DEVELOPMENT OF A RISK MODEL FOR ADVERSE DRUG EVENTS IN THE ELDERLY

The aim of this study was to develop a predictive model for adverse dr ug events (ADEs) in elderly patients. Socio-demographic and medical da ta were collected from chart reviews, computerised information and a p atient interview, for a population of 929 elderly patients (aged great er than or equal to 65 years) whose admission to the Waveney/B raid Va lley Hospital in Northern Ireland was not scheduled. A further 204 pat ients formed a validation group. An ADE score was assigned to each pat ient using a modified Naranjo algorithm scoring system. The ADE scores ranged from 0 to 8. For the purposes of developing a risk model, scor es of 4 or more were considered to constitute a high risk of an ADE. L ogistic regression analysis was used to produce a risk model for ADEs in the elderly. Seven variables significantly influenced the risk of a n elderly person developing an ADE. Prescribed digoxin [odds ratio (OR ) = 1.99], antidepressants (OR = 5.79), and a number of disease states , i.e. gastrointestinal disorders (nausea, vomiting, diarrhoea) [OR = 2.16], chronic obstructive airways disease (OR = 2.41) and angina (OR = 0.17), significantly influenced ADE score. An abnormal potassium lev el (OR = 2.57) and patient belief that their medication was in some wa y responsible for their hospital admission (OR = 4.21) also significan tly influenced ADE score. Validation of the model revealed that it had a specificity of 69%, a sensitivity of 41%, with an overall accuracy of 63%. This model was therefore better at predicting elderly patients with ADE scores of 3 or less. Nonetheless, the variables highlighted are significant risk factors for ADEs in the elderly.