Optimizing medication reviews through decision support: prescribing a better pill to swallow

Abstract

The expected growth of the elderly population in the coming decennia presents great challenges for public health. With increasing age comes a greater dependency on medicine, resulting in many elderly people using five or more medicines simultaneously. There is ample evidence that structured medication reviews could improve these polypharmacy patients’ medication, but that there are major barriers impeding their implementation in general practice. Clinical decision support systems have been shown to effectively improve prescribing processes in primary care, reinforcing the assumption that they could be successfully implemented for the conduct of structured medication reviews. In this dissertation, the conception and development of a decision support system to facilitate the conduct of structured medication reviews by physicians and pharmacists in primary care is described. The resulting system is validated in both a controlled environment and in practice, and is shown to significantly improve practitioners’ effectiveness and efficiency in optimizing medication. The research presented here extends the body of knowledge on the development and implementation of decision support systems in the domain of primary care. It demonstrates how mixed methods can be employed for the validation of such systems in controlled environments and in practice. It deepens our understanding of barriers currently impeding the utility of decision support systems in primary care, most notably those of semantic interoperability and safe application of association rule mining. It proves that the implementation of decision-supported structured medication reviews leads to improvements in polypharmacy patients’ medication, and can be of great societal benefit in terms of health benefit and cost reduction.