Using big data to strengthen the evidence about effects of prescribing and deprescribing of medications in older people with limited life- expectancy

Generally, nursing home (NH) residents use many medications.
Medications are beneficial and needed to treat symptoms and
diseases, but some medications have questionable benefits at the end of life. These medications with questionable benefits are suitable for deprescribing. Deprescribing means stopping or tapering a medication.
Up to now, we do not know the effects of changes in medication use (e.g. deprescribing medications with questionable benefits and initiating beneficial medications) at the end of life. In this study, we will evaluate these effects on the quality of life of NH residents with limited life-expectancy, as well as on their susceptibility to disease and risk of dying, using innovative data techniques.
We will use data on quality of life and physical and psychosocial health of NH residents with limited life-expectancy collected in an ongoing data implementation project (BelRAI 2.0). These data are linked to administrative databases (“Big Data”) including reimbursed treatment and medication data of the whole Belgian population. Using these data we can approximate an RCT and measure effects of changes in medication use on quality of life, susceptibility to disease and mortality by comparing people for whom use of a specific medication has changed (exposure group) to people for whom use of this medication has not changed (control group), without putting them at actual risks of e.g. dying sooner by actually stopping a medication in real-life.