Parameswaran Nair, N and Chalmers, L and Bereznicki, BJ and Castelino, RL and Peterson, GM and Curtain, CM and Connolly, MJ and Bereznicki, LRE, Development of a Score to Predict Hospitalisation due to Adverse Drug Reactions in Older Patients, 2015 Joint APSA-ASCEPT Annual Conference, 29 November - 2 December, 2015, Hobart, Tasmania (2015) [Conference Extract]
Introduction: Adverse drug reactions (ADRs) are a significant cause of hospitalisation in elderly patients.
Aim: To develop a risk score to predict ADR-related hospitalisation in people aged ≥65 years.
Methods: We conducted a prospective cross-sectional study at the Royal Hobart Hospital, Tasmania over a 12-month period to identify the proportion of patients whose admission was caused by an ADR. Identification of ADRs was based on reviewing medical records and patient interview. A wide range of potential predictors of ADR were evaluated in 70 patients admitted due to ADRs that were deemed preventable and 698 controls. Variables included the number of regular medications, number of comorbid conditions, dementia, heart failure, liver failure, renal failure, recent hospital admission and use of potentially inappropriate medications defined by Beer’s criteria. The variables associated with ADRs (p<0.05) in the bivariate analyses were entered into a multivariate logistic regression model. Variables retained in the final model were used to compute the ADR risk score. A score of 1 was assigned to variables with an odds ratio (OR) between 1.00 and 1.99; and a score of 2, to those with an OR between 2.00 and 2.99. The ADR risk score was computed based on the sum of scores of individual variables. Further analyses were performed to determine the cut-off score, sensitivity, specificity and model performance.
Results: The variables that predicted admission due to an ADR included number of regular medications (≥8), number of comorbid conditions (>6), presence of dementia and hospital admission within the past month. An ADR score cut off of 3 had a sensitivity of 70% and a specificity of 59%. The predictive ability of the risk score was assessed from a calculation of the area under the receiver operator characteristic curve and found to be 0.69 (95% CI, 0.63-0.75), suggesting that the ability of the model to predict ADRs is better than chance alone.
Discussion: The ADR risk score developed, after further validation, may be useful in clinical practice as a tool to identify patients at risk of hospitalisation due to preventable ADRs, and to target a subgroup of elderly that could benefit from interventions aimed to reduce this risk.
|Item Type:||Conference Extract|
|Research Division:||Biomedical and Clinical Sciences|
|Research Group:||Pharmacology and pharmaceutical sciences|
|Research Field:||Clinical pharmacy and pharmacy practice|
|Objective Division:||Expanding Knowledge|
|Objective Group:||Expanding knowledge|
|Objective Field:||Expanding knowledge in the health sciences|
|UTAS Author:||Parameswaran Nair, N (Dr Nibu Parameswaran Nair)|
|UTAS Author:||Chalmers, L (Dr Leanne Chalmers)|
|UTAS Author:||Bereznicki, BJ (Dr Bonnie Bereznicki)|
|UTAS Author:||Castelino, RL (Dr Ronald Castelino)|
|UTAS Author:||Peterson, GM (Professor Gregory Peterson)|
|UTAS Author:||Curtain, CM (Mr Colin Curtain)|
|UTAS Author:||Connolly, MJ (Mr Michael Connolly)|
|UTAS Author:||Bereznicki, LRE (Professor Luke Bereznicki)|
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