View clinical trials related to Adverse Drug Events.
Filter by:We tested two interventions to improve the accuracy of medication histories obtained at hospital admission. The interventions target elderly and chronically ill patients prone to erroneous medication histories and resultant medication errors. For targeted patients, we tested the effect of using pharmacists and pharmacy technicians to obtain an initial medication history. This was studied using a randomized controlled trial of usual care (which involves nurses and physicians) vs usual care + pharmacists vs usual care + pharmacy technicians to obtain an admission medication history. The overarching hypothesis was that by leveraging pharmacists and pharmacy technicians we can minimize admission medication history errors and related downstream events.
To highlight the incidence of adverse reactions of Qingkailing Injection.
Adverse drug events (ADEs) are the most clinically significant and costly medication-related problems in nursing homes (NH) and are associated with an estimated 93,000 deaths a year and as much as $4 billion of excess healthcare expenditures. Current ADE detection and management strategies that rely on pharmacist retrospective chart reviews (i.e., usual care) are inadequate. Active medication monitoring systems are recommended by many safety organizations as an alternative to detect and manage ADEs. These systems have been shown to be less expensive, faster, and identify ADEs not normally detected by clinicians in the hospital setting. The investigators developed and pilot-tested an active medication monitoring system for use in a single NH, where it was shown to detect ADEs with a high degree of accuracy and at a rate of nearly 2.5 times that of usual care. The long-term objective of our proposed research is to improve patient safety with respect to medications in NHs. The short-term objectives or specific aims of our proposed research are to determine if NH patients managed by physicians who receive active medication monitoring alerts have more ADEs detected, have a faster ADE management response time, and can result in more cost-savings from a societal perspective compared to usual care.
Patients often have problems after they leave the hospital, in part because errors are made in the medications they are prescribed. The goal of this project is to develop a more accurate and safe medication prescription process when patients enter and leave the hospital and implement this process at six U.S. hospitals. The investigators will measure the success of the project and develop lessons learned so this process can be applied to other hospitals.
The purpose of this study is to determine if a physician's use of electronic medication reconciliation software when writing a patient's discharge prescription will prevent adverse drug events and readmissions to the hospital. This electronic medication software will provide the physician with the most up-to-date list of medications the patient was taking before being admitted to the hospital, through a real-time link to the provincial drug insurance agency's administrative databases. It will also provide the list of medications the patient has taken while admitted to the hospital. With these two pieces of information, the physician will write the discharge prescription using the medication management software, print the discharge prescription for the patient, and the software will fax a copy of any prescriptions that should be stopped to the patient's community pharmacist.
This initiative aims to decrease the risk of medication errors at the hospital-community interface as well as health system utilization following hospital discharge by implementing a pharmacist-led medication reconciliation in the patients' home within 72 hours of hospital discharge.
The study will measure the effect of basic clinical decision support on medical errors and adverse drug events in the ambulatory setting.
The purpose of this study is to determine if an electronic alerting technology improves time to intervention for possible ADEs, identify what factors affect adoption of ADE alerts, and whether there is a cost benefit associated with the alerting technology.
Adverse drug events (ADEs) after hospital discharge are common. The purpose of this research study is see if we can design an electronic tool given to your primary care provider (PCP) that will reduce adverse drug events, hospital readmissions, and emergency department visits after you are discharged from the hospital.
Medications are the single most common form of treatment in the long-term care setting, and often represent the most efficacious (and cost-effective) therapeutic modality used in this clinical setting. However, the residents of nursing homes are at increased risk for experiencing adverse drug events. This risk is increased by the physiologic decline and pharmacologic changes that occur with aging, and also by the special clinical and social circumstances that characterize institutional long-term care. In a study funded by the National Institute on Aging (AG 14472), we have previously determined that adverse drug events are common and often preventable in the nursing home setting and that the more serious the adverse drug event, the more likely it is to be preventable. This study will test whether a computer-based clinical decision support system can lower the rate of adverse drug events (ADEs) and potential ADEs in the long-term care setting. The study design is a randomized trial based in the resident care units of two large long-term care facilities. Within each facility, half of the resident care units will be randomized to an intervention arm receiving the computer-based clinical decision support system which will display warnings, messages, and prompts based on resident and drug use characteristics; with over-rides by the prescriber required for some warnings. Rates of ADEs and potential ADEs will be tracked by the study's on-site clinical pharmacists prior to and during the intervention period. Rates will be compared between units receiving and not receiving the computer¬based clinical decision support system and to baseline, pre-intervention rates in the same units. We will track all project costs directly related to the development and installation of the computer-based clinical decision support system. We will also develop and test the sensitivity and specificity of a computerized adverse drug event monitor and assess the validity of a nursing home resident risk model developed in our prior study of adverse drug events in the nursing home setting.