes involved in severe drug–drug interactions and to highlight clinically relevant DDIs in a pediatric population.

Material and Methods:

A total of 1500 prescriptions during the 12-month study period were retrospectively reviewed; 510 prescriptions that comprised two or more drugs were included in study. The presence of potential drug–drug interactions was identified by using the Lexi-Interact database and categorized according to severity A (unknown), B (minor), C (moderate), D (major), and X (contraindicated).

Results:

There were 1498 drugs in 510 prescriptions; 253 of these (49.6%) included 2 drugs, 228 (44.7%) included 3–4 drugs, and 29 (5.6%) included ≥5 drugs. A total of 634 (42%) potential drug–drug interactions were idenfied. Among those, 271 (42.7%) were categorized as A, 284 (44.8%) as B, 53 (8.4%) as C, and 26 (4.1%) as D. There was no potential risk for X interaction. Anti-infectives (36%) were the most commonly prescribed drug classes involved in C and/or D categories. Clarithromycin was the most commonly interacting agent that interfered with budesonide.

Conclusion:

It is noteworthy that a significant number of drugs causing potential drug–drug interactions are prescribed together in pediatric clinics. Increasing the awareness of physicians on this issue will prevent potential complications and ensure patient safety.

An overview of clinical decision support systems: benefits, risks, and strategies for success

Computerized clinical decision support systems, or CDSS, represent a paradigm shift in healthcare today. CDSS are used to augment clinicians in their complex decision-making processes. Since their first use in the 1980s, CDSS have seen a rapid evolution. They are now commonly administered through electronic medical records and other computerized clinical workflows, which has been facilitated by increasing global adoption of electronic medical records with advanced capabilities. Despite these advances, there remain unknowns regarding the effect CDSS have on the providers who use them, patient outcomes, and costs. There have been numerous published examples in the past decade(s) of CDSS success stories, but notable setbacks have also shown us that CDSS are not without risks. In this paper, we provide a state-of-the-art overview on the use of clinical decision support systems in medicine, including the different types, current use cases with proven efficacy, common pitfalls, and potential harms. We conclude with evidence-based recommendations for minimizing risk in CDSS design, implementation, evaluation, and maintenance.

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.

Optimising computerised decision support to transform medication safety and reduce prescriber burden: study protocol for a mixed-methods evaluation of drug-drug interaction alerts

INTRODUCTION

Drug-drug interaction (DDI) alerts in hospital electronic medication management (EMM) systems are generated at the point of prescribing to warn doctors about potential interactions in their patients' medication orders. This project aims to determine the impact of DDI alerts on DDI rates and on patient harm in the inpatient setting. It also aims to identify barriers and facilitators to optimal use of alerts, quantify the alert burden posed to prescribers with implementation of DDI alerts and to develop algorithms to improve the specificity of DDI alerting systems.

METHODS AND ANALYSIS

A controlled pre-post design will be used. Study sites include six major referral hospitals in two Australian states, New South Wales and Queensland. Three hospitals will act as control sites and will implement an EMM system without DDI alerts, and three as intervention sites with DDI alerts. The medical records of 280 patients admitted in the 6 months prior to and 6 months following implementation of the EMM system at each site (total 3360 patients) will be retrospectively reviewed by study pharmacists to identify potential DDIs, clinically relevant DDIs and associated patient harm. To identify barriers and facilitators to optimal use of alerts, 10-15 doctors working at each intervention hospital will take part in observations and interviews. Non-identifiable DDI alert data will be extracted from EMM systems 6-12 months after system implementation in order to quantify alert burden on prescribers. Finally, data collected from chart review and EMM systems will be linked with clinically relevant DDIs to inform the development of algorithms to trigger only clinically relevant DDI alerts in EMM systems.

ETHICS AND DISSEMINATION

This research was approved by the Hunter New England Human Research Ethics Committee (18/02/21/4.07). Study results will be published in peer-reviewed journals and presented at local and international conferences and workshops.

Potential drug-drug interactions and associated factors among hospitalized cardiac patients at Jimma University Medical Center, Southwest Ethiopia

Background

Concomitant use of several drugs for a patient is often imposing increased risk of drug-drug interactions. Drug-drug interactions are a major cause for concern in patients with cardiovascular disorders due to multiple co-existing conditions and the wide class of drugs they receive. This study is aimed to assess the prevalence of potential drug-drug interactions and associated factors among hospitalized cardiac patients at medical wards of Jimma University Medical Center, Southwest Ethiopia.

Methods

A hospital-based prospective observational study was conducted among hospitalized cardiac adult patients based on the inclusion criteria. Patient-specific data were collected using structured data collection tool. Potential drug-drug interaction was analyzed using Micromedex 3.0 DRUG-REAX^® System. Data were analyzed using statistical software package, version 20.0. To identify the independent predictors of potential drug-drug interaction, multiple stepwise backward logistic regression analysis was done. Statistical significance was considered at a p-value < 0.05. Written informed consent from patients was obtained and the patients were informed about confidentiality of the information obtained.

Results

Of the total 200 patients, majority were male (52.50%) and with a mean(±standard deviation) age of 42.54(±7.89) years. Out of 673 patients' prescriptions analyzed, 521 prescriptions comprised potential drug interactions and it was found that 967 drug interactions were present. The prevalence rate of potential drug-drug interactions among the study unit was 4.83 per patient and 1.44 per prescription regardless of the severity during their hospital stay. Overall the prevalence rate of potential drug interactions was 74.41%. Older age (adjusted odds ratio (95% confidence interval): 1.067 (2.33-27.12), p = 0.049), long hospital stay (⩾7 days) (adjusted odds ratio (95% confidence interval): 2.80 (1.71-4.61), p = 0.024), and polypharmacy (adjusted odds ratio (95% confidence interval): 1.64 (0.66-4.11), p = 0.041) were independent predictors for the occurrence of potential drug-drug interactions.

Conclusion

This study demonstrated a high prevalence of potential DIs among hospitalized cardiac patients in medical wards due to the complexity of pharmacotherapy. The prevalence rate is directly related to age, number of prescribed drugs, and length of hospital stay. Pharmacodynamic drug-drug interaction was the common mechanism of drug-drug interactions. Therefore, close monitoring of hospitalized patients is highly recommended.

Drug-drug interactions in patients with acute coronary syndrome across phases of treatment

The objective of this study is to evaluate potential drug-drug interactions (pDDIs) and risk factors for pDDIs in three phases of an acute coronary syndrome (ACS) treatment: from the point of first medical contact to the coronary angiography (first phase), after coronary angiography to the last day of hospitalization (second phase), and at discharge from hospital (third phase). This retrospective observational cohort clinical study was conducted at the Clinic for Cardiology of the Clinical Centre Kragujevac, a public tertiary care hospital in Kragujevac, Serbia. Micromedex^® interaction checker was used to detect pDDIs. This study included 245 ACS patients. All patients were exposed to at least one pDDI in all the phases of treatment. Mean total number of pDDIs was 9.47 ± 6.07, 10.11 ± 6.92, and 6.29 ± 3.66 in first, second, and third phases, respectively. Age, > 6 h from the beginning of the symptoms to admission, primary PCI, STE-ACS, COPD, delirium, hyperlipidemia, hypertension, obesity, systolic blood pressure at admission, TIMI risk score at admission, ALT, LDL, number of physicians who prescribed drugs to a single patient, number of prescribed drugs, and various pharmacological classes increased risk of pDDIs. Mechanical ventilation, dementia, and drug allergy noted in the medical documentation protected against them. Effects of heart failure, diabetes, and aPTT depended on phase of treatment and severity of pDDI. In conclusion, physicians should be vigilant to the possibility of pDDIs in patients harbouring factors that may increase their rate.

Drug-Drug Interactions in Hepatitis Patients: Do these Interactions Matter in Clinical Perspectives?

INTRODUCTION AND AIM

Hepatitis patients usually present with comorbidities and polypharmacy which increases risk of potential drug-drug interactions (pDDIs). We explored frequency, levels, predictors, and clinical relevance of pDDIs in hospitalized hepatitis patients.

MATERIAL AND METHODS

Retrospective cohort study was used. Clinical profiles of 413 hepatitis patients were reviewed for pDDIs using Micromedex-DrugReax. Frequency, levels and clinical relevance of pDDIs were reported. Logistic regression analysis was used to calculate odds-ratios for predictors.

RESULTS

Of total 413 patients, pDDIs were reported in 55.2%. Major-pDDIs were found in 35% patients. Total 660 pDDIs were identified, of which, 304 (46%) were of major-severity and 299 (45%) of moderateseverity. Patient's profiles of top-10 major-pDDIs were presented with signs/symptoms such as fever, hepatomegaly, anorexia, jaundice, hypertension, tachycardia, bradycardia, & pedal edema; and abnormalities in labs such as electrolytes-level, alanine aminotransferase, blood urea nitrogen, bilirubin-level, & serum creatinine. Significant association was observed for the presence of pDDIs with > 9 prescribed medicines (p < 0.001), hospitalization of > 5 days (p = 0.03), and stroke as comorbidity (p = 0.05). Moreover, odds of exposure to major-pDDIs were significantly higher in patients taking > 9 prescribed medicines (p < 0.001), hospitalization of > 5 days (p = 0.002), and stroke as comorbidity (p = 0.002).

CONCLUSION

We observed hepatitis patients presented with a considerable number of clinically relevant pDDIs. Attention should be given to widespread major-pDDIs and their potential adverse outcomes. Clinically relevant parameters, such as labs and signs/symptoms should be monitored particularly in high risk patients having polypharmacy, prolong hospitalization, and stroke as comorbidity.

Assessment of Consistency of Drug Interaction Information in Drug Labels Among the United States, the United Kingdom, China, Japan, and Korea

Information gap in drug labeling among countries create challenges in therapeutic use of drugs. We aimed to evaluate the consistency of drug interaction information in drug labels among five countries. The study drugs were chosen from the commonly approved drug list in the US, UK, China, Japan, and Korea. The degree of agreement of drug interaction data was evaluated by kappa coefficient. Thirty-eight drugs were evaluated, and moderate degree of agreement was observed among all countries' labeling (κ = 0.43, 95% confidence interval (CI) = 0.41-0.46). The degree of agreement was the highest for the UK and Korea (κ = 0.71, 95% CI = 0.67-0.75) and the lowest for the UK and Japan (κ = 0.02, 95% CI = 0.00-0.04). Information regarding drug interactions listed in the studied drug labels was not in high agreement. International standardization of drug labeling is required to ensure safe drug therapy.

Detection and analysis of drug-drug interactions among hospitalized cardiac patients in the Mohammed V Military Teaching Hospital in Morocco

INTRODUCTION

Drug-drug interactions (DDIs) are defined as two or more drugs interacting in such a manner that the effectiveness or toxicity of one or more drugs is altered. Patients with cardiovascular disorders are at higher risk for DDIs because of the types and number of drugs they receive. The aim of the present study was to assess the prevalence of DDIs in patients admitted to the cardiology department of a hospital in Morocco.

METHODS

A prospective observational study from June 2016 to September 2016 was carried out in the cardiology department of a hospital in Morocco. Those patients who were taking at least two drugs and had a hospital stay of at least 48 hours were included in the study. The medications of the patients were analysed for possible interactions. All the prescriptions of the study population were screened for drug-drug interactions using a computerized DDI database system (Theriaque®).

RESULTS

During the study period, 138 patients were included; 360 interactions were detected among 94 patients, with an average number of drugs taken of 5.2. The prevalence of DDIs was estimated at 68.11%, the most common of which concerned Kardegic/Plavix (12.22%), Kardegic/Heparin (8.33%), and Lasilix/Spironolactone (5.83%). Among the 726 prescribed drugs, (372 [51.24%]) were drugs of the cardiovascular system, followed by blood and hematopoietic organ drugs (288 [39.67%]) according to the Anatomical Therapeutic Chemical Classification codes. These interactions were categorized on the basis of level of severity: interactions with major severity accounted for 11.11% (40) of the total DDIs while those with moderate and minor severity accounted for 37.22% (134) and 51.66% (186), respectively.

CONCLUSION

This study reports the prevalence of DDIs in patients admitted to the cardiology department of a hospital in Morocco. This study shows that DDIs are frequent among hospitalized cardiac patients and highlights the need to screen prescriptions of cardiovascular patients for possible DDIs, as this helps in their detection and prevention.Pan African Medical Journal - ISSN: 1937- 8688 (www.panafrican-med-journal.com)Published in partnership with the African Field Epidemiology Network (AFENET). (www.afenet.net)Pan African Medical Journal - ISSN: 1937- 8688 (www.panafrican-med-journal.com)Published in partnership with the African Field Epidemiology Network (AFENET). (www.afenet.net).

Assessment of Drug-Drug Interaction in Ayder Comprehensive Specialized Hospital, Mekelle, Northern Ethiopia: A Retrospective Study

Introduction

Adverse drug interaction is a major cause of morbidity and mortality. Its occurrence is influenced by a multitude of factors. The influences of drug-drug interactions (DDIs) can be minimized through creation of awareness to health care professionals.

Objective

The objective of this study was to assess DDIs in Ayder Comprehensive Specialized Hospital (ACSH).

Methodology

A retrospective study design was employed on patient prescriptions available in the outpatient department of pharmacy and filled from September 2016 to February 2017 in ACSH.

Result

From the 600 prescription records assessed, the average number of drugs on single prescription was 2.73. Regarding the interaction observed 34 (9.63%) prescriptions with major drug-drug interaction, 210 (59.5%) moderate, 87 (24.65%) minor, and 22 (6.22%) unknown were identified. Age category showed significant association to affect the occurrence of DDIs and polypharmacy had statistically significant association with DDIs in bivariate analysis which was lost in adjusted OR.

Conclusion

From the current study it can be concluded that nearly half of the prescription ordered in ACSH contained DDIs and from the prescription with interacting medications majority of them had moderate DDIs.

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.

The prevalence and preventability of potentially relevant drug-drug interactions in patients admitted for cardiovascular diseases: A cross-sectional study

AIM

The aim was to describe the type and prevalence of potentially relevant drug-drug interactions (pDDIs) in a population of patients admitted for cardiovascular diseases (CVD), and management strategies for reducing the occurrence of pDDIs.

METHODS

A retrospective cross-sectional study was performed on Cardiology ward of University Clinical Hospital Center in Belgrade, Serbia. A total of 527 patients, with more than one prescription during hospital stay, were enrolled in this study. Data were obtained from medical records. LexiInteract was used as the screening tool.

RESULTS

At least one potentially relevant pDDI was identified in 83.9% of patients. Occurrence was significantly more prevalent in patients with higher number of drugs, multimorbidity, longer length of stay, arrhythmia, heart failure, infectious and respiratory disease. About 13% of pDDIs exposures were accompanied with concurrent renal or liver disease, as an additional risk for DDI manifestation. Among CVD, patients with a history of myocardial infarction possessed the highest additional risk. The most common potential clinical outcome was the effect on cardiovascular system 48.5%, renal function and/or potassium 22.3%, bleeding 9.5%, impaired glucose control 6.8% and digoxin toxicity 4.6%. Main management strategies to avoid X or D class included using paracetamol instead of NSAID or alternative NSAID (38%), alternative antibiotic or antifungal (20.4%), H₂ receptor antagonist instead of PPI (8.3%), avoiding therapeutic duplication (7.3%), and alternative HMG-CoA reductase inhibitor (7%). Heart rate, blood pressure, electrolytes/potassium and blood glucose could have been employed in monitoring for potential consequence of 72.2% C class pDDIs.

CONCLUSIONS

Use of drug interaction screening tools can be beneficial risk mitigation strategy for potentially relevant pDDIs in CVD patients. DDI screening software could be linked to the patient's laboratory results or clinical data regarding renal or liver function, as an approach to reinforce DDIs alert quality.

Comorbidity, Polytherapy, and Drug Interactions in a Neurological Context: An Example of a Multidisciplinary Approach to Promote the Rational Use of Drugs

Purpose:

A high number of adverse drug reactions (ADRs), mainly caused by drug–drug interactions (DDIs), occur in neurological wards and few data are available about incidence and prevalence of DDIs in this context. This study investigated—(1) the prevalence of drug–drug and drug–disease interactions in patients admitted to a neurological unit in Italy, (2) the risk factors for DDIs, and (3) the diseases and the drug classes mostly involved in drug–drug and drug–disease interactions.

Methods:

For 2 months, we performed a retrospective, observational study in the neurological unit of St Bassiano Hospital, enrolling 79 patients who received a drug prescription at discharge.

Results:

About half of the patients were discharged with 5 or more prescribed drugs, and 72% of patients showed potential, clinically relevant DDIs. Linear correlations were observed between age and number of prescribed drugs ( P < .01) and between age and number of interactions ( P < .01). The number of prescribed drugs was associated with the number of detected DDIs ( P < .01). The application of drug interaction alerts and the use of medication inappropriateness criteria (ie, Beers criteria) were not satisfactory in choosing the best therapy for each patient. Therefore, multidisciplinary discussions of each clinical case was required.

Conclusion:

The study demonstrated that the neurological patient, especially if elderly, has a high risk of DDI and ADRs and that many of these can be avoided by case discussion in multidisciplinary team meetings, in which the presence of a dedicated clinical pharmacist is crucial.

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.

Drug-drug interactions and adverse drug reactions in polypharmacy among older adults: an integrative review

OBJECTIVE

to identify and summarize studies examining both drug-drug interactions (DDI) and adverse drug reactions (ADR) in older adults polymedicated.

METHODS

an integrative review of studies published from January 2008 to December 2013, according to inclusion and exclusion criteria, in MEDLINE and EMBASE electronic databases were performed.

RESULTS

forty-seven full-text studies including 14,624,492 older adults (≥ 60 years) were analyzed: 24 (51.1%) concerning ADR, 14 (29.8%) DDI, and 9 studies (19.1%) investigating both DDI and ADR. We found a variety of methodological designs. The reviewed studies reinforced that polypharmacy is a multifactorial process, and predictors and inappropriate prescribing are associated with negative health outcomes, as increasing the frequency and types of ADRs and DDIs involving different drug classes, moreover, some studies show the most successful interventions to optimize prescribing.

CONCLUSIONS

DDI and ADR among older adults continue to be a significant issue in the worldwide. The findings from the studies included in this integrative review, added to the previous reviews, can contribute to the improvement of advanced practices in geriatric nursing, to promote the safety of older patients in polypharmacy. However, more research is needed to elucidate gaps.

OBJETIVO

identificar e sintetizar estudos que examinam as interações medicamentosas (IM) e reações adversas a medicamentos (RAM) em idosos polimedicados.

MÉTODOS

revisão integrativa de estudos publicados de janeiro de 2008 a dezembro de 2013, de acordo com critérios de inclusão e exclusão, nas bases de dados eletrônicas MEDLINE e EMBASE.

RESULTADOS

foram analisados 47 estudos de texto completo, incluindo 14,624,492 idosos (≥ 60 anos): 24 (51,1%) sobre RAM, 14 (29,8%) sobre IM e 9 estudos (19,1%) que investigaram tanto IM como RAM. Encontramos uma variedade de desenhos metodológicos. Os estudos revisados reforçaram que a polifarmácia é um processo multifatorial, e os preditores e a prescrição inadequada estão associados a resultados negativos de saúde, como aumento da frequência e tipos de RAM e IM envolvendo diferentes classes de drogas, além disso, alguns estudos mostram as intervenções mais bem-sucedidas para otimizar a prescrição.

CONCLUSÕES

IM e RAM entre idosos continuam a ser um problema significativo no mundo todo. Os resultados dos estudos incluídos nesta revisão integrativa, adicionado às revisões anteriores, podem contribuir para a melhoria das práticas avançadas de enfermagem geriátrica, para promover a segurança dos pacientes idosos em polifarmácia. No entanto, são necessárias mais pesquisas para elucidar lacunas.

OBJETIVO

identificar y resumir los estudios que analizan tanto las interacciones medicamentosas (IM) como las reacciones adversas a medicamentos (RAM) en los adultos mayores polimedicados.

MÉTODOS

revisión integradora de estudios publicados entre enero de 2008 a diciembre de 2013, siguiendo criterios de inclusión y exclusión, en las bases de datos electrónicas MEDLINE y EMBASE.

RESULTADOS

cuarenta y siete estudios de texto completo incluidos fueron analizados incluyendo 14,624,492 adultos mayores (≥ 60 años), de ellos 24 (51,1%) en relación con RAM, 14 (29,9%) con IM y 9 estudios (19,1%) que investigaron tanto IM como RAM. Encontramos una gran variedad de diseños metodológicos. Los estudios revisados reforzaron el concepto que la polifarmacia es un proceso multifactorial, y los predictores y la prescripción inadecuada se asocian con resultados negativos para la salud tales como el aumento de la frecuencia y tipos de RAM y IM implicando diferentes clases de fármacos, además que algunos estudios muestran cuales son las intervenciones más exitosas para optimizar la prescripción.

CONCLUSIONES

IM y RAM siguen siendo un problema importante en el mundo entero entre los adultos mayores. Los resultados de los estudios incluidos en esta revisión integradora, sumado a las revisiones previas, pueden contribuir a la mejora de las prácticas avanzadas de enfermería geriátrica, para promover la seguridad de los pacientes de mayor edad en la polifarmacia. Sin embargo, se necesita más investigación para esclarecer los vacíos de conocimiento.

Prevalence and risk of potentially adverse drug interactions in the treatment of acute alcohol poisoning

ABSTRACT The aim of this paper is to determine the profile of acute alcohol poisoning and to estimate the risk of potentially adverse drug interactions (ADIs) in patients intoxicated by alcohol when attended in emergency care at hospital. A descriptive serial cross-sectional study was performed with 4,271 individuals intoxicated by alcohol, from January 2009 to July 2011. Possible correlations were measured by Pearson's chi-square test. The data show high consumption in the population, especially in males between 25 and 59 years. The main circumstances for poisoning were alcohol misuse (96.3%). After treatment complete recovery from the signs or symptoms of the poisoning was observed in 96.88% cases; and death in 0.70%. The demonstration of potential risk for ADIs in medical care included 300 medical records which contained a history of acute alcohol poisoning. Possible drug-drug interactions (44.2%) and drug-alcohol interactions (55.8%) were demonstrated in 60.60% of analyzed medical records. Among these cases, 3%, 92.4% and 4.6% were classified as mild, moderate and severe, respectively. The measurement of ADIs aims to prevent clinical complications in medical care for alcohol misuse disorders.

Drug-drug interaction checking assisted by clinical decision support: a return on investment analysis

BACKGROUND

Drug-drug interactions (DDIs) are very prevalent in hospitalized patients.

OBJECTIVES

To determine the number of DDI alerts, time saved, and time invested after suppressing clinically irrelevant alerts and adding clinical-decision support to relevant alerts.

MATERIALS AND METHODS

The most frequently occurring DDIs were evaluated for clinical relevance by a multidisciplinary expert panel. Pharmacist evaluation of relevant DDIs was facilitated using computerized decision support systems (CDSS). During Phase 1, only CDSS-assisted DDI checking was implemented. During Phase 2, CDSS-assisted DDI checking remained in place, and clinically irrelevant DDIs were suppressed. In each phase, the number of alerts and duration of pharmacist DDI checking were compared to conventional DDI checking. In addition, the time invested to implement and configure the CDSS was compared to the time saved using CDSS-assisted DDI checking.

RESULTS

CDSS-assisted DDI checking resulted in a daily decrease of DDI checking alerts from 65 to 47 alerts in Phase 1 (P = .03) and from 73 to 33 alerts in Phase 2 (P = .003). DDI checking duration decreased from 15 to 11 minutes (P = .044) and from 15½ to 8½ minutes (P = .001) in Phases 1 and 2, respectively. Almost 298 of the 392 hours required for implementation were invested by pharmacists. An annual timesaving of 30 hours yielded a return on investment of 9.8 years.

CONCLUSION

CDSS-assisted DDI checking resulted in a 55% reduction of the number of alerts and a 45% reduction in time spent on DDI checking, yielding a return on investment of almost 10 years. Our approach can be used to refine other drug safety checking modules, increasing the efficiency of checking for drug safety without the need to add more staff pharmacists.

Assessment of drug-drug interactions in hypertensive patients at a superspeciality hospital

Objective:

The objective of the study was to assess the incidence and pattern of drug-drug interactions (DDIs) in hypertensive patients by using Micromedex and Medscape databases.

Materials and Methods:

A prospective observational study was carried out in a superspeciality hospital setting in South India for period of 9 months. Hypertensive patients who admitted into the hospital with the age more than 18 years, received more than 3 drugs per prescription and length of hospital stay for more than 24 hours were included in the study. An appropriate data was collected and assessed for DDIs with the help of Micromedex and Medscape databases.

Results:

A total of 227 patients were enrolled during the study period. Among the 227 patients, 48 of them developed 53 clinically significant DDIs. Out of 48 patients, most of them were in the age-group of 50–60 years [18 (37.49%)]. The percentage of DDIs were higher in males [30 (62.5%)] compared to females [18 (37.5%)]. The most common drugs responsible for DDIs in the present study were Insulin [18 (33.96%)] followed by Metoprolol [10 (18.86%)], Torsemide [8 (15.09%)], and Hydrochlorothiazide [8 (15.09%)]. The most commonly interacting pairs were Ciprofloxacin-Insulin [6 (11.32%)], followed by Metoprolol-Insulin [4 (7.54%)] and Atenolol-Insulin [4 (7.54%)]. The most common consequences of interacting pairs were reduced serum potassium levels and hyperglycemia.

Conclusion:

The overall incidence rate of DDIs was found to be 21.14% and the increasing number of co-morbidities (P ≤ 0.003) and polypharmacy (P ≤ 0.002) were the risk factor for the development of significant number of DDIs.

Drug-drug interaction software in clinical practice: a systematic review

PURPOSE

Several electronic databases which report the prevalence of drug-drug interactions (DDIs) are used as a tool for evaluation of potentially harmful DDIs. The aim of our review was to evaluate the usability and appropriateness of commercially available electronic databases which assess the prevalence of potential DDIs.

METHODS

The systematic electronic literature search was conducted with the following search terms: "database" AND "software," and "drug-drug interactions" AND "database," and the inclusion and exclusion criteria were applied in order to identify the publications of interest.

RESULTS

A total of 3766 papers were identified by systematic search. After applying inclusion and exclusion criteria, 38 publications were included in the analysis. The most commonly used software in the included studies was Micromedex® Drug-Reax, for which some authors argue to be the most reliable due to highest sensitivity. It gives information about clinical consequences of DDIs, classifies underlying mechanism and onset of the adverse outcome (either rapid, or delayed) as well as severity (such as minor, moderate, or major), and provides the level of evidence which supports this information. This data is also provided by Drug Interaction Facts®, Lexi-Interact®, and Pharmavista®. A small number of studies which compared assessment of DDIs with electronic database and the clinician's assessment showed large discrepancy in number and relevance of detected DDIs. The overlap was in some cases as low as 11 %.

CONCLUSION

The deficiency of clinical relevance of detected DDIs should be addressed in the upcoming research as it would provide more relevant information to the prescribers' in clinical practice.

Understanding adverse drug reactions in older adults through drug-drug interactions

AIMS

The aims of this study are to evaluate prevalence and characteristics of adverse drug reactions (ADRs) and to evaluate the potential contribution of specific medications, therapeutic categories and drug-drug interactions (DDIs) in older adults.

METHODS

All ADR reporting forms of persons aged 65+ years collected by the pharmacovigilance of one of the main hospitals in Italy during 2013 were evaluated. DDIs were analysed by a computerized prescription system (INTERCheck) and based on the interactions' database managed by the Istituto di Ricerche Farmacologiche Mario Negri. DDIs were classified according to their clinical relevance as contraindicated, major, and moderate.

RESULTS

Amongst all the ADR reporting forms (n=1014) collected during 2013, 343 affected older adults. The most frequent ADRs were: haemorrhages (n=122, 35.5%), allergic reactions (n=56, 16.3%), and elevated International Normalized Ratio (INR>6, n=54, 15.7%). The specific medications that contributed to ADRs were warfarin (42.5%), acenocumarol (9%), and allopurinol (8.5%); while the therapeutic categories were haematological agents (67%) and proton pump inhibitors (13%). A total of 912 DDIs were found; one third of them were contraindicated or major and 31.5% of them potentially contributed to ADRs; of these, the most frequent were: warfarin and heparin (contraindicated, n=5); warfarin and a statin (major, n=38); warfarin and a proton pump inhibitor (moderate, n=40). At least one DDI contributed to 66 haemorrhages out of 122 (54%) and to 41 elevated INR out of 54 (76%).

CONCLUSION

DDIs significantly contribute to the onset of ADRs in older adults and intervention programmes, e.g., the employment of a computerized system, may reduce the burden of iatrogenic illnesses in the elderly.

Differences of Reasons for Alert Overrides on Contraindicated Co-prescriptions by Admitting Department

OBJECTIVES

To reveal differences in drug-drug interaction (DDI) alerts and the reasons for alert overrides between admitting departments.

METHODS

A retrospective observational study was performed using longitudinal Electronic Health Record (EHR) data and information from an alert and logging system. Adult patients hospitalized in the emergency department (ED) and general ward (GW) during a 46-month period were included. For qualitative analyses, we manually reviewed all reasons for alert overrides, which were recorded as free text in the EHRs.

RESULTS

Among 14,780,519 prescriptions, 51,864 had alerts for DDIs (0.35%; 1.32% in the ED and 0.23% in the GW). The alert override rate was higher in the ED (94.0%) than in the GW (57.0%) (p < 0.001). In an analysis of the study population, including ED and GW patients, 'clinically irrelevant alert' (52.0%) was the most common reason for override, followed by 'benefit assessed to be greater than the risk' (31.1%) and 'others' (17.3%). The frequency of alert overrides was highest for anti-inflammatory and anti-rheumatic drugs (89%). In a sub-analysis of the population, 'clinically irrelevant alert' was the most common reason for alert overrides in the ED (69.3%), and 'benefit assessed to be greater than the risk' was the most common reason in the GW (61.4%).

CONCLUSIONS

We confirmed that the DDI alerts and the reasons for alert overrides differed by admitting department. Different strategies may be efficient for each admitting department.

Potential drug-drug interactions in hospitalized patients with chronic heart failure and chronic obstructive pulmonary disease

INTRODUCTION

Polypharmacy is common in patients with chronic heart failure (HF) and/or chronic obstructive pulmonary disease (COPD), but little is known about the prevalence and significance of drug-drug interactions (DDIs). This study evaluates DDIs in hospitalized patients.

MATERIAL AND METHODS

We retrospectively screened medical charts over a 6-month period for diagnosis of chronic HF and/or COPD. Potential DDIs were evaluated using Lexi-Interact software.

RESULTS

Seven hundred and seventy-eight patients were included in the study (median age 75 years, 61% men). The median number of drugs on admission and discharge was 6 (interquartile range (IQR) 4-9) and 7 (IQR 5-), respectively (p = 0.10). We recorded 6.5 ±5.7 potential DDIs per patient on admission and 7.2 ±5.6 on discharge (p = 0.2). From admission to discharge, type-C and type-X potential DDIs increased (p < 0.05 for both). Type X interactions were rare (< 1%), with the combination of a β-blocker and a β2 agonist being the most common (64%). There were significantly more type-C and type-D potential DDIs in patients with chronic HF as compared to patients with COPD (p < 0.001). Patients with concomitant chronic HF and COPD had more type-C and type-X potential DDIs when compared to those with individual disease (p < 0.005). An aldosterone antagonist and ACE inhibitor/ARB were prescribed to 3% of chronic HF patients with estimated glomerular filtration rate < 30 ml/(min × 1.73 m(2)).

CONCLUSIONS

The DDIs are common in patients with chronic HF and/or COPD, but only a few appear to be of clinical significance. The increase in potential DDIs from admission to discharge may reflect better guideline implementation rather than poor clinical practice.

Prevalence of potential drug-drug interactions among internal medicine ward in University of Gondar Teaching Hospital, Ethiopia

OBJECTIVE

To determine the prevalence, clinical significance and the associated risk factors of potential drug-drug interactions (DDIs) at internal medicine ward of University of Gondar (UOG) hospital.

METHOD

A prospective cross-sectional study was conducted on patients treated in internal medicine ward of UOG hospital from April 29, 2013 to June 2, 2013. Data was collected from medical records and by interviewing the patients face to face. Descriptive analysis was conducted for back ground characteristics and logistic regression was used to determine the associated risk factors.

RESULT

In our study, we have identified a total number of 413 potential DDIs and 184 types of interacting combinations with 4.13 potential DDIs per patient. Among 413 potential DDIs most were of moderate interactions 61.2% (n=253) followed by 26% (n=107) of minor interactions and 12.8% (n=53) of major interactions. There was significant association of occurrence of potential DDIs only with taking three or more medications.

CONCLUSION

We have recorded a high rate of prevalence of potential DDI in the internal medicine ward of UOG hospital and a high number of clinically significant DDIs which the most prevalent DDI were of moderate severity. Careful selection of drugs and active pharmaceutical care is encouraged in order to avoid negative consequences of these interactions.