How to measure success?
Outcome selection for an interventional study will inevitably stem from
the intervention scope and target; in considering what would be a
success, it is important to reflect on the goals of the intervention,
and the audience for whom evidence is being produced. Particularly for
deprescribing trials, no change in clinical or patient-reported outcomes
may be considered a success, assuming success is judged as a reduction
in the number of medications. This should be decided a priori, with the
study design and analysis planned appropriately to evaluate
non-inferiority in clinical outcomes. In contrast for medicines
optimisation trials, a reduction in medicines may not always occur (or
be appropriate), and therefore some benefit in other outcomes may be the
goal and basis for designing and powering the study. Process outcomes
are important regardless of intervention focus, to assess whether the
behavioural strategies have been delivered. For deprescribing, process
outcomes could also include the number of participants who had a
medicine (or medicines) deprescribed or, similar to above, the mean
reduction in the number of medicines. However, using similar measures in
a medicines optimisation trial may not fully capture the degree to which
actions have been taken, and a small or negligible reduction in the mean
number of medicines could be underpinned by a large, balanced number of
medicines stopped and started.(7)
Outcomes should be selected with regard to what is meaningful for
stakeholders, including patients, healthcare professionals, and
decision-makers who may wish to implement the intervention being
assessed.(8) Core outcome sets can be drawn on as a means of enhancing
consistency and cumulative evidence across trials.(9) Arguably these
should be tied to trials with the same intervention scope and targets
(i.e. core outcomes for medicines optimisation interventional studies
may not all be relevant or useful for a deprescribing interventional
study of a single medication class).
Focusing on single medications may facilitate selection of outcomes that
are highly specific to that context (and potentially more meaningful to
patients), both for clinical and patient-reported outcomes e.g. sleep
quality as an outcome if deprescribing hypnotic agents, cognition for
anticholinergic agents. It may be difficult to assess success using
measures that reflect general medicines optimisation, particularly where
such generic or global health measures may not be sensitive to changes
in medications.(8) In such cases, outcomes often include measures of
prescribing appropriateness, adverse drug reactions, and
medicines-related hospitalisations, where the attributable risk due to
inappropriate prescribing, and preventability via medications
optimisation, may be low.
Costs and cost-effectiveness are important for decision-makers. For
interventions targeting many medications, estimating the indirect costs
saved through averting adverse outcomes is challenging when these events
are likely rare, diverse, and potentially difficult to measure. Although
costs relating to occurrence of a generic adverse drug reaction or
medicines-related hospitalisation could be estimated, these may have
limited acceptability among decision-makers, and add significant
uncertainty to the cost-effectiveness estimate. In contrast, for single
medication interventions, evidence on the known risks of continued
prescribing can be integrated with the effectiveness of the intervention
in reducing such prescribing to estimate the incremental costs and
benefits of implementing the intervention, and can be extrapolated over
a timeframe beyond the trial duration.(10)