Bastiaan Sallevelt

278 CHAPTER 4.1 Introduction Polypharmacy poses an increasing challenge in health care and is largely driven by the steadily growing multimorbid elderly population and prescribers’ adherence to single-disease oriented guidelines [1]. Polypharmacy is, as a negative by-product of the benefits of pharmacotherapy, associated with an increased risk of negative health outcomes, such as adverse drug events, falls, decline in cognitive function, hospitalisation and even death, especially in frailer older people [2]. Therefore, the potential benefits should outweigh the potential risks of pharmacotherapy for each patient, and this balance should be evaluated both on treatment initiation and regularly during long-term follow-up through medication review. Explicit screening tools, such as the Screening Tool of Older Persons’ Prescriptions (STOPP) and the Screening Tool to Alert to Right Treatment (START), have been developed to facilitate the detection of potentially inappropriate prescribing in the process of regular medication review in older people [3–6]. Research has shown that the use of STOPP/START criteria in patient care can lead to a reduction of polypharmacy, inappropriate prescribing and adverse drug reactions [5,6]. However, application of STOPP/START v2 – which comprises 114 criteria – is time-consuming, which hampers its use in everyday clinical practice [7]. Hence, STOPP/START criteria v2 were converted into software algorithms that can be implemented into a clinical decision support system (CDSS) to facilitate their application [8,9]. A recent systematic review concluded that the use of CDSS-generated signals is likely to reduce potentially inappropriate prescriptions in older patients. However, studies reported adherence values to these signals by clinicians ranging from 33%- 55% [10]. Too many irrelevant signals can result in alert fatigue and inappropriate alert overrides, impeding the effectiveness of CDSS in clinical practice [11,12]. The STOPP/START criteria are population-based recommendations to detect medication overuse, misuse (STOPP) and underuse (START) and require clinicians’ careful consideration concerning their applicability to individual patients. Investigating the relevance of CDSS-assisted detection of potential medication overuse, underuse and misuse by STOPP/START for individual patients in clinical practice is necessary to gain insight into the applicability of these population-based recommendations to individual patient care. This study aimed to determine the frequency of CDSS-generated STOPP/START signals and subsequent acceptance by a pharmacotherapy team for use in individual hospitalised older patients with polypharmacy and multimorbidity. In addition, measurable determinants that may be associated with acceptance were investigated.

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