Abstract
Adverse drug reaction is a recognized hazard of the drug therapy. The practice in clinical pharmacy also ensures that ADRs are minimized by avoiding drugs with potential side effects in susceptible patients. This paper reviews the different methodologies for detection of adverse events and discusses their relative advantages and limitations. While manual chart review has been considered the ‘‘gold-standard’’ for identifying adverse events in many patient safety studies. Investigators are currently evaluating, several electronic methods that can detect adverse events using coded data, free-text clinical narratives, or a combination of techniques. Physicians being frontline caregivers, a study was conducted to determine the level of awareness of physicians about ADR reporting and the extent of their involvement in pharmacovigilance activities. Current quantitative methods are not applicable to Electronic Health Record (EHR)data so, new alogrithm was proposed a novel quantitative postmarketing surveillance algorithm, the Comparison of Laboratory Extreme Abnormality Ratio (CLEAR ), for detecting adverse drug reaction (ADR) signals from EHR data. In present the implementation of a prospective pharmacovigilance program based on automatic laboratory signals (ALSs) at a hospital. The use of the “trigger tool”, a relatively low cost and “low tech” modification of the automated technique. The adapted technique appears to increase the rate of ADE detection approximately 50-fold over traditional reporting methodologies. ADRs can be detected in the Nursing Home setting with a high degree of accuracy using a clinical event monitor that employs a set of signals derived by expert consensus.Frequency of adverse drug reactions (ADRs) identified through the use of automatic signals generated from laboratory data (ALS) in hospitalised patient.
