Potential drug-drug interactions in the medication of medical patients at hospital discharge

Polypharmacy and high-alert medications in patients with nasally placed feeding tube on admission and at hospital discharge: Multicenter cross-sectional study

Background

Polypharmacy and the use of high-alert medications in patients with nasally placed feeding tube (NPFT) increase the risks of drug related problems.

Objective

Characterize drugs prescribed to patients with NPFT and compare the rates of polypharmacy and high-alert medication use at admission and hospital discharge.

Design and setting

Multicenter cross-sectional study with 327 participants.

Methods

Data of patients with NPFT were obtained from the medical records and recorded in an electronic data collection tool. Mean number of drugs, polypharmacy and number of high-alert medications prescribed on admission and at discharge were compared using Wilcoxon or McNemar's tests. Generalized Estimating Equations analyzed the relationship between polypharmacy and high-alert medications according to age and time point. Primary reason for hospital admission, level of consciousness, severity of comorbid diseases and patient care complexity were also assessed.

Results

Most patients were male, older people, hospitalized for circulatory system diseases and had at least one comorbidity. On admission, a significant number of patients were alert (59.9%), at high risk for death (43.1%) and high dependent on nursing care (35.4%). Additionally, 92% patients were on polypharmacy on admission, versus 84.7% at hospital discharge (p = 0,0011). The occurrence of polypharmacy was independent of age (p = 0.2377). >17% of all drugs prescribed were high-alert medications, with no statistically significant difference between admission and discharge (p = 0,3957). There was no statistical evidence that the use of high-alert medications increases with age (n = 0,5426).

Conclusions

These results support the planning of multidisciplinary qualified actions for patients using NPFT.

Predictors of potential clinically harmful drug-drug interactions at the medical wards in the University of Benin Teaching Hospital, Benin City

Drug-drug interactions are preventable causes of adverse events. Different factors have been recognized as important predictors of drug-drug interactions but few studies have addressed these predictors in patients admitted into medical wards of a tertiary hospital in Nigeria hence this study. This was a retrospective study conducted using case records of patients admitted into the medical wards between January 1 and December 31, 2020. Patients were selected using a systematic random sampling method. Socio-demographic details including age, gender, number of comorbidities, and number of medications prescribed and diagnosis were collected on days 1, 3, and at discharge. Potential drug-drug interactions were checked using Lexi-interact® software. Analysis was set at p < 0.05. A total of 430 case records were included in this study based on the inclusion criteria. Lexi-interact recorded a prevalence of (217) 50.5% on day 1, (146) 34.0% on day 3, and (290) 67.4% at discharge. A significant association (p < 0.05) was found between the potential drug-drug interactions (DDI) and an increased number of medicines prescribed on all the days of admission. Also, patients without certain infectious or parasitic diseases have reduced odds of developing DDI. There is a need for continuous monitoring of medications from admission to discharge especially in the elderly, those on multiple medications, certain infectious or parasitic diseases, and comorbidities as these impact on DDIs.

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).

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

Purpose

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

Methods

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

Results

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

Conclusions

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

Potential Drug-Drug Interactions in Hospitalized Medical Patients: Data From Low Resource Settings

Introduction

Adverse events related to Drug-Drug Interactions (DDIs) are among the few common reasons for hospitalization worldwide; however, they can be prevented with an efficient patient-centered system. Different mechanisms have successfully limited the prevalence of DDIs in developed countries. There are limited data regarding DDIs from limited-resource settings. Furthermore, there is no cost-effective system that has shown promising results in preventing them in this setting. This study aims to assess the frequency of potential DDIs in a low-resource setting and to check its association with different factors such as poly-pharmacy and demographics.

Methods

Through this cross-sectional study, drug charts of patients admitted to a medical unit in November 2019 were analyzed using a structured questionnaire. A list of drugs co-prescribed to each patient was entered into the Medscape Drug Interaction checker to calculate the frequency and severity of potential DDIs.

Results

The mean age of patients was 49 years, and on average, seven drugs were prescribed to each patient. Among 100 analyzed prescriptions, 400 potential DDIs were identified with a mean of 4±5.42 per patient. According to Medscape interaction checker classification, 2 DDIs were contraindicated, 28 were serious, 246 required close monitoring, and 124 were minor. The most frequently encountered drug interaction was "spironolactone with furosemide." There was a significant correlation of the occurrence of potential DDIs with increased numbers of prescribed drugs.

Conclusion

Our patient population was prescribed more drugs per patient than calculated in other settings. Poly-pharmacy is an independent risk factor for DDIs. Lastly, advancing age exposes patients to poly-pharmacy, and therefore, they are at a higher risk of developing DDIs.

Does DDI-Predictor Help Pharmacists to Detect Drug-Drug Interactions and Resolve Medication Issues More Effectively?

The characterization of drug-drug interactions (DDIs) may require the use of several different tools, such as the thesaurus issued by our national health agency (i.e., ANSM), the metabolic pathways table from the Geneva University Hospital (GUH), and DDI-Predictor (DDI-P). We sought to (i) compare the three tools’ respective abilities to detect DDIs in routine clinical practice and (ii) measure the pharmacist intervention rate (PIR) and physician acceptance rate (PAR) associated with the use of DDI-P. The three tools’ respective DDI detection rates (in %) were measured. The PIRs and PARs were compared by using the area under the curve ratio given by DDI-P (R_AUC) and applying a chi-squared test. The DDI detection rates differed significantly: 40.0%, 76.5%, and 85.2% for ANSM (The National Agency for the Safety of Medicines and Health Products), GUH and DDI-P, respectively (p < 0.0001). The PIR differed significantly according to the DDI-P’s R_AUC: 90.0%, 44.2% and 75.0% for R_AUC ≤ 0.5; R_AUC 0.5–2 and R_AUC > 2, respectively (p < 0.001). The overall PAR was 85.1% and did not appear to depend on the R_AUC category (p = 0.729). Our results showed that more pharmacist interventions were issued when details of the strength of the DDI were available. The three tools can be used in a complementary manner, with a view to refining medication adjustments.

Prevalence of potential drug-drug interactions in breast cancer patients and determination of their risk factors

Breast cancer patients use numerous medications, which include cytotoxic chemotherapy drugs, hormonal agents and supportive medication, so they are more vulnerable to potential adverse drug interactions. This study aimed to evaluate frequency, severity, clinical importance and risk factors responsible for the Drug-drug interactions (DDIs) in a cohort of patients suffering from breast cancer. Data was obtained from 150 patients in the oncology ward (both inpatient and outpatient) with a confirmed diagnosis of breast cancer and currently receiving standard breast cancer-directed treatment. The data was recorded into a pre-designed form specifically made for this study through individual patient interviews and by reviewing the detailed medical chart records of the patients. DDIs were identified by using drug interaction software such as Medscape mobile application and Micromedex version 2.The results of this study showed that all patients were female. The mean numbers of drugs that patients used were 7. Potential drug interactions were identified in 92% of the patients. When drug groups were overviewed, 32% of interactions were between anti neoplastic drugs, 62.9% interactions were between the anti neoplastic agent and supportive care drugs and 5% of them were between anti-cancer drugs and drugs used to treat comorbidities. Major DDIs were found in 62.2% of patients, 25.3% of DDIs were moderate and 12.4% were minor. The number of drugs, comorbid diseases, and selection of chemo protocols were the risk factors for drug interactions. Most of the DDIs found in breast cancer therapy may have adverse consequences on patient health and therapeutic outcomes. Therefore, health care professionals should review the medication regimen of patients with breast cancer before starting any chemotherapy treatment.

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.

Prevalence and nature of potential drug-drug interactions among hospitalized HIV patients presenting with suspected meningitis in Uganda

Background

Management of co-infections including cryptococcal meningitis, tuberculosis and other opportunistic infections in persons living with HIV can lead to complex polypharmacotherapy and increased susceptibility to drug-drug interactions (DDIs). Here we characterize the frequency and types of potential DDIs (pDDIs) in hospitalized HIV patients presenting with suspected cryptococcal or tuberculous meningitis.

Methods

In a retrospective review of three cryptococcal meningitis trials between 2010 and 2017 in Kampala, Uganda, medications received over hospitalization were documented and pDDI events were assessed. IBM Micromedex DRUGDEX® online drug reference system was used to identify and describe potential interactions as either contraindicated, major, moderate or minor. For antiretroviral DDIs, the Liverpool Drug Interactions Checker from the University of Liverpool was also used to further describe interactions observed.

Results

In 1074 patients with suspected meningitis, pDDIs were present in 959 (overall prevalence = 89.3%) during the analyzed 30 day window. In total, 278 unique interacting drug pairs were identified resulting in 4582 pDDI events. Of all patients included in this study there was a mean frequency of 4.27 pDDIs per patient. Of the 4582 pDDI events, 11.3% contraindicated, 66.4% major, 17.4% moderate and 5% minor pDDIs were observed. Among all pDDIs identified, the most prevalent drugs implicated were fluconazole (58.4%), co-trimoxazole (25.7%), efavirenz (15.6%) and rifampin (10.2%). Twenty-one percent of the contraindicated pDDIs and 27% of the major ones involved an antiretroviral drug. Increased likelihood of QT interval prolongation was the most frequent potential clinical outcome. Dissonance in drug interaction checkers was noted requiring clinicians to consult more than one database in making clinical decisions about drug combinations.

Conclusions

The overall prevalence of pDDIs in this population is high. An understanding of drug combinations likely to result in undesired clinical outcomes, such as QT interval prolongation, is paramount. This is especially important in resource limited settings where availability of therapeutic drug monitoring and laboratory follow-up are inconsistent. Adequate quantification of the increased likelihood of adverse clinical outcomes from multiple drug-drug interactions of the same kind in a single patient is needed to aid clinical decisions in this setting.

Pilot study: Evaluation of potential drug-drug interactions in hospitalized pediatric patients

PURPOSE

Evaluate the type and severity of potential drug-drug interactions and identify risk factors involved, in pediatric patients admitted in a hospital setting.

METHODS

Transversal retrospective analytical study was carried out with hospitalized pediatric patients from a Hospital in the West of Mexico, second and third level. The patients included were ≤18 years old hospitalized in the children wards; those admitted at the emergency room, neonatal intermediate and intensive therapy units were not included. Medical prescriptions were reviewed taking into consideration anthropometric characteristics, diagnosis and number of drugs prescribed to identify potential drug-drug interactions using Micromedex 2.0 database.

RESULTS

88 patients were included, an average of 4.6 ± 2.8 of drugs were prescribed per patient. 37 subjects (42%) presented some degree of potential drug-drug interactions of which 25.5% were major and 27.7% moderate according to the software. Identified risk factors were: age ≥ 4 years (OR 1.917; 95% CI 1.081-3.399), BSA ≥ 0.8m2(OR 1.825; 95% CI 1.021-3.263), height ≥ 1 m (OR 2.556;95% CI 1.322 - 4.941), and number of prescribed medications ≥ 4 (OR 2.106;95% CI 1.248 - 3.556).

CONCLUSION

Some of the interactions found were for the benefit of the patient, but others were considered undesirable because they altered the pharmacokinetics of some of the medications administered. Detecting in time the harmful interactions for a patient may favor the patient's safety.

[Potential drug interactions in adults and the elderly in primary health care]

The objective of the present study was to characterize the potential drug interactions (PDI), estimating the factors associated to their occurrence in adults and the elderly assisted by the Programa Médico de Família de Niterói, Rio de Janeiro. This is a sub-study of STUDY DIGITALIS, which included individuals enrolled in the Niteroi Family Medical Program (45-99 years). In this study, 341 individuals with a prescription of two or more drugs were analyzed. The classification of PDI followed MICROMEDEX. There were 113 different interactions. Of the total number of individuals, 63.6% had at least one PDI. The variables with higher probability of PDI were: lower level of schooling; income less than R$800.00; absence of health plan; previous diagnosis of hypertension and diabetes; use of 5 or more medications prescribed. After adjustment, the variables previous diagnosis of hypertension and diabetes and use of 5 or more prescription drugs remained statistically significant. Careful management of primary care treatment with monitoring is important in patients with PDI, especially in patients who are more susceptible.

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

Aims

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

Material and methods

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

Results

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

Conclusion

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

Potential drug-drug interactions among pneumonia patients: do these matter in clinical perspectives?

BACKGROUND

Pneumonia patients are usually hospitalized due to severe nature of the disease or for the management of comorbid illnesses or associated symptoms. Such patients are prescribed with multiple medications which increase the likelihood of potential drug-drug interactions (pDDIs). Therefore, in this study the prevalence, levels (severity and documentation), predictors (risk factors), and clinical relevance of pDDIs among inpatients diagnosed with pneumonia have been investigated.

METHODS

Clinical records of 431 hospitalized patients with pneumonia were checked for pDDIs using drug interactions screening software (Micromedex-DrugReax). Odds-ratios for predictors were calculated using logistic regression analysis. Clinical relevance of pDDIs was assessed by evaluation of patients' clinical profiles for potential adverse outcomes of the most frequent pDDIs. Abnormal patients' signs/symptoms and laboratory investigations indicating adverse outcomes of interactions were reported.

RESULTS

Of total 431 profiles, pDDIs were reported in 73.1%. Almost half of the profiles were having major-pDDIs (53.8%). Total number of pDDIs were 1318, of which 606 were moderate- and 572 were major-pDDIs. Patient's profiles identified with the most frequent interactions were presented with signs, symptoms, and abnormalities in labs indicating decrease therapeutic response, electrolyte abnormalities, hypoglycemia, bleeding, hepatotoxicity, and hypertension. These adverse events were more prevalent in patients taking higher doses of the interacting drugs as compared to lower doses. Logistic regression analysis revealed significant association for major-pDDIs with 6-10 prescribed medicines (OR = 26.1; p = 0.002), > 10 prescribed medicines (OR = 144; p <  0.001), and tuberculosis (OR = 8.2; p = 0.004).

CONCLUSIONS

PDDIs are highly prevalent in patients with pneumonia. Most frequent and clinically important pDDIs need particular attention. Polypharmacy and tuberculosis increase the risk of pDDIs. Identifying patients more at risk to pDDIs and careful monitoring of pertinent signs/symptoms and laboratory investigations are important measures to reduce pDDIs and their related adverse consequences.

Studying the Prevalence of Medical Interventions in the Recipes

BACKGROUND:

Drug interaction is a term used to refer to unfavourable side effects caused by mixing or taking two or more drugs simultaneously. Although it is not possible to identify all drug interactions, awareness of therapeutic team of potential drug interactions, risk factors that enhance the possibility of these interactions and familiarity with mechanisms of drug interactions can help reduce real drug interactions.

AIM:

The present research seeks to study the frequency and intensity of possible interactions among various age groups and their correlation with doctor’s speciality, time of drug prescription, patient’s gender, etc.

MATERIAL AND METHOD:

This is observational, cross-sectional research conducted in spring and winter to study the prevalence of drug interactions among 6000 recipes belonging to 2 private and 2 public drug stores. The information associated with recipes was recorded, and drug interactions were studied based upon quick index of interactions using Up to Date software. Quick index of medical interactions is a response to data dealing with how drugs interact with one another. The risk factor is divided into groups A, B, C, D, and X according to this index with each one having its own definition. The data analysis was studied in terms of prevalence type of drug interactions and the possible correlation with other parameters. SPSS v.16 was used for statistical analysis.

RESULTS:

The average age of the patients was 42.07 ± 21.56 years. The frequency of male patients was 41.7%. An average number of 4.82 ± 1.91 drugs were prescribed for each patient and an average number of 1.95 ± 2.40 drugs had interaction with one another with levels C, D, and X having the following drug interaction levels: 1.60 ± 2.05, 0.275 ± 0.69, and 0.072 ± 0.31. No such interactions were observed in 31.1% (1846 cases) of recipes. The presence of drug interaction was statistically significant in terms of age, season, drug store and speciality of doctor (P-value < 0.05). The average number of interactions in the recipes issued by psychologists, cardiologists, rheumatologist, neurologists, and general practitioners was more, and this result was statistically significant (P-value < 0.05).

CONCLUSION:

Considering the results achieved in this research, we may conclude that the drug interactions in recipes exhibit a noticeable frequency with the highest frequency observed in level C influenced by factors such as age, season, class of drugs, and expertise of the doctor.

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.

Potential Drug-drug Interactions at a Referral Pediatric Oncology Ward in Iran: A Cross-sectional Study

Incidence of drug-drug interactions (DDIs) has been widely reported; however, such reports in pediatric oncology patients still remain scarce. We studied frequency and demographic correlates of moderate and major DDIs at a pediatric oncology ward in Isfahan, Iran. All pediatric oncology patients admitted to the Omid hospital during a 6-month period (2017) who received at least 2 anticancer or non-anticancer drugs concomitantly were included in our study. Potential DDIs between anticancer and non-anticancer drugs during hospitalization was identified using Lexi-Interact on-line software. We detected 194 DDIs with moderate or major severity for our included 115 patients. Mechanistically, most of DDIs (56.4%) were pharmacodynamic. Systematic use of corticosteroids (82.0%), antimetabolites (77.0%), and antiemetic drugs (69.5%) were the most frequent medication classes responsible for detected DDIs. The interaction between aminoglycosides and the third generation cephalosporins was the most common (13.9%) non-anticancer DDI. The only identified interaction between 2 anticancer drugs was doxorubicin with cyclophosphamide. Age, sex, and the number of administered medications were associated with DDIs. Potential moderate or major DDIs occur frequently among pediatric cancer patients. More studies are needed to assess clinical and economic implications of DDIs in pediatric oncology patients.

Examining the effect of prescription sequence on developing adverse drug reactions: The case of renal failure in diabetic patients

OBJECTIVES

While the effect of medications in development of Adverse Drug Reactions (ADRs) have been widely studied in the past, the literature lacks sufficient coverage in investigating whether the sequence in which [ADR-prone] drugs are prescribed (and administered) can increase the chances of ADR development. The present study investigates this potential effect by applying emergent sequential pattern mining techniques to electronic health records.

MATERIALS AND METHODS

Using longitudinal medication and diagnosis records from more than 377,000 diabetic patients, in this study, we assessed the possible effect of prescription sequences in developing acute renal failure as a prevalent ADR among this group of patients. Relying on emergent sequential pattern mining, two statistical case-control approaches were designed and employed for this purpose.

RESULTS

The results taken from the two employed approaches (i.e. 76.7% total agreement and 68.4% agreement on the existence of some significant effect) provide evidence for the potential effect of prescription sequence on ADRs development evidenced by the discovery that certain sequential patterns occurred more frequently in one group of patients than the other.

CONCLUSION

Given the significant effects shown by our data analyses, we believe that design and implementation of automated clinical decision support systems to constantly monitor patients' medication transactions (and the sequence in which they are administered) and make appropriate alerts to prevent certain possible ADRs, may decrease ADR occurrences and save lives and money.

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.

Potential Drug-Drug Interactions in a Cohort of Elderly, Polymedicated Primary Care Patients on Antithrombotic Treatment

INTRODUCTION

Drug-drug interactions (DDIs) are an important risk factor for adverse drug reactions. Older, polymedicated patients are particularly affected. Although antithrombotics have been detected as high-risk drugs for DDIs, data on older patients exposed to them are scarce.

METHODS

Baseline data of 365 IDrug study outpatients (≥ 60 years, use of an antithrombotic and one or more additional long-term drug) were analyzed regarding potential drug-drug interactions (pDDIs) with a clinical decision support system. Data included prescription and self-medication drugs.

RESULTS

The prevalence of having one or more pDDI was 85.2%. The median number of alerts per patient was three (range 0-17). For 58.4% of the patients, potential severe/contraindicated interactions were detected. Antiplatelets and non-steroidal anti-inflammatory drugs (NSAIDs) showed the highest number of average pDDI alert involvements per use (2.9 and 2.2, respectively). For NSAIDs, also the highest average number of severe/contraindicated alert involvements per use (1.2) was observed. 91.8% of all pDDI involvements concerned the 25 most frequently used drug classes. 97.5% of the severe/contraindicated pDDIs were attributed to only nine different potential clinical manifestations. The most common management recommendation for severe/contraindicated pDDIs was to intensify monitoring. Number of drugs was the only detected factor significantly associated with increased number of pDDIs (p < 0.001).

CONCLUSION

The findings indicate a high risk for pDDIs in older, polymedicated patients on antithrombotics. As a consequence of patients' frequently similar drug regimens, the variety of potential clinical manifestations was small. Awareness of these pDDI symptoms and the triggering drugs as well as patients' self-medication use may contribute to increased patient safety.

Potential Drug-Drug Interactions with Antimicrobials in Hospitalized Patients: A Multicenter Point-Prevalence Study

Background

Improper use of antimicrobials can cause adverse drug events and high costs. The purpose of this study was to investigate the frequency and potential drug–drug interactions associated with antimicrobials among hospitalized patients.

Material/Methods

This study was conducted on the same day in 5 different hospitals in Turkey. We included patients aged ≥18 years who received at least 1 antimicrobial drug and at least 1 of any other drug. The Micromedex^® online drug reference system was used to control and describe the interactions. Drug interactions were classified as contraindicated, major, moderate, and minor.

Results

Potential drug–drug interactions with antimicrobials were 26.4% of all interactions. Five (42%) of 12 contraindicated interactions and 61 (38%) of 159 major interactions were with antimicrobials. Quinolones, triazoles, metronidazole, linezolid, and clarithromycin accounted for 173 (25.7%) of 673 prescribed antimicrobials, but were responsible for 141 (92.1%) of 153 interactions. In multivariate analysis, number of prescribed antimicrobials (odds ratio: 2.3001, 95% CI: 1.6237–3.2582), number of prescribed drugs (odds ratio: 1.2008, 95% CI: 1.0943–1.3177), and hospitalization in the university hospital (odds ratio: 1.7798, 95% CI: 1.0035–3.1564) were independent risk factors for developing drug interactions.

Conclusions

Due to risk of drug interactions, physicians should be more cautious when prescribing antimicrobials, particularly when prescribing quinolones, linezolid, azoles, metronidazole, and macrolides.

A multicentered pharmacoepidemiological approach to evaluate clinically significant potential drug–drug interactions in medical intensive care settings in Pakistan

Background:

Iatrogenic injuries due to drug–drug interactions are particularly significant in critical care units because of the severely compromised state of the patient. The risk further increases with the use of multiple drugs, increasing age, and stay of the patient.

Objective:

The aim was to assess potential drug–drug interactions, evaluate clinically significant potential drug–drug interactions and their predictors in medical intensive care units of tertiary hospitals in Pakistan.

Methods:

Analysis of patient data collected from medical intensive care units of tertiary hospitals in Pakistan were carried out using Micromedex DrugReax. Various statistical tools were applied to identify the significance of associated predictors.

Results:

In a total of 830 patients, prevalence of potential drug–drug interactions was found to be 39%. These attributed to 190 drug combinations, of which 15.4% were clinically significant. A significant association of potential drug–drug interactions was present with number of prescribed drugs, age, and gender. In terms of clinically significant potential drug–drug interactions, the association was significant with increasing age. Moreover, one-way analysis of variance revealed a significant difference in the means of potential drug–drug interactions among the four hospitals.

Conclusion:

A prevalence of 39% potential drug–drug interactions was observed in patients of medical intensive care unit, with 22.8% being clinically significant. These attributed to nine drug pairs and could easily be avoided to reduce the risk of adverse effects from potential drug–drug interactions.

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.

Systemic anticancer therapy (SACT) for lung cancer and its potential for interactions with other medicines

Background

Systemic anticancer therapy, comprising chemotherapy agents alongside targeted therapies and immunotherapy, is clinically indicated for late-stage lung cancer. It is delivered in regimens often containing multiple anticancer agents as well as supportive care medicines to reduce side effects, raising potential for polypharmacy and therefore the possibility of drug–drug interactions with medicines taken for comorbidities. A pharmacy-led process commonly performed to assist safe prescribing in secondary care is medicines reconciliation; its benefit in minimising interactions involving systemic anticancer therapy medicines has not been assessed previously.

Objectives

The objectives were to characterise the potential drug–drug interactions between systemic anticancer therapy medicines for lung cancer and other medicines and to evaluate the rate of medicines reconciliation being performed and the extent of documentation of potential interactions (clinical audit).

Methodology

This retrospective case series study involved recording the medicines being taken by lung cancer patients undergoing systemic anticancer therapy elicited in consultations at Chelsea and Westminster Hospital, United Kingdom. Potential interactions were identified and characterised in terms of severity using the British National Formulary and other sources. Patient consultation records were also searched for documentation of medicines reconciliation and acknowledgement of potential drug–drug interactions.

Results

Twenty-three patients were included in this study. Eighty-eight potential drug–drug interactions were identified across 21 patients, 39% (34/88) of which involved the supportive care medicine dexamethasone. 3.0% of consultations included a documented medicines reconciliation, and 15.9% of potential interactions were documented in the notes, with no correlation between the two. Potentially serious interactions were significantly more likely to be documented (p < 0.05).

Conclusions

Many potential drug–drug interactions involving anticancer agents and supportive care medicines exist; particular attention should be paid to dexamethasone. Documentation of interactions and medicines reconciliation occur much less often than expected, suggesting there is scope for implementing methods of safe prescribing to prevent adverse drug effects.

Interações medicamentosas potenciais entre medicamentos psicotrópicos dispensados

RESUMO Objetivo Estimar a frequência e caracterizar as interações medicamentosas potenciais entre fármacos psicotrópicos sujeitos a controle especial pela portaria 344/98 da Agência Nacional de Vigilância Sanitária (Anvisa), os quais foram prescritos e dispensados em uma farmácia pública do Município de Cascavel, Paraná. Métodos Estudo retrospectivo com desenho seccional foi realizado em uma Farmácia Pública Municipal. A amostra foi composta por prescrições de medicamentos sujeitos a controle especial, dispensados entre primeiro de julho a 31 de agosto de 2010. As prescrições retidas na farmácia foram analisadas retrospectivamente e as informações, coletadas. As interações medicamentosas potenciais foram identificadas em 824 prescrições. Resultados As prescrições eram na maioria para pacientes do sexo feminino e com idade entre 19 e 59 anos. Em relação à especialidade do prescritor, 30,6% foram prescritas por psiquiatra. Em 77,9% das prescrições identificou-se pelo menos uma interação medicamentosa potencial. Foram descritas 54 diferentes interações medicamentosas potenciais, sendo 34 graves e 20 moderadas. Encontrou-se uma correlação linear entre medicamentos prescritos e interações medicamentosas potenciais (p valor < 0,001). Conclusão O presente estudo identificou uma alta frequência de interações medicamentosas potenciais envolvendo fármacos de controle especial e uma associação positiva entre o número de fármacos prescritos com a maior frequência dessas interações.

Effect of Continuity of Care on Drug-Drug Interactions

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Prevalence and predictors of potential drug-drug interactions in patients of internal medicine wards of a tertiary care hospital in India

Background

Drug-drug interactions are a major source of adverse drug events (ADEs). Polypharmacy, age and the number of comorbid conditions are important predictors of adverse drug interactions. ADEs account for up to 5% of hospital admissions per year and an increase in the length of hospital stay.

Objective

To find the prevalence and predictors of potential drug-drug interactions (pDDIs) in patients admitted to the wards of an internal medicine department of a tertiary care hospital.

Method

Patients admitted to internal medicine wards with prescriptions having more than one drug were selected. Demographic details including age, gender, number of comorbid conditions, number of drugs prescribed and the disease for which the patient was admitted were recorded in a case record form. Interactions were checked using Micromedex DrugReax software.

Results

A total of 939 patients were recruited for this study based on inclusion criteria. 433 prescriptions (46%) had one or more pDDIs, with a range of 1-13 drug interactions per prescription. A total of 1395 drug interactions were found, with 866 moderate drug interactions (62%), 435 major interactions (31.1%) and 89 minor interactions (6.3%). During the study period only three contraindicated drug combinations (0.2%) were recorded. A significant association (p<0.01) was found between the number of pDDIs and predictors, age and number of drugs.

Conclusion

A total of 433 prescriptions (46%) had one or more pDDIs. Older patients and those prescribed >6 drugs are at major risk for occurrence of pDDIs. Moderate severity interactions were the highest number followed by major severity interactions.

Prevalence study on potential drug–drug interaction in cancer patients in Piacenza hospital’s Onco-Haematology department

Background

Cancer patients can be a human model of potential drug interactions. Usually they receive a large number of different medications, including antineoplastic agents, drugs for comorbid illness and medication for supportive care, however information about these interactions are fragmented and poor.

Objective

We assessed a prospective study to evaluate the prevalence of drug interaction among patients hospitalized in the Onco-Haematology department, Hospital of Piacenza.

Methods

Data on drugs administered for cancer, comorbidities, or supportive care were collected from different computerized prescription software in use in the department; we compared them with a database to focus on the co-administration of drugs. A literature review was performed to identify major potential drug interaction and to classify them by level of severity and by strengths of scientific evidence.

Results

In this study 284 cancer patients were enrolled; patients had taken an average of seven drugs on each day of therapy plus chemotherapeutic agents, we identified 67 potential drug interactions. At least 53 patients had one potential drug interaction. Of all potential drug interactions 63 were classified as moderate severity and only four as major. In 55 cases chemotherapeutic agents were involved in possible interactions with supportive care drugs, meanwhile in 12 cases the potential drug interactions were between supportive care drugs.

Conclusions

In our centre, thanks to a computerized prescription software, integrated with caution alarm in case of possible interaction, we had a lower rate of potential drug interactions than the one from literature. It is possible to improve the software integrating the alarm with the potential drug interactions between chemotherapy agents and supportive care drugs.

Prevalence of potentially serious drug-drug interactions among South African elderly private health sector patients using the Mimica Matanović/Vlahović-Palčevski protocol

OBJECTIVES

To determine the prevalence of potentially serious drug-drug interactions (DDIs) and their relationship with gender and age, among elderly in South Africa.

METHODS

A cross-sectional study was conducted using pharmaceutical claims data for 2013, for a total of 103 420 medical scheme beneficiaries' ≥65 years. All medications dispensed within one calendar month where the days' supply of medication dispensed overlapped, were grouped as one prescription. DDIs per prescription were then identified using the Mimica Matanović/Vlahović-Palčevski DDI protocol. Results were interpreted using effect sizes, that is Cramér's V, Cohen's d and Cohen's ƒ² .

KEY FINDINGS

A total of 331 659 DDIs were identified on 235 870 (25.8%, N = 912 713) prescriptions (mean 0.36 (SD 0.7) (95% CI, 0.36 to 0.37)). Women encountered 63.5% of all DDIs. Effect sizes for the association between DDIs and age group (Cramér's V = 0.06), and gender (Cramér's V = 0.05) was negligible. There was no difference between men and women regarding the mean number of DDIs identified per prescription (Cohen's d = 0.10). The number of medicine per prescription (ƒ² = 0.51) was the biggest predictor of the DDIs. The most frequent interacting drug combinations were between central nervous system medicines (30.6%).

CONCLUSION

Our study is the first to report the prevalence of potentially serious DDIs among an elderly population in the South African private health sector utilising the Mimica Matanović/Vlahović-Palčevski DDI protocol. Overall, we identified DDIs in approximately 26% of the prescriptions in our study. Age and gender were not found to be predictors of potentially serious DDIs.

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

BACKGROUND

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

OBJECTIVES

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

DESIGN

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

PARTICIPANTS

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

MEASUREMENTS

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

RESULTS

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

CONCLUSION

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

Frequency and clinical relevance of potential cytochrome P450 drug interactions in a psychiatric patient population - an analysis based on German insurance claims data

BACKGROUND

Numerous drugs used in the treatment of psychiatric disorders are substrates of cytochrome P450 enzymes and are potential candidates for drug-drug interactions (DDIs).

METHODS

Claims data of a German statutory health insurance company from severely mentally ill patients who registered in an integrated care contract from August 2004 to December 2009 were analysed. We measured time periods of concomitant prescription of drugs that have been reported to interact via cytochrome P450, with a focus on drugs acting as strong inhibitors. Such drug-drug exposure (DDE) is an incontrovertible precursor of DDIs. We assessed whether potential DDIs were considered clinically relevant based on the prescribing information of the respective drugs.

RESULTS

Among all 1221 patients, 186 patients (15.2 %; Clopper-Pearson 95 % confidence interval (CI): 13.3-17.4 %) had at least one DDE prescription, and 58 patients (4.8 %; 95 % CI 3.6-6.1) had at least one DDE prescription involving a strong cytochrome P450 inhibitor. In 59 patients, (4.8 %; 95 % CI: 3.7-6.2 %) five or more DDEs were identified, and five or more DDEs with a strong inhibitor were identified in 18 patients (1.5 %; 95 % CI: 0.9-2.3). The rates of DDEs were 0.27 (Garwood 95%CI: 0.25-0.28) per person-year and 0.07 (95 % CI: 0.07-0.08) for strong-inhibitor DDEs. Four of the ten most frequent DDEs were identified as clinically relevant, and seven of the eight most frequent DDEs involving a strong inhibitor were clinically relevant.

CONCLUSIONS

The number of patients with DDEs was not alarmingly high in our sample. Nevertheless, prescription information showed that some prescribed drug combinations could result in serious adverse consequences that are known to weaken or strengthen the effect of the drugs and should therefore be avoided.

Potential drug-drug interactions in medical intensive care unit of a tertiary care hospital in Pakistan

Background Patients admitted to intensive care unit (ICU) present with severe and life-threatening illnesses. Most of them suffer from various comorbidities. They usually receive complex pharmacotherapy with large number of medicines which increase the risk of drug-drug interactions (DDIs). Objective The present report aimed to investigate prevalence and levels of potential DDIs (pDDIs) in medical ICU. Methods Medications profiles of 416 patients were checked for pDDIs using Micromedex Drug-Reax(®). Prevalence, levels of severity and levels of documentation were reported. Results Of total 416 patients, 310 were exposed to pDDIs (overall prevalence = 74.5 %). Likewise, a prevalence rate of 13.9 % was recorded for contraindicated pDDIs, 52.2 % for major pDDI and 58.4 % for moderate pDDI. This study reported 740 interacting drug pairs that were presented in total 1686 pDDIs. Of 1686 pDDIs, 4.3 % were of contraindicated severity, 33.8 % of major severity and 49.6 % of moderate severity, whereas 45.5 % were of fair scientific evidence and 41.4 % of good scientific evidence. Conclusion In this study, pDDIs were found highly prevalent in ICU patients at a rate of 74.5 %. Most of the pDDIs had moderate severity; however, substantial number of interactions (38.1 %) had major and contraindicated severity.

Drug-Drug Interaction Associated with Mold-Active Triazoles among Hospitalized Patients

The majority of hospitalized patients receiving mold-active triazoles are at risk of drug-drug interactions (DDIs). Efforts are needed to increase awareness of DDIs that pose a serious risk of adverse events. Triazoles remain the most commonly utilized antifungals. Recent developments have included the mold-active triazoles (MATs) itraconazole, voriconazole, and posaconazole, which are first-line agents for the treatment of filamentous fungal infections but have the potential for DDIs. This objective of this study was to evaluate the prevalence of triazole DDIs. Hospitalized U.S. adults with MAT use were identified in the Cerner HealthFacts database, which contained data from over 150 hospitals (2005 to 2013). The severities of DDIs with MATs were categorized, using drug labels and the drug information from the Drugdex system (Thompson Micromedex), into four groups (contraindicated, major, moderate, and minor severity). DDIs of minor severity were not counted. A DDI event was considered to have occurred if the following two conditions were met: (i) the patient used at least one drug with a classification of at least a moderate interaction with the MAT during the hospitalization and (ii) there was a period of overlap between the administration of the MAT and that of the interacting drug of at least 1 day. A total of 6,962 hospitalizations with MAT use were identified. Among them, 88% of hospitalizations with voriconazole use, 86% of hospitalizations with itraconazole use, and 93% of hospitalizations with posaconazole use included the use of a concomitant interacting drug. A total of 68% of hospitalizations with posaconazole use, 34% of hospitalizations with itraconazole use, and 20% of hospitalizations with voriconazole use included the use of at least one drug with a DDI of contraindicated severity. A total of 83% of hospitalizations with posaconazole use, 61% of hospitalizations with itraconazole use, and 82% of hospitalizations with voriconazole use included the use of at least one drug that resulted in a severe DDI. The findings of this study demonstrate that a majority of hospitalized patients receiving MAT are at risk for severe drug-drug interactions and highlight the need for antifungal stewardship.

Serious Drug-Drug Interactions in the Prescriptions of Diabetic Patients

A large number of drugs are introduced every year, and newer interactions between medications are increasingly reported. Clinically significant drug interactions can occur when two or more drugs are taken in combination. With the continuing increase in the list of drugs capable of interactions, detection of these interactions from prescriptions becomes more important to ensure effective patient care. The aim of this study is to identify the possible drug interactions in the prescriptions of diabetic inpatients and to make physicians aware of these interactions to prevent the occurrence of clinically adverse effects. In a specially designed and validated data entry format, data for the following criteria were collected: drugs prescribed, major drug class prescribed, pharmacological classification of the observed drug interaction, and frequently occurring drug interactions. All the possible drug interactions were identified and evaluated using standard drug interaction reference books and databases. During the study period, 50 prescriptions of diabetic inpatients were screened randomly. Out of these prescriptions, 35 (70%) prescriptions had at least one possible drug-drug interaction. The major classes of drugs causing interactions included cardiac drugs (92%), analgesic drugs (66%), antibiotic drugs (52%), antidiabetic drugs (26%), diuretic drugs (26%), and antipsychotic drugs (24%). This study showed that 34 (68%) of the above prescriptions had minor interactions, 33(66%) had moderate interactions, and 10 (20%) had severe interactions. Of these, the drugs prescribed specifically for diabetes caused only nine moderate interactions. Thus, screening of prescriptions by the clinical pharmacist will help to minimize clinical occurrence of major/severe drug interactions in diabetic patients.

A pilot study on the impact of known drug-drug interactions in cancer patients

Background

When a patient concomitantly uses two or more drugs, a drug-drug interaction (DDI) can possibly occur, potentially leading to an increased or decreased clinical effect of a given treatment. Cancer patients are at high risk of such interactions because they commonly receive multiple medications. Moreover, most cancer patients are elderly and require additional medications for comorbidities. Aim of this preliminary observational study was to evaluate the incidence of well known and established DDIs in a cohort of cancer outpatients undergoing multiple treatments.

Methods

Anamnestic and clinical data were collected for 64 adult patients in the ambulatory setting with malignant solid tumors who were receiving systemic anticancer treatment.

Patients also declared all drugs prescribed by other specialists or self-taken in the previous 2 weeks. DDIs were divided into two different groups: ‘neoplastic DDIs’ (NDDIs), involving antitumoral drugs, and ‘not neoplastic DDIs’ (nDDIs), involving all other classes of drugs. The severity of DDIs was classified as major, moderate and minor, according to the ‘Institute for Pharmacological Research Mario Negri’ definition.

Results

About 34 % of cancer outpatients within our cohort were prescribed/assumed interacting drug combinations. The most frequent major NDDIs involved the anticoagulant warfarin (33 % of total NDDIs) that, in association with tamoxifen, or capecitabine and paclitaxel, increased the risk of haemorrhage. About 60 % of nDDIs involved acetylsalicylic acid.

Conclusions

Overall, 16 % of DDIs were related to an A-level strength of recommendation to be avoided. The lack of effective communication among specialists and patients might have a role in determining therapeutic errors. Our pilot study, although limited by a small cohort size, highlights the urgent need of implementing the clinical management of cancer outpatients with new strategies to prevent or minimize potential harmful DDIs.

Evaluation of Potential Drug-Drug Interactions with Antidepressants in Two Tertiary Care Hospitals

BACKGROUND

Limited resources of healthcare system and high use of antidepressants have raised some serious concerns regarding proper surveillance system of prescribed medicines. Not much literature is available from Pakistan regarding the potential drug-drug interactions (pDDIs) associated with antidepressants.

OBJECTIVE

The objective of this study was to assess the frequency of pDDIs associated with antidepressants, their severity, significance and their association with patient characteristics.

MATERIALS AND METHODS

A prospective, observational study was conducted in two major hospitals of Karachi for the period of three months. Patient profiles, medication charts, and physician notes were thoroughly reviewed to gather all the relevant information. Inclusion and exclusion criteria were set prior to data collection. The collected data was then analysed using Micromedex Drug-REAX System. Descriptive and binomial logistic regression analysis was used to express results.

RESULTS

Of 245 prescriptions reviewed, 141 prescriptions had at least one pDDI (57.5%). A total of 181 pDDIs were identified in prescription containing antidepressant. The ratio of pDDI per prescriptions was 0.78. 42.5% interactions were moderate in severity, 30% of interactions were rapid in onset, and 43% were considered as significant interactions. Polypharmacy (OR=3.41, p< 0.001) and presence of chronic problems (OR=2.14, p=0.002) were significantly associated with the occurrence of pDDIs. Citalopram and diclofenac (11.6%) was commonly prescribed interacting pair in this study.

CONCLUSION

The findings of this study recorded high frequency of antidepressants associated pDDIs. Our results confirm the significant association of polypharmacy with the occurrence of pDDIs with antidepressants. Future studies are warranted to establish these results by including hospitals in different parts of the country.

Lucky guess or knowledge: a cross-sectional study using the Bland and Altman analysis to compare confidence-based testing of pharmacological knowledge in 3rd and 5th year medical students

Multiple-choice-questions are common in medical examinations, but guessing biases assessment results. Confidence-based-testing (CBT) integrates indicated confidence levels. It has been suggested that correctness of and confidence in an answer together indicate knowledge levels thus determining the quality of a resulting decision. We used a CBT approach to investigate whether decision quality improves during undergraduate medical education. 3rd- and 5th-year students attended formative multiple-choice exams on pharmacological issues. Students were asked to indicate their confidence in a given answer. Correctness of answers was scored binary (1-correct; 0-wrong) and confidence levels were transformed to an ordinal scale (guess: 0; rather unsure: 0.33; rather sure: 0.66; very sure: 1). 5th-year students gave more correct answers (73 ± 16 vs. 49 ± 13 %, p < 0.05) and were on average more confident regarding the correctness of their answers (0.61 ± 0.18 vs. 0.46 ± 0.13, p < 0.05). Correlation of these parameters was stronger for 5th-year students (r = 0.81 vs. r = 0.52), but agreement of confidence and correctness ('centration') was lower. By combining the Bland-and-Altman approach with categories of decision-quality we found that 5th-year students were more likely to be 'well-informed' (41 vs. 5 %), while more 3rd-students were 'uninformed' (24 vs. 76 %). Despite a good correlation of exam results and confidence in given answers increased knowledge might be accompanied by a more critical view at the own abilities. Combining the statistical Bland-and-Altman analysis with a theoretical approach to decision-quality, more advanced students are expected to apply correct beliefs, while their younger fellows are rather at risk to hesitate or to act amiss.

Potential drug-drug interactions in hospitalized patients undergoing systemic chemotherapy: a prospective cohort study

BACKGROUND

Adverse drug-drug interactions (DDI) are a major cause of morbidity and mortality in susceptible populations. Cancer patients are a population at high risk for DDI especially because they commonly receive several drugs concomitantly. The knowledge about the most common interactions between drugs used in oncology inpatients is essential to reduce drug-related problems and increase the safety and efficacy of the therapy.

OBJECTIVE

To assess the frequency of potential DDI throughout the hospital stay of cancer patients undergoing systemic chemotherapy, describe their epidemiology, and identify risk factors for major DDI. Setting An oncology-hematology inpatient unit of a public hospital in southern Brazil.

METHOD

Drug prescriptions were prospectively reviewed throughout the hospital stay of patients admitted for systemic chemotherapy. Descriptive statistics and Poisson regression were used for data analysis.

MAIN OUTCOME MEASURE

Potential DDI and their characteristics.

RESULTS

The cohort consisted of 113 patients, who used a mean of 8.9 ± 2.7 drugs/day. All patients had at least one potential DDI (median, 7.0/patient; 25th-75th percentile, 3.5-12.0), and 46 % of the patients had at least one DDI classified as major, i.e. that it may result in death, hospitalization, permanent injury, or therapeutic failure. Only 13.7 % of all interactions involved antineoplastic agents, identified in 62.8 % of patients. Most interactions were of moderate severity, 6.4 % were major, and 8.5 % had a recommendation for therapy modification. Multivariate analysis revealed mean number of drugs prescribed [relative risk (RR) for each additional drug: 1.12; 95 % confidence interval (CI) 1.07-1.17; P < 0.01] and age ≥60 years (RR 1.48; 95 % CI 1.03-2.14; P < 0.01) as independent risk factors for major DDI.

CONCLUSION

Potential DDI were highly frequent in this cohort. Older age and number of drugs prescribed were more likely to lead to major interactions. Prospective surveillance is required to detect adverse DDI, aiming primarily at reducing the risk of toxicity or treatment failure.

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.

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.

A study on drug-drug interactions through prescription analysis in a South Indian teaching hospital

OBJECTIVE

The objective of this study was to assess the drug-drug interactions (DDIs) through prescription analysis among the inpatients of a South Indian teaching hospital.

METHODS

The study was a prospective observational prescription analysis conducted for a period of 6 months, from October 2010 to March 2011. The prescriptions having two or more drugs and where a DDI was suspected were selected by the physician in charge of the ward. The drugs in the prescription were then entered into the drug interaction checker software. The DDIs were classified based on the mechanism of interactions, severity of interactions, relation to the number of drugs prescribed, and disease conditions were also determined.

RESULTS

A total of 204 prescriptions were analyzed, of which 186 prescriptions had 856 DDIs. Most of the DDIs were pharmacokinetic drug interactions (42%) followed by unknown mechanisms (34%) and pharmacodynamic mechanisms (24%). The study findings showed that the prescriptions for cardiovascular with respiratory disease conditions had the greatest number of drug interactions on average. A severity assessment showed that majority of the DDIs were moderate (70%) followed by minor (28%). The study results showed that as the number of drugs increases in a prescription, the number of DDIs also increases. The interventions determined showed that dosage adjustment (12%) was to be followed in most of the DDIs.

CONCLUSION

This study assists in understanding the factors associated with DDIs that can help in safe and effective use of drugs in the future.

Prevention of inappropriate prescribing in hospitalized older patients using a computerized prescription support system (INTERcheck(®))

BACKGROUND

Polypharmacy is very common among older adults and can lead to inappropriate prescribing, poor adherence to treatment, adverse drug events and the prevalence of potential drug-drug interactions (DDIs). Electronic prescription database software may help to prevent inappropriate prescribing and minimize the occurrence of adverse drug reactions. INTERcheck(®) is a Computerized Prescription Support System (CPSS) developed in order to optimize drug prescription for elderly people with multimorbidity.

OBJECTIVES

The objectives of this study were (i) to evaluate the applicability of INTERcheck(®) as a means of reviewing the pharmacological profiles of elderly patients hospitalized in an acute geriatric ward in Northern Italy; and (ii) to evaluate the effectiveness of INTERcheck(®) in reducing potentially inappropriate medications (PIMs), potentially severe DDIs and the anticholinergic burden in daily practice.

METHODS

Two samples of elderly patients (aged 65+ years) hospitalized in a geriatric ward in Italy were enrolled throughout 2012. During the first (observation) phase, medications prescribed to 74 patients at admission and discharge were analyzed with INTERCheck(®) without any kind of interference based on information obtained from the software. During the second (intervention) phase, the treatment of 60 patients was reviewed and changed at discharge according to INTERCheck(®) suggestions.

RESULTS

In the observational period, the number of patients exposed to at least one PIM remained unchanged on both admission (n = 29; 39.1 %) and discharge (n = 28; 37.8 %). In the intervention phase, 25 patients (41.7 %) were exposed to at least one PIM at admission and 7 (11.6 %) at discharge (p < 0.001). The number of patients exposed to at least one potentially severe DDI decreased from 27 (45.0 %) to 20 (33.3 %), although the difference was not statistically significant (p = 0.703), while the number of new-onset potentially severe DDIs decreased from 37 (59.0 %) to 9 (33.0 %) [p < 0.001].

CONCLUSIONS

The use of INTERCheck(®) was associated with a significant reduction in PIMs and new-onset potentially severe DDIs. CPSSs combining different prescribing quality measures should be considered as an important strategy for optimizing medication prescription for elderly patients.

Drug-drug interactions in a cohort of hospitalized elderly patients

PURPOSE

The aim of this study is to assess the prevalence of patients exposed to potentially severe drug-drug interactions (DDIs) at hospital admission and discharge and the related risk of in-hospital mortality and adverse clinical events, readmission, and all-cause mortality at 3 months.

METHODS

This cross-sectional, prospective study was held in 70 Italian internal medicine and geriatric wards. Potentially severe DDIs at hospital admission and discharge; risk of in-hospital mortality and of adverse clinical events, readmission, and all-cause mortality at 3-month follow-up.

RESULTS

Among 2712 patients aged 65 years or older recruited at hospital admission, 1642 (60.5%) were exposed to at least one potential DDI and 512 (18.9%) to at least one potentially severe DDI. Among 2314 patients discharged, 1598 (69.1%) were exposed to at least one potential DDI and 1561 (24.2%) to at least one potentially severe DDI. Multivariate analysis found a significant association with an increased risk of mortality at 3 months in patients exposed to at least two potentially severe DDIs (Odds ratio 2.62; 95% confidence interval, 1.00-6.68; p = 0.05). Adverse clinical events were potentially related to severe DDIs in two patients who died in the hospital, in five readmitted, and one who died at 3 months after discharge.

CONCLUSIONS

Hospitalization was associated with an increase in potentially severe DDIs. A significant association was found for mortality at 3 months after discharge in patients with at least two potentially severe DDIs. Careful monitoring for potentially severe DDIs, especially those created at discharge or recently generated, is important to minimize the risk of harm.

Actual drug-drug interactions in elderly patients discharged from internal medicine clinic: a prospective observational study

PURPOSE

The aim of the study was to evaluate the incidence and type of actual drug-drug interactions (DDIs) that result in adverse drug reactions (ADRs) or diminished therapeutic effect in elderly patients within 30 days of discharge from an internal medicine clinic.

METHODS

A prospective observational study was conducted at the Internal Medicine Clinic of University Hospital Dubrava, Zagreb, Croatia, between October and December 2011. Patients aged ≥ 65 years discharged from the Internal Medicine Clinic during the study period with a prescription for two or more medications were eligible for inclusion in the study. A total of 222 patients were ultimately enrolled in the study. For each patient, potential DDIs were identified using Lexi-Interact software. The follow-up visit was scheduled approximately 30 days after discharge. Causality between DDIs and ADRs or diminished therapeutic effect of drugs was assessed by two independent clinicians.

RESULTS

Potential DDIs were identified in 190 (85.6 %) patients. Actual DDIs were detected in 21 (9.5 %) patients. In 19 patients, DDIs resulted in an ADR. Diminished therapeutic effect resulting from DDIs was detected in two patients. Angiotensin-converting enzyme inhibitors were the drug class most frequently associated with DDI-related ADRs.

CONCLUSIONS

A significant incidence of actual DDIs suggests that DDIs play an important role in patient safety. Drug therapy should be initiated if absolutely necessary, and the number of drugs used to treat elderly patients should be minimized to reduce the incidence of DDI-related adverse patient outcomes.