Prevalence and typology of potential drug interactions occurring in primary care patients

Prevalence of Drug-Drug Interactions in Older Community-Dwelling Individuals: A Systematic Review and Meta-analysis

BACKGROUND

Drug-drug interactions (DDIs) can lead to medication-related harm, and the older population is at greatest risk. We conducted a systematic review and meta-analysis to estimate DDI prevalence and identify common DDIs in older community-dwelling adults.

METHODS

PubMed and EMBASE were searched for observational studies published between 01/01/2010 and 10/05/2021 reporting DDI prevalence in community-dwelling individuals aged ≥ 65 years. Nursing home and inpatient hospital studies were excluded. Study quality was assessed using the Joanna Briggs Institute critical appraisal tool. Meta-analysis was performed using a random-effects model with logit transformation. Heterogeneity was evaluated using Cochran's Q and I². DDI prevalence and 95% confidence intervals (CIs) are presented. All analyses were performed in R (version 4.1.2).

RESULTS

There were 5144 unique articles identified. Thirty-three studies involving 17,011,291 community-dwelling individuals aged ≥ 65 years met inclusion criteria. Thirty-one studies reported DDI prevalence at the study-participant level, estimates ranged from 0.8% to 90.6%. The pooled DDI prevalence was 28.8% (95% CI 19.3-40.7), with significant heterogeneity (p < 0.10; I² = 100%; tau² = 2.13) largely explained by the different DDI identification methods. Therefore, 26 studies were qualitatively synthesised and seven studies were eligible for separate meta-analyses. In a meta-analysis of three studies (N = 1122) using Micromedex^®, pooled DDI prevalence was 57.8% (95% CI 52.2-63.2; I² = 69.6%, p < 0.01). In a meta-analysis of two studies (N = 809,113) using Lexi-Interact^®, pooled DDI prevalence was 30.3% (95% CI 30.2-30.4; I² = 6.8%). In a meta-analysis of two studies (N = 947) using the 2015 American Geriatrics Society Beers criteria^®, pooled DDI prevalence was 16.6% (95% CI 5.6-40.2; I² = 97.5%, p < 0.01). Common DDIs frequently involved cardiovascular drugs, including ACE inhibitor-potassium-sparing diuretic; amiodarone-digoxin; and amiodarone-warfarin.

CONCLUSIONS

DDIs are prevalent among older community-dwelling individuals; however, the methodology used to estimate these events varies considerably. A standardised methodology is needed to allow meaningful measurement and comparison of DDI prevalence.

Prevalence and Factors Associated with Potential Drug-Drug Interactions in Older Community-Dwelling Adults: A Prospective Cohort Study

BACKGROUND

Older patients are at increased risk of drug-drug interactions (DDIs) due to polypharmacy. Cardiovascular and central nervous system (CNS) drugs are commonly implicated in serious DDIs.

OBJECTIVES

This study aimed to determine the prevalence and factors associated with potential 'severe' cardiovascular and CNS DDIs among older (≥ 70 years) community-dwellers.

METHODS

This was a prospective cohort study using linked data from a national pharmacy claims database and waves 1 and 2 of The Irish LongituDinal study on Ageing (TILDA). 'Severe' cardiovascular and CNS DDIs were identified using the British National Formulary 77 and Stockley's Drug Interactions. The prevalence of 'severe' DDIs (any DDI vs. none) was calculated. Logistic regression was used to examine the association between sociodemographic, functional ability, and medication-related factors and the risk of DDI exposure between waves 1 and 2.

RESULTS

A total of 1466 patients were included [mean age (standard deviation) = 78 (5.5) years; female n = 795, 54.2%]. In total, 332 community-dwellers aged ≥ 70 years [22.65%, 95% confidence interval (CI) 20.58-24.86] were potentially exposed to at least one 'severe' cardiovascular or CNS DDI, with more than half (54.82%) of this cohort dispensed the same DDI for a prolonged time (≥ 3 consecutive claims). Aspirin-warfarin was the most frequently dispensed (co-prescribed) DDI (n = 34, 10.24%, 95% CI 7.39-14.00), followed by atorvastatin-clarithromycin (n = 19, 5.72%, 95% CI 3.64-8.81). Polypharmacy [≥ 10 vs. < 5 drugs, odds ratio (OR) 13.40, 95% CI 8.22-21.85] and depression (depressed vs. not, OR 2.12, 95% CI 1.34-3.34) were significantly associated with these DDIs, after multivariable adjustment.

CONCLUSION

'Severe' cardiovascular and CNS DDIs are prevalent in older community-dwellers in Ireland, and those with polypharmacy and depression are at a significantly increased risk.

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study

Background

Drug interactions increase the risk of treatment failure, intoxication, hospital admissions, consultations and mortality. Computer-assisted prescription systems can help to detect interactions.

Objectives

To describe the drug–drug interaction (DDI) and drug–disease interaction (DdI) prevalence identified by a computer-assisted prescription system in patients with multimorbidity and polypharmacy. Factors associated with clinically relevant interactions were analysed.

Methods

Observational, descriptive, cross-sectional study in primary health care centres was undertaken in Spain. The sample included 593 patients aged 65–74 years with multimorbidity and polypharmacy participating in the MULTIPAP Study, recruited from November 2016 to January 2017. Drug interactions were identified by a computer-assisted prescription system. Descriptive, bivariate, and multivariate analyses with logistic regression models and robust estimators were performed.

Results

Half (50.1% (95% CI 46.1–54.1)) of the patients had at least one relevant DDI and 23.9% (95% CI 18.9–25.6) presented with a DdI. Non-opioid–central nervous system depressant drug combinations and benzodiazepine–opioid drug combinations were the two most common clinically relevant interactions (10.8% and 5.9%, respectively). Factors associated with DDI were the use of more than 10 drugs (OR 11.86; 95% CI 6.92–20.33) and having anxiety/depressive disorder (OR 1.98; 95% CI 1.31–2.98). Protective factors against DDI were hypertension (OR 0.62; 95% CI 0.41–0.94), diabetes (OR 0.57; 95% CI 0.40–0.82), and ischaemic heart disease (OR 0.43; 95% CI 0.25–0.74).

Conclusion

Drug interactions are prevalent in patients aged 65–74 years with multimorbidity and polypharmacy. The clinically relevant DDI frequency is low. The number of prescriptions taken is the most relevant factor associated with presenting a clinically relevant DDI.

Potential and clinical relevant drug-drug interactions among elderly from nursing homes: a multicentre study in Murcia, Spain

This study purposes to determine the prevalence of potential and clinical relevant Drug-Drug-Interactions (pDDIs) in institutionalized older adults and to identify the pertinent factors associated. We conduct an observational, multicenter and cross-sectional study during the last quarter of 2010. We selected a sample of 275 subjects (aged ≥ 65 years) from 10 nursing homes of Murcia (Spain) by a two-stage complex sampling. pDDIs were identified using the College of Pharmacists Database. We only considered pDDIs of clinical relevance, and thereafter the relevant factors were identified through uni-level and multi-level regression analyses. A total of 210 pDDIs were identified, 120 of which were considered clinically relevant (57.1%), affecting a total of 70 elderly (25.8%). Eight pharmacological groups made up 70.2% of the clinically relevant pDDIs. More clinically relevant DDIs were found in people suffering several pathologies (OR = 2.3; 95%CI = 1.4-4.5), and also in people who take ten or more drugs daily (OR = 9.6; 95%CI = 4.8-19.1), and people who take anti-inflammatory drugs (OR = 3.9; 95%CI = 1.4-10.4). This study reveals that clinically relevant pDDIs are very common in institutionalized elderly people, and that caregivers should aim at improving their practice in order to reduce the prevalence of this phenomenon.

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.

Clinically relevant potential drug-drug interactions among outpatients: A nationwide database study

BACKGROUND

Adverse drug events due to drug-drug interactions (DDIs) represent a considerable public health burden, also in Slovenia. A better understanding of the most frequently occurring potential DDIs may enable safer pharmacotherapy and minimize drug-related problems.

OBJECTIVES

The aim of this study was to evaluate the prevalence and predictors of potential DDIs among outpatients in Slovenia.

METHODS

An analysis of potential DDIs was performed using health claims data on prescription drugs from a nationwide database. The Lexi-Interact Module was used as the reference source of interactions. The influence of patient-specific predictors on the risk of potential clinically relevant DDIs was evaluated using logistic regression model.

RESULTS

The study population included 1,179,803 outpatients who received 15,811,979 prescriptions. The total number of potential DDI cases identified was 3,974,994, of which 15.6% were potentially clinically relevant. Altogether, 9.3% (N = 191,213) of the total population in Slovenia is exposed to clinically relevant potential DDIs, and the proportion is higher among women and the elderly. After adjustment for cofactors, higher number of medications and older age are associated with higher odds of clinically relevant potential DDIs. The burden of DDIs is highest with drug combinations that increase risk of bleeding, enhance CNS depression or anticholinergic effects or cause cardiovascular complications.

CONCLUSION

The current study revealed that 1 in 10 individuals in the total Slovenian population is exposed to clinically relevant potential DDIs yearly. Taking into account the literature based conservative estimate that approximately 1% of potential DDIs result in negative health outcomes, roughly 1800 individuals in Slovenia experience an adverse health outcome each year as a result of clinically relevant potential interactions alone.

Medication errors detected in elderly patients admitted to an internal medicine service

OBJECTIVE

The aim of the work was to analyse the outpatient medication errors detected on admission in senior patients in a Spanish general internal medicine service.

PATIENTS AND METHODS

We carried out a retrospective cohort study based on a review of the admission reports of consecutive, non-selected, patients aged ≥ 65 years.

RESULTS

Eight hundred and sixty admission reports (cases) were analysed. Overall, we detected 218 errors in 173 (20.1%) of them. 'Wrong drug' errors were found in 165 occasions (75.7% of the 218 detected errors), being the most frequent among these 'not indicated/inappropriate drug for the diagnosis' (61 cases, 28.0%), followed by 'not indicated/inappropriate drug for the patient's condition' (55 cases, 25.2%). The binary logistic regression analysis showed association (p<0.05) between medication errors and sex (female) (OR 0.53, 95%, CI 0.37-0.76), cognitive impairment (OR 0.57, 95% CI 0.38-0.85), length of hospital stay (OR 1.06, 95% CI 1.00-1.11), number of diagnoses (OR 0.92, 95% CI 0.85-0.98), number of medicines at admission (OR 1.20, 95% CI 1.13-1.28) and lack of a recent previous admission in an internal medicine department (OR 2.07, 95% CI 1.14-3.74).

CONCLUSION

Although previous studies are not completely comparable, the incidence of errors found at admission in our study is low. We stress the relevance of the reconciliation of treatment in elderly people (where internists may play an important role, from their perspective of a comprehensive patient's care) and integrated procedures for medication prescription and dispensation.

Potential drug-drug interactions in prescriptions to patients over 45 years of age in primary care, southern Brazil

BACKGROUND

Few cross-sectional studies involving adults and elderly patients with major DDIs have been conducted in the primary care setting. The study aimed to investigate the prevalence of potential drug-drug interactions (DDIs) in patients treated in primary care.

METHODOLOGY/PRINCIPAL FINDINGS

A cross-sectional study involving patients aged 45 years or older was conducted at 25 Basic Health Units in the city of Maringá (southern Brazil) from May to December 2010. The data were collected from prescriptions at the pharmacy of the health unit at the time of the delivery of medication to the patient. After delivery, the researcher checked the electronic medical records of the patient. A total of 827 patients were investigated (mean age: 64.1; mean number of medications: 4.4). DDIs were identified in the Micromedex® database. The prevalence of potential DDIs and major DDIs was 63.0% and 12.1%, respectively. In both the univariate and multivariate analyses, the number of drugs prescribed was significantly associated with potential DDIs, with an increasing risk from three to five drugs (OR = 4.74; 95% CI: 2.90-7.73) to six or more drugs (OR = 23.03; 95% CI: 10.42-50.91). Forty drugs accounted for 122 pairs of major DDIs, the most frequent of which involved simvastatin (23.8%), captopril/enalapril (16.4%) and fluoxetine (16.4%).

CONCLUSIONS/SIGNIFICANCE

This is the first large-scale study on primary care carried out in Latin America. Based on the findings, the estimated prevalence of potential DDIs was high, whereas clinically significant DDIs occurred in a smaller proportion. Exposing patients to a greater number of prescription drugs, especially three or more, proved to be a significant predictor of DDIs. Prescribers should be more aware of potential DDIs. Future studies should assess potential DDIs in primary care over a longer period of time.

How frequently are contraindicated or warned against combinations of drugs prescribed to patients receiving long-term opioid therapy for chronic pain?

PURPOSE

To analyse the proportion of patients treated with an opioid for chronic pain who were prescribed concomitant medications that are warned against or contraindicated in the German summary of product characteristics to determine if warnings on drug-drug interactions (DDIs) are observed.

METHODS

This retrospective analysis used longitudinal aggregated patient data from the Intercontinental Marketing Services Disease Analyzer in Germany. Patients with two or more prescriptions of morphine, hydromorphone, oxycodone or tramadol from 1 January 2006 to 31 December 2008 were included; drugs prescribed within 30 days of an opioid prescription were identified as concomitant medications. The frequency of concomitant treatment with drugs warned against or contraindicated in the German opioid summary of product characteristics was determined. Concomitant treatment with drugs metabolised by CYP3A4 inhibitors and inducers and CYP2D6 inhibitors was also considered.

RESULTS

The Intercontinental Marketing Services database contained 13,405 eligible patients; 72% had concomitant diseases which may increase the risk for DDIs (hypertension, diabetes mellitus, renal failure, renal glomerular disease or renal tubulointerstitial disease). Very few patients received concomitant prescriptions of an opioid with a contraindicated drug. Many patients were prescribed opioids concomitantly with drugs with potential for harmful safety-related DDIs or DDIs that alter the effectiveness of one or more of the opioids. A large proportion of all concomitant prescriptions with potential for DDIs were given to at-risk patients aged 65 years and older.

CONCLUSIONS

Many patients that received an opioid for chronic pain were prescribed concomitant medications with the potential for safety-related DDIs or interactions that would alter the effectiveness of the opioid.

How the practice of allergy shows the promise and challenge of personalized medicine

Personalized medicine seeks to stratify therapies according to individual characteristics, and by so doing improve effectiveness and reduce complications. However, there are not many models of care that is highly stratified within a single diagnosis in this manner. One potential model is the practice of allergy, in which care is tailored to specific allergens for individual patients within the broader context of care for rhinitis or asthma. Allergists have already confronted many of the same regulatory issues anticipated for personalized medicine. The history of allergy practice also anticipates some of the patient safety concerns that may arise from tracking and using highly personalized medical information. Finally, the therapy of allergy and asthma has been at the forefront of attempts to incorporate pharmacogenomics information into patient care. Individualized therapy has always been central to the practice of allergy, and so provides a useful proving ground for personalized medicine as a concept of care.

[Analysis of the drug interactions associated to domiciliary drug therapy in elderly hospitalized patients]

OBJECTIVE

To determine the prevalence of potentially relevant drug-drug interactions associated with chronic treatment of elderly patients over 64-years of age on hospital admission and the factors associated with an increased presence of these.

SUBJECTS AND METHODS

Cross-sectional observational study in a hospital referral area. All patients aged 65 or over admitted to the hospital in the last three months in 2009 were included. Based on the drug database of the General Council of Colleges of Pharmacy (BOT), drug-drug interactions and their potential clinical relevance were identified. To identify the variables associated with a higher prevalence of drug-drug interactions, analyses of correlation and of univariable linear regression and uni-and multivariable logistic regression analyses were performed using the SPSS, version 15.0.

RESULTS

We analyzed the drug prescription data of 382 patients, whose mean age was 7.7 years. A total of 45.3% of patients had comorbidities and 78.8% had taken 5 or more drugs. We identified 272 clinically relevant drug-drug interactions that involved 159 patients (41.6%). Seven pharmacological groups accounted for 80.6% of the drug-drug interactions. The variables that had a statistically significant association to a higher prevalence of relevant interactions were polypharmacy, respiratory insufficiency, and treatment with proton-pump inhibitors, vitamin K antagonists, diuretics or anti-platelet drugs.

CONCLUSIONS

A high prevalence of relevant drug-drug interactions was found in elderly hospitalized patients. Our findings suggest that prevention strategies should be implemented to avoid their associated adverse events, especially in high risk populations.

[A hazard scale for severe interactions: a tool for establishing prioritising strategies to improve the safety of the prescription in family medicine]

OBJECTIVE

To effectively locate the drugs most implicated in severe interactions as a basis of designing actions to improve patient safety in Primary Care.

DESIGN

Cross-sectional study of prescriptions using the Primary Care computerised medical records database (OMI-PC).

SETTING

Murcia (Spain) Health Areas I, VI, VII and IX (723,664 inhabitants).

PARTICIPANTS

There are 362,271 patients over 14 years-old available in the OMI-PC and are assigned to a doctor who uses the OMI-PC regularly.

MAIN MEASUREMENTS

We analysed the drugs that each patient could be taking, looking for severe interactions. We constructed a severe interaction hazard scale (e-PIG) calculating [1] the probability that a non-selected patient may be taking a particular drug and [2] the probability that a drug may produce a severe interaction. With this, we estimated the risk of producing a severe interaction for each drug, which was converted into a 5 point logarithmic scale.

RESULTS

We found 83,138 patients (22.9%) at risk (they took 2 or more drugs). We identified 466,940 prescriptions providing 939 drugs and 5,597 severe interactions (prevalence 5.8%). In these, 167 drugs were involved, of which e-PIG identified 5 (3%) with an extreme value: omeprazole, diazepam, acenocoumarol, ibuprofen and calcium.

CONCLUSIONS

e-PIG is a logarithmic expression of the risk that prescribing a particular drug may produce a severe interaction in a determined setting and time. Its monitoring could become a prioritisation element that may assist the design of strategies for improving the safety of the use of drugs.