Effect of Collaborative Review of Electronic Patient-Reported Outcomes for Shared Reporting in Breast Cancer Patients: Descriptive Comparative Study.

BACKGROUND: Digital monitoring of treatment-related symptoms and self-reported patient outcomes is important for the quality of care among cancer patients. As mobile devices are ubiquitous nowadays, the collection of electronic patient-reported outcomes (ePROs) is gaining momentum. So far, data are lacking on the modalities that contribute to the quantity and quality of ePROs. OBJECTIVE: The objective of our study was to compare the utilization of two versions of a subsequently employed mobile app for electronic monitoring of PROs and to test our hypothesis that a shared review of symptoms in patient-physician collaboration has an impact on the number of data entries. METHODS: The Consilium Care app engages cancer patients to standardize reporting of well-being and treatment-related symptoms in outpatient settings. For descriptive comparison of the utilization of two slightly different app versions, data were obtained from an early breast cancer trial (version 1 of the app, n=86) and an ongoing study including patients with advanced disease (version 2 of the app, n=106). In both app versions, patients and doctors were allowed to share the information from data entries during consultations. Version 2 of the app, however, randomly selected symptoms that required a detailed and shared regular patient-doctor review in order to focus on the collection and appropriate interpretation regarding awareness and guidance for severity grading. The numbers and types of symptom entries, satisfaction with both app versions, and patients' perceived effects during consultations were included for analysis. RESULTS: Symptom severity grading was performed according to the Common Terminology Criteria for Adverse Events (CTCAE) using a horizontal slider and was indicated in descriptive terminology in both apps, while a graphical display facilitated the illustration of symptom history charts. In total, 192 patients electronically reported 11,437 data entries on well-being and 33,380 data entries on individual symptoms. Overall, 628 (of 872 intended) requested patient-doctor symptom reviews were performed in version 2 of the app. Both the amount of data entries per patient and day for well-being (version 1 vs version 2: 0.3 vs 1.0; P<.001) and symptoms (version 1 vs version 2: 1.3 vs 1.9; P=.04) appeared significantly increased in version 2 of the app. Overall satisfaction with both app versions was high, although version 2 of the app was perceived to be more helpful in general. CONCLUSIONS: Version 2 of the app showed much better results than version 1 of the app. A request for collaborative patient-doctor symptom review is likely to affect the number of digital symptom data entries. This app shows high potential to improve the patient-doctor experience. TRIAL REGISTRATION: ClinicalTrials.gov NCT02004496; https://clinicaltrials.gov/ct2/show/NCT02004496 and ClinicalTrials.gov NCT03578731; https://clinicaltrials.gov/ct2/show/NCT03578731.

Medication as a risk factor for hospitalization due to heart failure and shock: a series of case-crossover studies in Swiss claims data.

PURPOSE: Heart failure is among the leading causes for hospitalization in Europe. In this study, we evaluate potential precipitating factors for hospitalization for heart failure and shock. METHODS: Using Swiss claims data (2014-2015), we evaluated the association between hospitalization for heart failure and shock, and prescription of oral potassium supplements, non-steroidal anti-inflammatory drugs (NSAIDs), and amoxicillin/clavulanic acid. We conducted case-crossover analyses, where exposure was compared for the hazard period and the primary control period (e.g., 1-30 days before hospitalization vs. 31-60 days, respectively). Conditional logistic regression was applied and subsequently adjusted for addressing potential confounding by disease progression. Sensitivity analyses were conducted and stratification for co-medication was performed. RESULTS: We identified 2185 patients hospitalized with heart failure or shock. Prescription of potassium supplements, NSAIDs, and amoxicillin/clavulanic acid was significantly associated with an increased risk for hospitalization for heart failure and shock with crude odds ratios (OR) of 2.04 for potassium (95% CI 1.24-3.36, p = 0.005, 30 days), OR 1.8 for NSAIDs (95% CI 1.39-2.33, p < 0.0001, 30 days), and OR 3.25 for amoxicillin/clavulanic acid (95% CI 2.06-5.14, p < 0.0001, 15 days), respectively. Adjustment attenuated odds ratios, while the significant positive association remained (potassium OR 1.70 (95% CI 1.01-2.86, p = 0.046), NSAIDs OR 1.50 (95% CI 1.14-1.97, p = 0.003), and amoxicillin/clavulanic acid OR 2.26 (95% CI 1.41-3.62, p = 0.001). CONCLUSION: Prescription of potassium supplements, NSAIDs, and amoxicillin/clavulanic acid is associated with increased risk for hospitalization. Underlying conditions such as pain, electrolyte imbalances, and infections are likely contributing risk factors. Physicians may use this knowledge to better identify patients at risk and adapt patient management.

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.

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.

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).

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.

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.

[Thrombocyte aggregation inhibitors: what are the risks?]. / 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.

Les événements hémorragiques, les interactions médicamenteuses et l'échec de thérapie constituent les risques majeurs des traitements à base d'antiagrégants plaquettaires. Les substances nouvelles, prasugrel et ticagrelor, présentent un effet anitagrégant plus important et diminuent les épisodes ischémiques d'une manière plus efficacement que le clopidogrel. Cependent la possibilité existe d'une augmentation d'épisodes de saignement. Le risque de résistance à la thérapie atteint jusqu'à 20% pour les patients traités à base de clopidogrel, entre autre en raison de polymorphismes génétiques. Il n'existe pas d'evidence pour un mécanisme pareil pour le prasugrel et le ticagrelor. Dans certaines situations de risque par contre, une adaption du dosage est conseillée pour minimiser les effets secondaires négatifs: Chez les patients de plus de 75 ans, et/ou d'un poids corporel de moins de 60 kg, une réduction du dosage de prasugrel est conseillée en raison d'un risque élevé d'hémorragie. Il est contrindiqué d'utiliser ticagrelor en combinaison avec des inhibiteurs puissants du cytochrome-P450­3A4.

Validation of a transparent decision model to rate drug interactions.

BACKGROUND: Multiple databases provide ratings of drug-drug interactions. The ratings are often based on different criteria and lack background information on the decision making process. User acceptance of rating systems could be improved by providing a transparent decision path for each category. METHODS: We rated 200 randomly selected potential drug-drug interactions by a transparent decision model developed by our team. The cases were generated from ward round observations and physicians' queries from an outpatient setting. We compared our ratings to those assigned by a senior clinical pharmacologist and by a standard interaction database, and thus validated the model. RESULTS: The decision model rated consistently with the standard database and the pharmacologist in 94 and 156 cases, respectively. In two cases the model decision required correction. Following removal of systematic model construction differences, the DM was fully consistent with other rating systems. CONCLUSION: The decision model reproducibly rates interactions and elucidates systematic differences. We propose to supply validated decision paths alongside the interaction rating to improve comprehensibility and to enable physicians to interpret the ratings in a clinical context.

Drug-related problems and factors influencing acceptance of clinical pharmacologists` alerts in a large cohort of neurology inpatients.

QUESTIONS UNDER STUDY/PRINCIPLES: Data regarding the prevalence and types of drug-related problems (DRPs) among neurology inpatients is sparse. The objective of this study was to characterise the types of DRPs seen among neurology inpatients and furthermore to study factors affecting the acceptance of clinical pharmacologists' and pharmacists' recommendations for improving drug safety. METHODS: 1,263 consecutive inpatient cases in a Swiss university hospital neurology unit were assessed for the presence of DRPs over 12 months. Treating neurologists' acceptance of the resulting recommendations was also recorded. Primary outcome measures were types of DRP, recommendations made by clinical pharmacologists and number of recommendations accepted. Factors potentially associated with acceptance were studied using univariate and multivariate generalised estimating equation modelling. RESULTS: Twenty-nine percent of cases demonstrated one or more DRPs. DRPs were the cause of admission in 10 cases (0.8%). In total 494 DRPs were identified and 467 recommendations given, of which 62% were accepted. Factors associated with an increased likelihood of acceptance were prescriptions involving regularly administered drugs (odds ratio [OR] 2.57 95% confidence interval [CI] 1.73-3.80), adverse drug events (OR 2.5; 95% CI 1.29-5.06), known drug side-effect (OR 1.85; 95% CI 1.06-3.22), high-risk drug-drug interactions (OR 3.22; 95% CI 1.07-9.69) and interventions involving changing a drug (OR 2.71; 95% CI 1.17-6.25). CONCLUSION: Clinical pharmacologists and pharmacists can play an important role in identifying DRPs among neurology inpatients. Their recommendations for optimising medication-safety are most likely to be accepted for regular prescriptions, prescriptions associated with an adverse drug event and high-risk drug combinations.

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 algorithms.

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 parameters.

Phynx: an open source software solution supporting data management and web-based patient-level data review for drug safety studies in the general practice research database and other health care databases.

PURPOSE: To develop a software solution that supports management and clinical review of patient data from electronic medical records databases or claims databases for pharmacoepidemiological drug safety studies. METHODS: We used open source software to build a data management system and an internet application with a Flex client on a Java application server with a MySQL database backend. The application is hosted on Amazon Elastic Compute Cloud. This solution named Phynx supports data management, Web-based display of electronic patient information, and interactive review of patient-level information in the individual clinical context. This system was applied to a dataset from the UK General Practice Research Database (GPRD). RESULTS: Our solution can be setup and customized with limited programming resources, and there is almost no extra cost for software. Access times are short, the displayed information is structured in chronological order and visually attractive, and selected information such as drug exposure can be blinded. External experts can review patient profiles and save evaluations and comments via a common Web browser. CONCLUSIONS: Phynx provides a flexible and economical solution for patient-level review of electronic medical information from databases considering the individual clinical context. It can therefore make an important contribution to an efficient validation of outcome assessment in drug safety database studies.