STUDY OBJECTIVE: To identify predictors of hospital admissions associated with adverse drug events (ADEs) and to determine the preventability of ADEs in patients admitted to two hospitals. DESIGN: Prospective observational study. SETTING: Medical admission units at two British National Health Service hospitals in the United Kingdom. PATIENTS: 3904 adults age 16 years or older who were admitted to the two hospitals between June 2006 and November 2007. MEASUREMENTS AND MAIN RESULTS: Clinical pharmacists identified hospital admissions associated with drug-related problems by using medical record review, supplemented by patient interview for those identified as having an ADE. The contribution of ADEs to hospital admission and the causality, severity, and preventability of the events were independently assessed by a multidisciplinary clinical team. Multivariate logistic regression was used to identify predictors of hospital admissions associated with ADEs, and a maximum-likelihood multinomial model was used to examine predictors of the preventability of ADEs. Of the 3904 patients included in the analysis, 439 (11.2%) were judged by the review panel to have experienced ADEs. Of these, 209 patients (47.6%) experienced preventable ADEs. Four independent variables were found to have significant relationships with ADE admissions and preventability of ADEs: patient age, length of time since starting new drug, total number of prescription drugs, and hospital site. Drug classes most commonly associated with preventable ADEs were antiplatelet drugs, anticoagulants, diuretics (loop and thiazide diuretics), angiotensin-converting enzyme inhibitors, and antiepileptic drugs. CONCLUSION: Adverse drug events are an important cause of hospital admission. Better systems for health care practitioners to identify patients at high risk of preventable hospital admissions associated with ADEs (e.g., age > 65 years old, receiving more than five drugs, and starting new high-risk drugs) should be implemented in order to minimize the risks to patients and the burden on the health care system.
STUDY OBJECTIVE: To identify predictors of hospital admissions associated with adverse drug events (ADEs) and to determine the preventability of ADEs in patients admitted to two hospitals. DESIGN: Prospective observational study. SETTING: Medical admission units at two British National Health Service hospitals in the United Kingdom. PATIENTS: 3904 adults age 16 years or older who were admitted to the two hospitals between June 2006 and November 2007. MEASUREMENTS AND MAIN RESULTS: Clinical pharmacists identified hospital admissions associated with drug-related problems by using medical record review, supplemented by patient interview for those identified as having an ADE. The contribution of ADEs to hospital admission and the causality, severity, and preventability of the events were independently assessed by a multidisciplinary clinical team. Multivariate logistic regression was used to identify predictors of hospital admissions associated with ADEs, and a maximum-likelihood multinomial model was used to examine predictors of the preventability of ADEs. Of the 3904 patients included in the analysis, 439 (11.2%) were judged by the review panel to have experienced ADEs. Of these, 209 patients (47.6%) experienced preventable ADEs. Four independent variables were found to have significant relationships with ADE admissions and preventability of ADEs: patient age, length of time since starting new drug, total number of prescription drugs, and hospital site. Drug classes most commonly associated with preventable ADEs were antiplatelet drugs, anticoagulants, diuretics (loop and thiazide diuretics), angiotensin-converting enzyme inhibitors, and antiepileptic drugs. CONCLUSION: Adverse drug events are an important cause of hospital admission. Better systems for health care practitioners to identify patients at high risk of preventable hospital admissions associated with ADEs (e.g., age > 65 years old, receiving more than five drugs, and starting new high-risk drugs) should be implemented in order to minimize the risks to patients and the burden on the health care system.
Authors: Jacqueline M Bos; Patricia M L A van den Bemt; Peter A G M de Smet; Cornelis Kramers Journal: Br J Clin Pharmacol Date: 2017-01-12 Impact factor: 4.335
Authors: Ghadah H Alshehri; Darren M Ashcroft; Joanne Nguyen; Mark Hann; Richard Jones; Kristof Seaton; Graham Newton; Richard N Keers Journal: Drug Saf Date: 2021-07-05 Impact factor: 5.606