Performance of different data sources in identifying adverse drug events in hospitalized patients

Purpose: The incidence of adverse drug events (ADE) is an important parameter in determining the quality of medical care. We identified the probability that a specific data source would identify ADEs in patients on the oncology ward, that could be assigned to one substance. Methods: We captured all medical adverse events (AE) from five different data sources. Each AE was determined to be drug-related according to the WHO criteria and classified according to the severity, category, and causality of the ADE. Results: The study recorded 129 patients with 252 hospitalizations over a 5-month period. A total of 3,341 medical events were captured and resulted in 1,121 ADEs. In 122 patients, at least one ADE (95%) was observed. Only 39 hospitalizations were believed not to have an ADE (15%). No ADE was captured by all data sources. The patient record captured 550, the nursing record 569, the laboratory tests 387, the questionnaire 63, and the event monitoring during grand rounds 141 ADEs. Only the nursing record and the laboratory tests had a significantly different probability of observing indicative ADEs. Conclusion: For all AEs reported in the data sources, physicians and nurses were the best source for ADEs. Data sources differed in identifying indicative ADEs and were influenced by specific patient parameter

Comparative evaluation of three clinical decision support systems: prospective screening for medication errors in 100 medical inpatients

Purpose: Clinical decision support systems (CDSS) are promoted as powerful screening tools to improve pharmacotherapy. The aim of our study was to evaluate the potential contribution of CDSS to patient management in clinical practice. Methods: We prospectively analyzed the pharmacotherapy of 100 medical inpatients through the parallel use of three CDSS, namely, Pharmavista, DrugReax, and TheraOpt. After expert discussion that also considered all patient-specific clinical information, we selected apparently relevant alerts, issued suitable recommendations to physicians, and recorded subsequent prescription changes. Results: For 100 patients with a median of eight concomitant drugs, Pharmavista, DrugReax, and TheraOpt generated a total of 53, 362, and 328 interaction alerts, respectively. Among those we identified and forwarded 33 clinically relevant alerts to the attending physician, resulting in 19 prescription changes. Four adverse drug events were associated with interactions. The proportion of clinically relevant alerts among all alerts (positive predictive value) was 5.7, 8.0, and 7.6%, and the sensitivity to detect all 33 relevant alerts was 9.1, 87.9, and 75.8% for Pharmavista, DrugReax and TheraOpt, respectively. TheraOpt recommended 31 dose adjustments, of which we considered 11 to be relevant; three of these were followed by dose reductions. Conclusions: CDSS are valuable screening tools for medication errors, but only a small fraction of their alerts appear relevant in individual patients. In order to avoid overalerting CDSS should use patient-specific information and management-oriented classifications. Comprehensive information should be displayed on-demand, whereas a limited number of computer-triggered alerts that have management implications in the majority of affected patients should be based on locally customized and supported algorithm

Thrombozytenaggregationshemmer: Was sind die Risiken?

The most common risks related to platelet inhibitor therapy are bleeding, drug-drug interactions and therapeutic failure. The new substances prasugrel and ticagrelor are more potent platelet inhibitiors than clopidogrel. This reduces the incidence of ischemic events, but also potentially increases the bleeding risk. Clopidogrel therapy has up to 20% non-response rates, which can partially be explained by genetic polymorphisms and drug-drug interactions. Currently no evidence exists that ticagrelor or prasugrel efficacy is affected by genetic polymorphisms. The therapy in patients at risk still has to be carefully adapted to minimize adverse events. Patients older than 75 years and/or weighing less than 60 kg should receive a reduced dose of prasugrel. The combination of ticagrelor with strong cytochrome-P450-3A4 inhibitors is contraindicated

Risks of inflammatory bowel disease treatment with glucocorticosteroids and aminosalicylates

BACKGROUND: Glucocorticosteroids and aminosalicylates, mainly mesalazine (5-ASA), are both standard therapeutics in the treatment of inflammatory bowel disease (IBD) patients. The glucocorticosteroids are highly effective in inducing remission in both ulcerative colitis and Crohn's disease, but their use is limited by the high incidence and the potentially serious nature of adverse events. In an attempt to limit systemic side effects, rapidly metabolized corticosteroids such as budesonide have been introduced. The safety profile of aminosalicylates differs between the formulations. METHODS: We summarize the potential risks associated with glucocorticosteroid and aminosalicylate therapy in IBDs. RESULTS: The numerous adverse events of glucocorticosteroids, particularly at high doses and prolonged treatment, include opportunistic infections, diabetes mellitus, hypertension, ocular effects (glaucoma and cataracts), psychiatric complications, hypothalamic-pituitary-adrenal axis suppression and increased fracture risk. Partially, these systemic adverse events occur with budesonide, which only has a low systemic exposure. The safety profile of 5-ASA is comparable to placebo and superior to the old aminosalicylate prodrug sulfasalazine, which had a significantly higher incidence of intolerance reactions including allergic rashes. Only in rare cases has nephrotoxicity such as interstitial nephritis been associated with 5-ASA. CONCLUSION: Considering the toxicity profile of conventional glucocorticosteroids, one primary goal of treatment in IBD should be corticosteroid-free remission. Therapy with budesonide may result in a better safety profile. 5-ASA treatment is usually well tolerated, but with regard to the rare nephrotoxic events, it is advisable to assess renal function before and during treatment with 5-ASA

Analysis of drug-drug interactions in Swiss claims data using tizanidine and ciprofloxacin as a prototypical contraindicated combination

BACKGROUND: Potential drug-drug interactions (pDDIs) are described in various case reports, but few studies have evaluated the impact of specific combinations on a population level. OBJECTIVE: To analyze the type and frequency of multiple contraindicated (X-pDDIs) and major interactions (D-pDDIs) and to subsequently assess the impact of the particular combination of tizanidine and ciprofloxacin on outpatient physician visits and hospitalizations. METHODS: Anonymized Swiss claims data from 524 797 patients in 2014-2015 were analyzed. First, frequencies of X- and D-pDDIs were calculated. Next, a retrospective cohort study was conducted among patients prescribed tizanidine and ciprofloxacin (exposed, n = 199) or tizanidine and other antibiotics (unexposed, n = 960). Hospitalizations and outpatient physician visits within 7, 14, and 30 days after initiation of antibiotic therapy were evaluated using multiple binary logistic regression and multiple linear regression. RESULTS: The relative frequencies of X- and D-pDDIs were 0.4% and 6.65%, respectively. In the cohort study, significant associations between exposure to tizanidine and ciprofloxacin and outpatient physician visits were identified for 14 and 30 days (odds ratio [OR] = 1.61 [95% CI = 1.17-2.24], P = 0.004, and OR = 1.59 [95% CI = 1.1-2.34], P = 0.016). A trend for increased risk of hospitalization was found for all evaluated time periods (OR = 1.68 [95% CI = 0.84-3.17], OR = 1.52 [95% CI = 0.63-3.33], and OR = 2.19 [95% CI = 0.88-5.02]). CONCLUSION and RELEVANCE: The interaction between tizanidine and ciprofloxacin is not only relevant for individual patients, but also at the population level. Further investigation of the impact of other clinically relevant DDIs is necessary to improve patient safety and reduce avoidable health care utilization

Pre-hospital medications in total hip arthroplasty: risk factors for poor outcomes

INTRODUCTION The influence of co-morbidities on complication rates and length of hospitalisation after surgery is well recognised. Clinical instruments predicting this influence, are of increasing interest. We sought to determine whether a count of a patient's preoperative pharmaceuticals would be associated to postoperative outcomes. MATERIAL AND METHODS In this retrospective, consecutive case series, 668 patients undergoing elective primary total hip arthroplasty (THA) were analysed. Age, gender, BMI, ASA-classification, nicotine or alcohol abuse, and the number and type of medications were documented. RESULTS Mean age was 63 years (18-94), 53% were females. A total of 60 (8.9%) local and 19 (2.8%) systemic complications occurred during hospital stay. A total of 11 (1.6%) patients died, while 49 (7.3%) local complications occurred during the first postoperative year. Length of hospital stay, blood transfusions, and morbidity were found to be significantly related to the quantity of medications (p<0.001). While the risk of an extended hospital stay (>7 days) increased by a factor of 1.15 (CI: 1.08-1.22) with each medication, the risk of experiencing a complication within the first postoperative year was 1.19 times (CI: 1.07-1.29) for each additional medication. Type of medication also influenced morbidity: the odds ratio was 1.89 (CI: 1.05-3.41) for platelet inhibiting agents and 4.07 (CI: 1.96-8.42) for oral anticoagulants in early morbidity, which increased to 6.05 (CI:2.92-12.53) in 1-year follow-up. CONCLUSIONS The investigation illustrated the significant influence of the number and/or type of medication on complications, morbidity and prolonged hospital stay. This predictive tool may be useful, for physicians and non-health professionals, in estimating particular outcomes after elective THA

Prediction of health care expenditure increase: how does pharmacotherapy contribute?

Background Rising health care costs are a major public health issue. Thus, accurately predicting future costs and understanding which factors contribute to increases in health care expenditures are important. The objective of this project was to predict patients healthcare costs development in the subsequent year and to identify factors contributing to this prediction, with a particular focus on the role of pharmacotherapy. Methods We used 2014–2015 Swiss health insurance claims data on 373′264 adult patients to classify individuals’ changes in health care costs. We performed extensive feature generation and developed predictive models using logistic regression, boosted decision trees and neural networks. Based on the decision tree model, we performed a detailed feature importance analysis and subgroup analysis, with an emphasis on drug classes. Results The boosted decision tree model achieved an overall accuracy of 67.6% and an area under the curve-score of 0.74; the neural network and logistic regression models performed 0.4 and 1.9% worse, respectively. Feature engineering played a key role in capturing temporal patterns in the data. The number of features was reduced from 747 to 36 with only a 0.5% loss in the accuracy. In addition to hospitalisation and outpatient physician visits, 6 drug classes and the mode of drug administration were among the most important features. Patient subgroups with a high probability of increase (up to 88%) and decrease (up to 92%) were identified. Conclusions Pharmacotherapy provides important information for predicting cost increases in the total population. Moreover, its relative importance increases in combination with other features, including health care utilisation

Performance of different data sources in identifying adverse drug events in hospitalized patients

For all AEs reported in the data sources, physicians and nurses were the best source for ADEs. Data sources differed in identifying indicative ADEs and were influenced by specific patient parameters

A Mobile App to Stabilize Daily Functional Activity of Breast Cancer Patients in Collaboration With the Physician: A Randomized Controlled Clinical Trial

BACKGROUND: The well-being of breast cancer patients and reporting of adverse events require close monitoring. Mobile apps allow continuous recording of disease- and medication-related symptoms in patients undergoing chemotherapy. OBJECTIVE: The aim of the study was to evaluate the effects of a mobile app on patient-reported daily functional activity in a supervised and unsupervised setting. METHODS: We conducted a randomized controlled study of 139 breast cancer patients undergoing chemotherapy. Patient status was self-measured using Eastern Cooperative Oncology Group scoring and Common Terminology Criteria for Adverse Events. Participants were randomly assigned to a control group, an unsupervised group that used a mobile app to record data, or a supervised group that used the app and reviewed data with a physician. Primary outcome variables were change in daily functional activity and symptoms over three outpatient visits. RESULTS: Functional activity scores declined in all groups from the first to second visit. However, from the second to third visit, only the supervised group improved, whereas the others continued to decline. Overall, the supervised group showed no significant difference from the first (median 90.85, IQR 30.67) to third visit (median 84.76, IQR 18.29, P=.72). Both app-using groups reported more distinct adverse events in the app than in the questionnaire (supervised: n=1033 vs n=656; unsupervised: n=852 vs n=823), although the unsupervised group reported more symptoms overall (n=4808) in the app than the supervised group (n=4463). CONCLUSIONS: The mobile app was associated with stabilized daily functional activity when used under collaborative review. App-using participants could more frequently report adverse events, and those under supervision made fewer and more precise entries than unsupervised participants. Our findings suggest that patient well-being and awareness of chemotherapy adverse effects can be improved by using a mobile app in collaboration with the treating physician. CLINICALTRIAL: ClinicalTrials.gov NCT02004496; https://clinicaltrials.gov/ct2/show/NCT02004496 (Archived by WebCite at http://www.webcitation.org/6k68FZHo2

Analysis of Drug-Drug Interactions in Swiss Claims Data Using Tizanidine and Ciprofloxacin as a Prototypical Contraindicated Combination

Background: Potential drug-drug interactions (pDDIs) are described in various case reports, but few studies have evaluated the impact of specific combinations on a population level. Objective: To analyze the type and frequency of multiple contraindicated (X-pDDIs) and major interactions (D-pDDIs) and to subsequently assess the impact of the particular combination of tizanidine and ciprofloxacin on outpatient physician visits and hospitalizations. Methods: Anonymized Swiss claims data from 524 797 patients in 2014-2015 were analyzed. First, frequencies of X- and D-pDDIs were calculated. Next, a retrospective cohort study was conducted among patients prescribed tizanidine and ciprofloxacin (exposed, n = 199) or tizanidine and other antibiotics (unexposed, n = 960). Hospitalizations and outpatient physician visits within 7, 14, and 30 days after initiation of antibiotic therapy were evaluated using multiple binary logistic regression and multiple linear regression. Results: The relative frequencies of X- and D-pDDIs were 0.4% and 6.65%, respectively. In the cohort study, significant associations between exposure to tizanidine and ciprofloxacin and outpatient physician visits were identified for 14 and 30 days (odds ratio [OR] = 1.61 [95% CI = 1.17-2.24], P = 0.004, and OR = 1.59 [95% CI = 1.1-2.34], P = 0.016). A trend for increased risk of hospitalization was found for all evaluated time periods (OR = 1.68 [95% CI = 0.84-3.17], OR = 1.52 [95% CI = 0.63-3.33], and OR = 2.19 [95% CI = 0.88-5.02]). Conclusion and Relevance: The interaction between tizanidine and ciprofloxacin is not only relevant for individual patients, but also at the population level. Further investigation of the impact of other clinically relevant DDIs is necessary to improve patient safety and reduce avoidable health care utilization.ISSN:1060-0280ISSN:1542-627