Evaluation of drug-drug interaction screening software combined with pharmacist intervention

The comorbidity and co-medication profile of patients with progressive supranuclear palsy

BACKGROUND

Progressive supranuclear palsy (PSP) is usually diagnosed in elderly. Currently, little is known about comorbidities and the co-medication in these patients.

OBJECTIVES

To explore the pattern of comorbidities and co-medication in PSP patients according to the known different phenotypes and in comparison with patients without neurodegenerative disease.

METHODS

Cross-sectional data of PSP and patients without neurodegenerative diseases (non-ND) were collected from three German multicenter observational studies (DescribePSP, ProPSP and DANCER). The prevalence of comorbidities according to WHO ICD-10 classification and the prevalence of drugs administered according to WHO ATC system were analyzed. Potential drug-drug interactions were evaluated using AiDKlinik®.

RESULTS

In total, 335 PSP and 275 non-ND patients were included in this analysis. The prevalence of diseases of the circulatory and the nervous system was higher in PSP at first level of ICD-10. Dorsopathies, diabetes mellitus, other nutritional deficiencies and polyneuropathies were more frequent in PSP at second level of ICD-10. In particular, the summed prevalence of cardiovascular and cerebrovascular diseases was higher in PSP patients. More drugs were administered in the PSP group leading to a greater percentage of patients with polypharmacy. Accordingly, the prevalence of potential drug-drug interactions was higher in PSP patients, especially severe and moderate interactions.

CONCLUSIONS

PSP patients possess a characteristic profile of comorbidities, particularly diabetes and cardiovascular diseases. The eminent burden of comorbidities and resulting polypharmacy should be carefully considered when treating PSP patients.

Experiences and Outcomes of Using e-Prescribing for Opioids: Rapid Scoping Review

BACKGROUND

e-Prescribing is designed to assist in facilitating safe and appropriate prescriptions for patients. Currently, it is unknown to what extent e-prescribing for opioids influences experiences and outcomes. To address this gap, a rapid scoping review was conducted.

OBJECTIVE

This rapid scoping review aims to (1) explore how e-prescribing has been used clinically; (2) examine the effects of e-prescribing on clinical outcomes, the patient or clinician experience, service delivery, and policy; and (3) identify current gaps in the present literature to inform future studies and recommendations.

METHODS

A rapid scoping review was conducted following the guidance of the JBI 2020 scoping review methodology and the World Health Organization guide to rapid reviews. A comprehensive literature search was completed by an expert librarian from inception until November 16, 2022. Three databases were electronically searched: MEDLINE (Ovid), Embase (Ovid), and Scopus (Elsevier). The search criteria were as follows: (1) e-prescribing programs targeted to the use or misuse of opioids, including those that were complemented or accompanied by clinically focused initiatives, and (2) a primary research study of experimental, quasi-experimental, observational, qualitative, or mixed methods design. An additional criterion of an ambulatory component of e-prescribing (eg, e-prescribing occurred upon discharge from acute care) was added at the full-text stage. No language limitations or filters were applied. All articles were double screened by trained reviewers. Gray literature was manually searched by a single reviewer. Data were synthesized using a descriptive approach.

RESULTS

Upon completing screening, 34 articles met the inclusion criteria: 32 (94%) peer-reviewed studies and 2 (6%) gray literature documents (1 thesis study and 1 report). All 33 studies had a quantitative component, with most highlighting e-prescribing from acute care settings to community settings (n=12, 36%). Only 1 (3%) of the 34 articles provided evidence on e-prescribing in a primary care setting. Minimal prescriber, pharmacist, and clinical population characteristics were reported. The main outcomes identified were related to opioid prescribing rates, alerts (eg, adverse drug events and drug-drug interactions), the quantity and duration of opioid prescriptions, the adoption of e-prescribing technology, attitudes toward e-prescribing, and potential challenges with the implementation of e-prescribing into clinical practice. e-Prescribing, including key features such as alerts and dose order sets, may reduce prescribing errors.

CONCLUSIONS

This rapid scoping review highlights initial promising results with e-prescribing and opioid therapy management. It is important that future work explores the experience of prescribers, pharmacists, and patients using e-prescribing for opioid therapy management with an emphasis on prescribers in the community and primary care. Developing a common set of quality indicators for e-prescribing of opioids will help build a stronger evidence base. Understanding implementation considerations will be of importance as the technology is integrated into clinical practice and health systems.

Comparative analysis of potential drug-drug interactions in a public and private hospital among chronic kidney disease patients in Khyber Pakhtunkhwa: A retrospective cross-sectional study

INTRODUCTION

Chronic kidney disease (CKD) is a significant public health challenge due to its rising incidence, mortality, and morbidity. Patients with kidney diseases often suffer from various comorbid conditions, making them susceptible to potential drug-drug interactions (pDDIs) due to polypharmacy and multiple prescribers. Inappropriate prescriptions for CKD patients and their consequences in the form of pDDIs are a major challenge in Pakistan.

AIM

This study aimed to compare the incidence and associated risk factors of pDDIs among a public and private sector hospital in Khyber Pakhtunkhwa, Pakistan.

METHOD

A retrospective cross-sectional study design was conducted to compare pDDIs among public and private sector hospitals from January 2023 to February 2023. Patients profile data for the full year starting from January 1 2022 to December 302022, was accessed All adult patients aged 18 years and above, of both genders, who currently have or have previously been diagnosed with end-stage renal disease (ESRD) were included. For assessing pDDIs, patient data was retrieved and checked using Lexicomp UpToDate® for severity and documentation of potential drug-drug interactions.

RESULTS

A total of 358 patients' data was retrieved (with n = 179 in each hospital); however, due to incomplete data, n = 4 patients were excluded from the final analysis. The prevalence of pDDIs was found to be significantly higher in private hospitals (84.7%) than in public hospitals (26.6%), with a p-value <0.001. Patients in the age category of 41-60 years (AOR = 6.2; p = 0.008) and those prescribed a higher number of drugs (AOR = 1.2; p = 0.027) were independently associated with pDDIs in private hospitals, while the higher number of prescribed drugs (AOR = 2.9; p = <0.001) was an independent risk factor for pDDIs in public hospitals. The majority of pDDIs (79.0%) were of moderate severity, and a significant number of patients (15.1%) also experienced major pDDIs, with a p-value <0.001. The majority of pDDIs had fair documentation for reliability rating in both public and private hospitals.

CONCLUSION

The prevalence of pDDIs was higher among CKD patients at private hospitals, and most of the pDDIs were of moderate severity. A considerable number of patients also experienced major pDDIs. The risk of experiencing pDDIs was found to be higher in older patients and among those prescribed a higher number of drugs.

Pharmacist-Driven Dosing Services and Pharmaceutical Care Increase Probability of Teicoplanin Target Concentration Attainment and Improve Clinical and Economic Outcomes in Non-Critically Ill Patients

INTRODUCTION

Pharmacist-driven (PD) dosing and monitoring services have been shown to improve the clinical and economic outcomes in patients treated with different antibiotics, other than teicoplanin. This study investigates the impact of PD dosing and monitoring services on the clinical and economic outcomes of non-critically ill patients receiving teicoplanin treatment.

METHODS

A single-center retrospective study was conducted. Patients were divided into the PD group and the non-PD (NPD) group. Primary outcomes included the achievement of target serum concentration, and a composite endpoint of all-cause mortality, intensive care unit (ICU) admission, and sepsis or septic shock development during hospitalization or within 30 days of hospital admission. The cost of teicoplanin, overall medication cost, and total cost during hospital stay were also compared.

RESULTS

A total of 163 patients from January to December 2019 were included and assessed. Seventy patients were assigned to the PD group and 93 to the NPD group. The PD group had a higher percentage of patients reaching the target trough concentration (54% versus 16%, p < 0.001). Around 26% of the patients in the PD group and 50% of the patients in the NPD group met the composite endpoint during their hospital stay (p = 0.002). The PD group exhibited a significantly lower incidence of sepsis or septic shock, shorter hospital stays, reduced drug costs, and lower total expenses.

CONCLUSIONS

Our study demonstrates that pharmacist-driven teicoplanin therapy can improve the clinical and economic outcomes for non-critically ill patients.

TRIAL REGISTRATION

https://www.chictr.org.cn ; identifier, ChiCTR2000033521.

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

Background

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

Methods

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

Results

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

Conclusion

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

Supplementary Information

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

Potential drug-drug interactions in patients with cardiovascular diseases: findings from a prospective observational study

Background

Patients with cardiovascular diseases (CVD) are at high risk of experiencing drug–drug interactions (DDIs). The objective of this study was to evaluate the frequency, level and risk factors associated with potential-DDIs (pDDIs) in hospitalized CVD patients at cardiology departments of two tertiary care hospitals in Quetta, Pakistan.

Methods

In the current prospective observational study, a total of 300 eligible CVD inpatients were evaluated for pDDIs using Lexicomp Interact®. The pDDIs were classified into class A (no known interaction); B (no action needed); C (monitor therapy: it is documented that the benefits of an interaction outweigh the risk, appropriately monitor therapy in order to avoid potential adverse outcomes); D (consider therapy modification: it is documented that proper actions must be taken to reduce the toxicity resulting from an interaction); X (avoid combination: the risk of an interaction outweighs the benefits and are usually contraindicated). Multivariate binary logistic regression analysis was used to find factors associated with the presence of Class-D and/or X pDDIs. A p-value < 0.05 was considered statistically significant.

Results

With a median of 8.50 pDDIs per patient, all patients (100%) had ≥ 1 pDDIs. Out of total 2787 pDDIs observed, 74.06% (n = 2064) were of moderate and (n = 483) 17.33% of major severity. Class C pDDIs were most common (n = 1971, 70.72%) followed by D (n = 582, 20.88%), B (n = 204, 7.32%) and X (n = 30, 1.08%). Suffering from cardiovascular diseases other than myocardial infarction (OR 0.053, p-value < 0.001) and receiving > 12 drugs (OR 4.187, p-value = 0.009) had statistical significant association with the presence of class D and/or X pDDIs.

Conclusion

In the current study, pDDIs were highly prevalent. The inclusion of DDI screening tools, availability of clinical pharmacists and paying special attention to the high-risk patients may reduce the frequency of pDDIs at the study sites.

Adverse Drug Events Caused by Drugs Contraindicated for Coadministration Reported in the Japanese Adverse Drug Event Report Database and Recognized by Reporters

The "INTERACTIONS" section of package inserts aims to provide alert-type warnings in clinical practice; however, these also include many drug-drug interactions that occur rarely. Moreover, considering that drug-drug interaction alert systems were created based on package inserts, repeated alerts can lead to alert fatigue. Although investigations have been conducted to determine prescriptions that induce drug-drug interactions, no studies have focused explicitly on the adverse events induced by drug-drug interactions. We, therefore, sought to investigate the true occurrence of adverse events caused by drug pair contraindications for coadministration in routine clinical practice. Toward this, we created a list of drug combinations that were designated as "contraindications for coadministration" and extracted the cases of adverse drug events from the Japanese Adverse Drug Event Report database that occurred due to combined drug usage. We then calculated the reporters' recognition rate of the drug-drug interactions. Out of the 2121 investigated drug pairs, drug-drug interactions were reported in 43 pairs, 23 of which included an injected drug and many included catecholamines. Warfarin potassium and miconazole (19 reports), azathioprine and febuxostat (11 reports), and warfarin potassium and iguratimod (six reports) were among the 20 most-commonly reported oral medication pairs that were contraindicated for coadministration, for which recognition rates of drug-drug interactions were high. Although these results indicate that only a few drug pair contraindications for coadministration were associated with adverse drug events (43 pairs out of 2121 pairs), it remains necessary to translate these findings into clinical practice.

Drug safety profiles in geriatric patients with Parkinson's disease using the FORTA (Fit fOR The Aged) classification: results from a mono-centric retrospective analysis

To reduce potentially inappropriate medications, the FORTA (Fit fOR The Aged) concept classifies drugs in terms of their suitability for geriatric patients with different labels, namely A (indispensable), B (beneficial), C (questionable), and D (avoid). The aims of our study were to assess the medication appropriateness in PD inpatients applying the FORTA list and drug-drug interaction software, further to assess the adequacy of FORTA list for patients with PD. We retrospectively collected demographic data, comorbidities, laboratory values, and the medication from the discharge letters of 123 geriatric inpatients with PD at the university hospital of Hannover Medical School. Patients suffered on average from 8.2 comorbidities. The majority of the medication was labeled A (60.6% of PD-specific and 40.9% of other medication) or B (22.3% of PD-specific and 26.9% of other medication). Administered drugs labeled with D were amantadine, clozapine, oxazepam, lorazepam, amitriptyline, and clonidine. Overall, 545 interactions were identified, thereof 11.9% severe interactions, and 1.7% contraindicated combinations. 81.3% of patients had at least one moderate or severe interaction. The FORTA list gives rational recommendations for PD-specific and other medication, especially for general practitioners. Considering the demographic characteristics and the common multimorbidity of geriatric PD patients, this study underlines the importance of awareness, education, and preventive interventions to increase drug safety.

Interventions to reduce medication errors in adult medical and surgical settings: a systematic review

Background and Aims:

Medication errors occur at any point of the medication management process, and are a major cause of death and harm globally. The objective of this review was to compare the effectiveness of different interventions in reducing prescribing, dispensing and administration medication errors in acute medical and surgical settings.

Methods:

The protocol for this systematic review was registered in PROSPERO (CRD42019124587). The library databases, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials were searched from inception to February 2019. Studies were included if they involved testing of an intervention aimed at reducing medication errors in adult, acute medical or surgical settings. Meta-analyses were performed to examine the effectiveness of intervention types.

Results:

A total of 34 articles were included with 12 intervention types identified. Meta-analysis showed that prescribing errors were reduced by pharmacist-led medication reconciliation, computerised medication reconciliation, pharmacist partnership, prescriber education, medication reconciliation by trained mentors and computerised physician order entry (CPOE) as single interventions. Medication administration errors were reduced by CPOE and the use of an automated drug distribution system as single interventions. Combined interventions were also found to be effective in reducing prescribing or administration medication errors. No interventions were found to reduce dispensing error rates. Most studies were conducted at single-site hospitals, with chart review being the most common method for collecting medication error data. Clinical significance of interventions was examined in 21 studies. Since many studies were conducted in a pre–post format, future studies should include a concurrent control group.

Conclusion:

The systematic review identified a number of single and combined intervention types that were effective in reducing medication errors, which clinicians and policymakers could consider for implementation in medical and surgical settings. New directions for future research should examine interdisciplinary collaborative approaches comprising physicians, pharmacists and nurses.

Lay summary

Activities to reduce medication errors in adult medical and surgical hospital areas

Introduction:

Medication errors or mistakes may happen at any time in hospital, and they are a major reason for death and harm around the world.

Objective:

To compare the effectiveness of different activities in reducing medication errors occurring with prescribing, giving and supplying medications in adult medical and surgical settings in hospital.

Methods:

Six library databases were examined from the time they were developed to February 2019. Studies were included if they involved testing of an activity aimed at reducing medication errors in adult medical and surgical settings in hospital. Statistical analysis was used to look at the success of different types of activities.

Results:

A total of 34 studies were included with 12 activity types identified. Statistical analysis showed that prescribing errors were reduced by pharmacists matching medications, computers matching medications, partnerships with pharmacists, prescriber education, medication matching by trained physicians, and computerised physician order entry (CPOE). Medication-giving errors were reduced by the use of CPOE and an automated medication distribution system. The combination of different activity types were also shown to be successful in reducing prescribing or medication-giving errors. No activities were found to be successful in reducing errors relating to supplying medications. Most studies were conducted at one hospital with reviewing patient charts being the most common way for collecting information about medication errors. In 21 out of 34 articles, researchers examined the effect of activity types on patient harm caused by medication errors. Many studies did not involve the use of a control group that does not receive the activity.

Conclusion:

A number of activity types were shown to be successful in reducing prescribing and medication-giving errors. New directions for future research should examine activities comprising health professionals working together.

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.

Potential drug-drug interactions associated with adverse clinical outcomes and abnormal laboratory findings in patients with malaria

BACKGROUND

Hospitalized patients with malaria often present with comorbidities or associated complications for which a variety of drugs are prescribed. Multiple drug therapy often leads to drug-drug interactions (DDIs). Therefore, the current study investigated the prevalence, levels, risk factors, clinical relevance, and monitoring parameters/management guidelines of potential DDIs (pDDIs) among inpatients with malaria.

METHODS

A retrospective cohort study was carried out at two tertiary care hospitals. A total of 398 patients' profiles were evaluated for pDDIs using the Micromedex Drug-Reax^®. Odds ratios were calculated to identify the strength of association between presence of DDIs and potential risk factors via logistic regression analysis. Further, the clinical relevance of frequent pDDIs was investigated.

RESULTS

Of 398 patients, pDDIs were observed in 37.2% patients, while major-pDDIs in 19.3% patients. A total of 325 interactions were found, of which 45.5% were of major- and 34.5% moderate-severity. Patients with the most common pDDIs were found with signs/symptoms and abnormalities in laboratory findings representing nephrotoxicity, hepatotoxicity, QT interval prolongation, and reduced therapeutic efficacy. The following drug pairs reported the highest frequency of adverse events associated with the interactions; calcium containing products-ceftriaxone, isoniazid-rifampin, pyrazinamide-rifampin, isoniazid-acetaminophen, and ciprofloxacin-metronidazole. The adverse events were more common in patients prescribed with the higher doses of interacting drugs. Multivariate regression analysis showed statistically significant association of pDDIs with 5-6 prescribed medicines (p = 0.01), > 6 prescribed medicines (p < 0.001), > 5 days of hospital stay (p = 0.03), and diabetes mellitus (p = 0.04).

CONCLUSIONS

PDDIs are commonly observed in patients with malaria. Healthcare professional's knowledge about the most common pDDIs could help in preventing pDDIs and their associated negative effects. Pertinent clinical parameters, such as laboratory findings and signs/symptoms need to be checked, particularly in patients with polypharmacy, longer hospital stay, and diabetes mellitus.

Potential Drug-Drug Interactions in Patients With Urinary Tract Infections: A Contributing Factor in Patient and Medication Safety

Introduction: Hospitalized patients with urinary tract infections (UTIs) often present with comorbid illnesses and are subsequently prescribed multiple medications, which increases the likelihood of drug-drug interactions. Therefore, this study aimed to explore the prevalence, levels, risk factors, and clinical relevance of potential drug-drug interactions (pDDIs) in hospitalized patients with UTIs. Secondly, we aimed to develop management guidelines and identify monitoring parameters for the most frequent interactions.

Methods: A retrospective cross-sectional study was conducted in internal medicine wards of two tertiary care hospitals in Peshawar, Khyber Pakhtunkhwa, Pakistan. The clinical profiles of 422 patients with UTIs were reviewed for pDDIs using the Micromedex Drug-Reax^®. Logistic regression was applied to assess the association of pDDIs with various risk factors. The clinical relevance of frequent pDDIs was identified by assessing the potential adverse outcomes of pDDIs including patients’ signs, symptoms, and abnormal laboratory findings.

Results: Of 422 patients, at least one pDDI was identified in 62.3% patients, while 40% patients had at least one major pDDI. A total of 1,086 pDDIs were identified, of which 53.4% and 39.3% were of moderate and major severity, respectively. Patients with most frequent pDDIs were presented with hypoglycemia, hepatotoxicity, nephrotoxicity, hypertension, and decreased therapeutic response. These adverse events were more prevalent in patients taking higher doses of interacting drugs. Multivariate regression analysis revealed significant association of pDDIs with six or more medicines (p < 0.001), diabetes mellitus (p < 0.001), ischemic heart disease (p = 0.02), and congestive cardiac failure (p = 0.04).

Conclusions: Patients with UTIs present with a considerable number of clinically important pDDIs. Polypharmacy, diabetes mellitus, ischemic heart disease, and congestive cardiac failure increase the risk of pDDIs. Knowledge about the most frequent pDDIs will enable healthcare professionals to implement optimized monitoring and management strategies regarding associated adverse consequences in order to ensure patient safety. Most of the interactions can be managed by considering alternative therapy and dose reduction.

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.

Drug-drug interactions and pharmacists' interventions among psychiatric patients in outpatient clinics of a teaching hospital in Saudi Arabia

Background

Lack of recognition of labeled drug-drug interactions (DDIs) is a type of medication error of particular relevance to the treatment of psychiatric patients. Pharmacists are in a position to detect and address potential DDIs.

Objective

This study aimed to explore pharmacists' role in the identification and management of DDIs among psychiatric patients in psychiatric outpatient clinics of a university-affiliated tertiary care hospital in Riyadh, Saudi Arabia.

Method

This study was a retrospective, cross-sectional medical chart review of patients visiting outpatient psychiatric clinics. It utilized medical records of patients who were taking any psychotropic medications and were prescribed at least one additional drug. The hospital Computerized Physician Order Entry system was used to identify DDIs and determine the pharmacists' interventions. The Beers criteria were applied to detect inappropriate prescribing among older patients.

Results

On average, the pharmacists intervened in 12 out of 213 (5.6%) cases of major or moderate DDIs. Older age, higher number of prescription medications, the severity of DDIs, and the utilization of lithium and anticoagulants were positively associated with the pharmacist undertaking an action.

Conclusion

Future studies should explore the prevalence rate of harmful DDIs among psychiatric patients on a large scale and examine the effectiveness of different pharmacy policies in the detection and management of DDIs.

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 pediatric patients admitted to intensive care unit of Khyber Teaching Hospital, Peshawar, Pakistan: A cross-sectional study

PURPOSE

To investigate frequencies, levels, clinical relevance and predictors of potential drug-drug interactions (pDDIs) in pediatric intensive care unit (PICU).

METHODS

Case notes of 411 patients were reviewed for pDDIs through Micromedex. Frequencies, levels and clinical relevance of pDDIs were reported. Logistic regression was applied to calculate the odds-ratios for predictors of pDDIs.

RESULTS

We recorded pDDIs in 59.4% patients. Major-pDDIs were found in 34.5% patients. Total 990 pDDIs were identified, of which, 37.8% were of moderate-severity and 30.6% of major-severity. Patient's case notes of top-ten pDDIs showed presence of signs/symptoms such as fever, jaundice, vomiting, anorexia, tachycardia, drowsiness, & lethargy; and abnormalities in labs such as total leukocytes count, blood urea nitrogen, alanine aminotransferase, & potassium-level. Odds of exposure to major-pDDIs were significantly higher in patients aged 6-12years (p=0.008); hospital stay of ≥7days (p=0.05); and ≥11 prescribed medicines (p<0.001).

CONCLUSION

Substantial numbers of patients in PICU are exposed to pDDIs. Major-pDDIs are of particular concern. Timely identification of pDDIs, preferably with computerized source, is crucial point for their management. Monitoring of clinically relevant parameters and identification of various predictors are needed to minimize or prevent the associated negative consequences of pDDIs.

Information Technology-Based Interventions to Improve Drug-Drug Interaction Outcomes: A Systematic Review on Features and Effects

The purpose of this systematic review was to identify features and effects of information technology (IT)-based interventions on outcomes related to drug-drug interactions (DDI outcomes). A literature search was conducted in Medline, EMBASE, and the Cochrane Library for published English-language studies. Studies were included if a main outcome was related to DDIs, the intervention involved an IT-based system, and the study design was experimental or observational with controls. Study characteristics, including features and effects of IT-based interventions, were extracted. Nineteen studies comprising five randomized controlled trials (RCT), five non-randomized controlled trials (NRCT) and nine observational studies with controls (OWC) were included. Sixty-four percent of prescriber-directed interventions, and all non-prescriber interventions, were effective. Each of the following characteristics corresponded to groups of studies of which a majority were effective: automatic provision of recommendations within the providers' workflow, intervention at the time of decision-making, integration into other systems, and requiring the reason for not following the recommendations. Only two studies measured clinical outcomes: an RCT that showed no significant improvement and an OWC that showed improvement, but did not statistically assess the effect. Most studies that measured surrogate outcomes (e.g. potential DDIs) and other outcomes (e.g. adherence to alerts) showed improvements. IT-based interventions improve surrogate clinical outcomes and adherence to DDI alerts. However, there is lack of robust evidence about their effectiveness on clinical outcomes. It is recommended that researchers consider the identified features of effective interventions in the design of interventions and evaluate the effectiveness on DDI outcomes, particularly clinical outcomes.

Risks of Adverse Events Following Coprescription of Statins and Calcium Channel Blockers: A Nationwide Population-Based Study

Some statins (simvastatin, lovastatin, and atorvastatin) are metabolized by cytochrome P450s 3A4 (CYP3A4). Inhibitors of CYP3A4 including some calcium channel blockers (CCBs) might increase statin blood concentration, owing to drug-drug interactions. Risk of adverse events such as acute kidney injury might occur following the coprescription of CYP3A4-metabolized statins and CCBs that inhibit CYP3A4.This was a population-based cohort study. The study analyzed data of patients treated between 1997 and 2011, retrieved from Taiwan's National Health Insurance database. We enrolled 32,801 patients who received coprescription of statins and CCBs that inhibit CYP3A4 (amlodipine, diltiazem, felodipine nicardipine, nifedipine, and verapamil). These patients were divided into 2 groups, according to whether they had received CYP3A4-metabolized statins (lovastatin, simvastatin, and atorvastatin) or non-CYP3A4-metabolized statins (fluvastatin, rosuvastatin, and pitavastatin). These 2 groups were 1:1 matched by age, gender, and Carlson comorbidity index. All outcomes were assessed within 90 days following drug coprescription.In this study, 5857 patients received coprescription of CYP3A4-metabolized statins and CCBs that inhibit CYP3A4. There were no differences in comorbidity or use of antihypertensive drugs between patients who received CYP3A4-metabolized statins and those who received non-CYP3A4-metabolized statins. Patients who received CYP3A4-metabolized statins had significantly higher risk of acute kidney injury (adjusted odds ratio [OR] = 2.12; 95% CI = 1.35-3.35), hyperkalemia (adjusted OR = 2.94; 95% CI = 1.36-6.35), acute myocardial infarction (adjusted OR = 1.55; 95% CI = 1.16-2.07), and acute ischemic stroke (adjusted OR = 1.35; 95% CI = 1.08-1.68) than those who received non-CYP3A4-metabolized statins.This nationwide cohort study demonstrated the increased risk of adverse events following the coprescription of CYP3A4-metabolized statins and CCBs that inhibit CYP3A4. Therefore, it is important to take into account the potential adverse events while coprescribing CYP3A4-metabolized statins and CCBs that inhibit CYP3A4.

The prevalence of major potential drug-drug interactions at a University health centre pharmacy in Jamaica

OBJECTIVE

To identify major potential drug-drug interactions (DDIs) on prescriptions filled at the University Health Centre Pharmacy, Mona Campus, Jamaica.

METHODS

This investigation utilised a cross-sectional analysis on all prescriptions with more than one drug that were filled at the Health Centre Pharmacy between November 2012 and February 2013. Potential DDIs were identified using the online Drug Interactions Checker database of Drugs.com.

RESULTS

During the period of the study, a total of 2814 prescriptions were analysed for potential DDIs. The prevalence of potential DDIs found during the study period was 49.82%. Major potential DDIs accounted for 4.7 % of the total number of interactions detected, while moderate potential DDIs and minor potential DDIs were 80.8 % and 14.5 % respectively. The three most frequently occurring major potential DDIs were amlodipine and simvastatin (n=46), amiloride and losartan (n=27) and amiloride and lisinopril (n=16).

CONCLUSION

This study has highlighted the need for educational initiatives to ensure that physicians and pharmacists collaborate in an effort to minimise the risks to the patients. These interactions are avoidable for the most part, as the use of online tools can facilitate the selection of therapeutic alternatives or guide decisions for closer patient monitoring and thus reduce the risks of adverse events.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Detection of potential drug-drug interactions for outpatients across hospitals

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