Computer-generated STOPP/START recommendations for hospitalised older adults: evaluation of the relationship between clinical relevance and rate of implementation in the SENATOR trial

Abstract

a large proportion (61%) of the computer-generated STOPP/START recommendations provided were of potential 'adverse significance', of 'no clinical relevance' or of 'possibly low relevance'. The adjudicated clinical relevance of computer-generated medication recommendations significantly affects their implementation. Meticulous software refinement is required for future interventions of this type to increase the proportion of recommendations that are of high clinical relevance. This should facilitate their implementation, resulting in prescribing optimisation and improved clinical outcomes for multimorbid older adults.