Potentially inappropriate prescribing among people with dementia in primary care: a retrospective cross-sectional study using the Enhanced Prescribing Database

Background: Little is known about prescribing appropriateness for community-dwelling people with dementia (PWD).
Objective To estimate potentially inappropriate prescribing (PIP) prevalence among PWD in primary care in Northern Ireland, and to investigate associations between PIP and polypharmacy, age and gender.

Methods: A retrospective cross-sectional study was conducted, using data from the Enhanced Prescribing Database. Patients were eligible if a medicine indicated for dementia management was dispensed to them during 01/01/2013 – 31/12/2013. Polypharmacy was indicated by use of ≥4 repeat medications from different drug groups. A subset of the Screening Tool of Older Persons Potentially Inappropriate Prescriptions (STOPP) criteria, comprising 36 indicators, was applied to the dataset. Overall prevalence of PIP and the prevalence per each STOPP criterion was calculated as a proportion of all eligible persons in the dataset. Logistic regression was used to investigate associations between PIP, polypharmacy, age and gender.

Results: The study population comprised 6826 patients. Polypharmacy was observed in 81.5% (n=5564) of patients. PIP prevalence during the study period was 64.4% (95% CI 63.2 – 65.5; n=4393). The most common instance of PIP was the use of anticholinergic/antimuscarinic medications (n=1718; 25.2%; 95% CI 24.2 – 26.2). In multivariable analyses, both polypharmacy and gender (being female) were associated with PIP, with odds ratios of 7.6 (95% CI 6.6 – 8.7) and 1.3 (95% CI 1.2 – 1.4) respectively. No association was observed between PIP and age, after adjustments for gender and polypharmacy.

Conclusion: This study identified a high prevalence of PIP in community-dwelling PWD. Future interventions may need to focus on certain therapeutic categories and polypharmacy.

Managed Acceleration for In-Memory Database Analytic Workloads

In-Memory Databases (IMDBs), such as SAP HANA, enable new levels of database performance by removing the disk bottleneck and by compressing data in memory. The consequence of this improved performance means that reports and analytic queries can now be processed on demand. Therefore, the goal is now to provide near real-time responses to compute and data intensive analytic queries. To facilitate this, much work has investigated the use of acceleration technologies within the database context. While current research into the application of these technologies has yielded positive results, they have tended to focus on single database tasks or on isolated single user requests. This paper uses SHEPARD, a framework for managing accelerated tasks across shared heterogeneous resources, to introduce acceleration into an IMDB. Results show how, using SHEPARD, multiple simultaneous user queries all receive speed-up by using a shared pool of accelerators. Results also show that offloading analytic tasks onto accelerators can have indirect benefits for other database workloads by reducing contention for CPU resources.