Methods for evaluating the benefit and harms of deprescribing in observational research using routinely collected data

Deprescribing is defined as “the planned and supervised process of dose reduction or stopping of medication that might be causing harm, or no longer be of benefit”. Barriers to deprescribing include healthcare professional fear and lack of guidance. These may stem from limited available evidence on benefits and harms of deprescribing medications commonly used among older persons. Advances in pharmacoepidemiology and causal inference methods to evaluate comparative effectiveness and safety of prescribing medications have yet to be considered for deprescribing medication. This paper discusses select methods and how they can be applied to deprescribing research, using case studies of benzodiazepines and low-dose acetylsalicylic acid (aspirin). Target trial emulation involves the explicit application of design principles from randomised controlled trials to observational studies. Several design aspects, including defining eligibility criteria and time zero, require additional considerations for deprescribing studies. The active comparator new user design also presents challenges, including selection of an appropriate comparator. This paper discusses these aspects, and others, in relation to deprescribing studies. Furthermore, methods proposed to control for confounding, in particular, the prior event rate ratio and propensity scores, are discussed. Introduction of billing codes or mechanisms for accurately determining when deprescribing has occurred would enhance the ability to conduct research using routinely collected data. Although the approaches discussed in this paper may strengthen observational studies of deprescribing, their use may be best suited to certain scenarios or research questions, where randomised controlled trials may be less feasible.