Medication optimisation in hospitalised older people with polypharmacy and multimorbidity

Abstract

The prevalence of multimorbidity and polypharmacy is increasing in the ageing population, and both are important risk factors for drug-related harm, such as drug-related hospital admissions. Previous studies have reported that 10%–30% of all hospital admissions in older people are drug-related, half of which are potentially preventable.

Several tools, such as the Screening Tool of Older Person’s Prescriptions (STOPP) and the Screening Tool to Alert to the Right Treatment (START) criteria, have been developed to detect potentially inappropriate prescribing in multimorbid older people to improve medication appropriateness and prevent adverse outcomes. To incorporate such tools into daily clinical practice, the application of software assistance has gained attention in facilitating medication optimisation. However, previous studies investigating pharmacotherapy optimisation interventions in older people reported inconsistent results on improved clinical outcomes.

In this thesis, we focus on strategies for medication optimisation in hospitalised, multimorbid older people with polypharmacy and evaluate the effectiveness of a software-assisted in-hospital medication review on clinical outcomes.

Key messages

- Current clinical practice guidelines (CPGs) include screening tools to identify patients at risk for drug-related harm. For future development of explicit drug optimisation tools, such as STOPP/START, the clarity on a language level can be improved to enhance clinical applicability.

- Screening tools recommended by CPGs have predictive value (~40%) to identify patients at risk for adverse drug reactions (ADRs) and for potentially inappropriate prescribing. However, when screening tools are integrated as clinical decision support in electronic health systems, their clinical applicability depends on the availability of structured patient information, the setting in which these tools will be used, and their intended end-users. (Chapter 2, 4.1)

- A structured in-hospital medication review, performed jointly by a physician and a pharmacist with the support of a clinical decision software system, reduced inappropriate prescribing without causing detriment to patient outcomes, however, it did not significantly affect drug-related hospital admissions. (Chapter 3)

- We found that medication errors identified at readmission were not addressed by the prior in-hospital medication review because either these medication errors occurred after the medication review (~50%), or no recommendation was given during the medication review (~25%), or the recommendation was not implemented (~25%). (Chapter 4.3)

Conclusion The interaction between attending physicians, patients and healthcare professionals with expertise in geriatric care remains essential in translating evidence-based signals for potentially inappropriate prescribing to the most appropriate pharmacotherapy at the individual patient level. Barriers to the non-implementation of proposed recommendations differed between prescribers and patients and varied per drug class. Future research should focus on optimising the medication review timing, setting and frequency and implementing of proposed medication recommendations across health care settings.

Overall, we learned that the association between a patient-specific medication review and the clinical outcome ‘drug-related hospital admission’ is difficult to establish with a randomised controlled trial because both the intervention and outcome are highly variable. To further explore the potential clinical benefits of medication optimisation interventions in older people, we recommend exploring research designs based on large, real-world data rather than randomised clinical trials.