Endpoints
This northern-Italian RCT investigated the effect of medication reviews and recommendations provided by three experts with different professional background on patient-relevant outcomes in older-aged general practice patients on polypharmacy. The study found a high prevalence of polypharmacy, PIMs and DDIs, as described in the publication of epidemiological baseline data [31]. The composite primary outcome of non-elective hospital admissions or death was experienced significantly more often in the IG in the unadjusted analysis; yet, as significance disappeared after adjustment, which was also noted for hospitalisations as single secondary endpoint, this phenomenon seems to be strongly related to the higher occurrence of hospital admissions in the IG within the pre-interventional period. Also, the frequency of pre-interventional falls and symptoms was significantly higher in the IG. Thus, patients of the IG seemed to be in less favourable physical preconditions than CG patients. This phenomenon could have been entailed by the cluster randomisation (e.g., GPs of the IG could have systematically recruited more clinically impaired patients); however, the cluster effects were considered in the outcome analysis and did not significantly influence the results.
Hospitalisation rates (as secondary endpoint) remained higher in the IG than in the CG at T2, yet, the difference between the study groups was reduced compared to baseline. For both groups, the descriptive within-group analysis showed an increase of hospitalisations up to T2, whereby the increase in the CG was more pronounced and nearly doubled (Supplementary Tab.III). Therefore, although the intervention was not able to actually reduce mortality and hospitalisation rates, it may cautiously be interpreted as having demonstrated a positive impact in terms of a slowed increase of hospitalisations in a frail older-aged population with natural tendency to deterioration of clinical and physiological functions.
No significant difference was detected regarding mortality as single endpoint and fractures. Both outcomes occurred tendentially but not significantly more often in the IG, probably because of the higher clinical impairment of IG patients at baseline.
The assessed patient-reported outcomes did not significantly differ between IG and CG either. In both treatment groups, quality of life and affective status showed a tendency to decrease over time, most probably due to the natural functional decline in older-aged patients. Interestingly, the cognitive function of the assessed participants remained stable throughout the observation period which concords to the fact that only few patients with diagnosticated dementia participated in the study [31] and severe cognitive impairment was an exclusion criterium.
A positive result was by contrast found regarding falls: although being more than twice as frequent in the IG at baseline, a significant risk reduction favouring the IG was observed at the end of the study. Therefore, the intervention seemed to have significantly reduced falls in the investigated older-aged population. On the other hand, as a rather small part of the medications rated as inappropriate was actually withdrawn (see below), the extent of the real impact of the intervention on the measured outcomes should not be overestimated. Yet, our results may suggest that even modest reductions of inappropriate medications are able to entail clinical benefits, and to do so without negative impact on measured patient-related outcomes. This was confirmed also by the European multicenter trial PRIMA-eDS [42] and points to safety of deprescribing [27, 43]. True improvements of patient-related outcomes, especially mortality and hospital admissions, may be difficult to be achieved in older-aged multimorbid populations with natural tendency to functional deterioration [22]; therefore, besides from real measurable improvements, also stabilisation of clinical outcomes could be considered a positive result. Moreover, the medical impact of reduced falls should not be underestimated.
Although it was significantly higher in the CG at baseline, the median number of drugs did not differ between the study groups at T2. In both groups, the number of drugs decreased over time while the median reduction was tendentially higher in the CG. Thus, in contrast to the findings of the PRIMA-eDS trial [42], the intervention in our study did not have a clear impact on the number of prescriptions. This is not surprising as discontinuation of inappropriate drugs was carried out only in 37% of concerned patients and only 16% of the drugs recommended to discontinue were definitively withdrawn by the GPs; a notable reduction of the overall number of drugs could therefore not be expected. On the other hand, physicians of the CG could have changed their prescribing behaviour as well due to the awareness of participating in a study aiming at reducing inappropriate polypharmacy (study effect); this might have contributed to the even higher reduction of drug prescriptions in the CG.
In the available literature, a persisting paucity is noted of studies investigating the reduction of polypharmacy in daily practice [11]; this applies especially to high-grade evidence and proven effects on patient-relevant outcomes. A British RCT with a comparable intervention in care homes largely confirmed our results: the study found a significant reduction in number of falls, but no change in number of drugs, hospitalisations, mortality, cognitive function and activities of daily living [44]. The PRIMA-eDS study found no conclusive evidence for the reduction of mortality, non-elective hospitalisations, falls, fractures or improvements in quality of life (SF-12 physical and mental component scores) while the number of drugs was significantly reduced without negative impact on patient outcomes [42].
Also other studies in the primary care setting aiming at decreasing inappropriate polypharmacy achieved significant reductions of drug numbers [45,46,47,48]. However, a recent update of a Cochrane review [23] found no clear evidence that the assessed interventions were able to reduce the number of inappropriate prescriptions, hospital admissions, medication-related problems, or to enhance quality of life [49]. These results confirmed those derived from a former systematic review and meta-analysis [50]. Positive impacts of deprescribing interventions on all-cause mortality were found for non-randomised studies [4], but convincing evidence from randomised trials is lacking [51].
Intervention
15.8% of all drug prescriptions in our sample were valued as inappropriate by at least two experts (median: one per patient). This number appears rather modest, however, more than three quarters of the patients were treated with at least one inappropriate drug and nearly one fifth received three or more inappropriate drugs. The EbM-expert valued the highest proportion of drugs as inappropriate (16.6%), while the internist who was the expert most closely related to real practice rated the lowest proportion of drugs as inappropriate (13.6%).
In relation to their prescribing frequency, the most concerned drug classes in our cohort were anxiolytics/hypnotics, alpha-blockers, antiarrhythmics, NSAIDs/COX-2-inhibitors, PPIs and antidepressants/antipsychotics. Among these, antidepressants/antipsychotics, PPIs and anxiolytics were the most difficult to discontinue whereas the largest potential of deprescribing was observed for Allopurinol and NSAIDs. As previous literature shows, NSAIDs belong to those drug classes causing the majority of drug-related hospital admissions [52]. Thus, a careful consideration of their risk and benefit may contribute to avoiding preventable hospitalisations. Yet, although NSAIDs were among the most successfully discontinued inappropriate medications in our sample, they were withdrawn in only 43% of those cases where discontinuation was recommended.
In total, 24.3% of the recommended drugs were stopped by the GPs. Of these, a third was restarted due to re-occurrence of conditions or symptoms; this concerned mainly antidepressants, PPIs, NSAIDs, benzodiazepines and beta-blockers. Thus, in total, effective withdrawal was obtained only for 16% of the recommended drugs. A narrative review found lower general proportions of patients who needed to restart discontinued drugs (2–18%) while the success rates of definitive discontinuation differed largely across drug classes (14–64% for PPIs, 25–85% for benzodiazepines) [28]. A non-controlled pre-post study involving community-dwelling older adults found that 82% of inappropriate drugs were withdrawn (benzodiazepines even almost 100%, PPIs 75%) and only 2% of the stopped drugs had to be re-administered. These numbers indicate a largely higher discontinuation rate than in our study, however, the study sample was small [53].
In general, the fact that many of the recommendations were not adopted by the GPs and only less than a fifth of the inappropriate medications was definitively discontinued make a conclusive statement regarding the effect of the intervention difficult. Other studies achieved higher acceptance of experts’ recommendations by the GPs (44–58%) [44, 48], however, also these numbers indicate that the implementation of such interventions meets significant barriers. This is a relevant result itself which poses the question why it is so difficult to discontinue drug therapies in patients with polypharmacy and which factors impede efficient deprescribing.
In our cohort, the most prevalent reason for recommending discontinuation by the experts was missing indication; on the other hand, most of those GPs who gave a justification for non-adherence to the experts’ recommendations reported that a specific indication was given. These contradicting points of view may have intrinsically lowered the potential for deprescribing; however, the high baseline prevalence of PIMs (46.3%) and major DDIs (66.1%) underpin the a priori-necessity of deprescribing. Besides from true missing indications or symptoms/conditions falsely interpreted by GPs as correct indications, also other scenarios could have played a role: e.g. if a GP was aware of a condition and had treated it correctly but not listed the respective diagnosis in the EHR [54]. This would represent rather a problem of thorough documentation which is however an important precondition for high-quality therapy, especially in case of changing physicians or care providers. In this way, although this was not an explicit trial objective, the study could have contributed to enhance physicians’ awareness towards consistent documentation.
Other frequent reasons for not discontinuing medications were prescriptions by specialists and patient’s refusal; these were identified also by previous studies as major barriers to deprescribing [28].
In general, the literature distinguishes three types of factors which hinder deprescribing. Physician-related barriers comprise lack of knowledge [55], low awareness regarding identification of inappropriate drugs, inertia (failure to act despite of awareness), or low perceived self-efficacy (e.g. GPs not ‘daring’ to stop a medication initiated by a specialist) [28]. System-related barriers are lack of resources and time, multiple care providers with poor collaboration among different care levels, lack of guidelines for older multimorbid patients, and missing financial incentives for GPs addressing polypharmacy [28, 56]. Although studies revealed willingness to deprescribing among patients [57, 58], also patient-related barriers were identified: convictions regarding necessity of drugs [28, 59], satisfaction with the current therapy [57], fears of health deterioration [28, 57, 58], free prescriptions, older age, and patients’ lower educational level [56].
A remarkable impact towards deprescribing was attributed to the GPs’ recommendation to stop a drug, the possibility of discussing doubts with the GP [28], a good patient-physician-relationship, and the feeling that deprescribing would be safe [57]. Moreover, multidisciplinary approaches [56], guidelines for deprescribing (e.g. a deprescribing algorithm for PPIs is available) [60], and appropriate information of patients regarding risk and benefit of stopping drugs [56] were mentioned as facilitators to deprescribing.
For improving the success of deprescribing initiatives in daily practice, these findings indicate the need of enhancing physicians’ awareness towards inappropriateness of drugs and deprescribing, of providing appropriate time and financial resources for enabling the physicians to conduct effective and satisfying deprescribing conversations with their polypharmacy patients, of strengthening the GP-patient-relationship and the physicians’ skills regarding shared decision-making, and of well-designed patient guidelines to enhance patient knowledge [58, 61]. In our study, although GPs received tailored supervision throughout the study period, patients were not directly approached e.g. by educational initiatives. Moreover, also GPs were not explicitly trained towards polypharmacy and deprescribing. Perhaps a more active inclusion of patients in the intervention and an additional pre-interventional training of the GPs could have entailed a more effective implementation.
Our results also support previous conclusions [7, 62] that prevention of polypharmacy may be more successful than an afterwards deprescribing of drugs which patients (and physicians) are used to. Thus, future interventions should additionally focus on new prescriptions. In daily practice, besides from medication reviews performed by physicians, pharmacists or multidisciplinary teams, also electronic tools providing decision support in real time may be useful (and even more practicable) for this purpose [42].
Strengths and limitations
A strength of the study is that we enrolled patients aged ≥75 years, as the older age groups are less studied up to now although being the most vulnerable cohort of patients [5].
A further strength is the multidisciplinary approach, i.e. the involvement of experts from three different fields of specialisation with the need of concordance of at least two experts. The experts’ recommendations were intended as an aid to the shared decision-making process between physicians and patients, not to replace clinical judgement and individual patient counselling.
Moreover, the close involvement of GPs and patients in the intervention can be considered a strength [28] as well as the integration of the intervention in daily practice; however, at the same time, this made its implementation challenging and probably met several barriers which we were not able to fully identify neither to confront. Deprescribing addressed only withdrawal of drugs; a more sensitive approach could be achieved by also recommending dose reduction, safer alternative drugs or starting appropriate drugs. However, the aim of this study was merely to assess the effect of drug discontinuation.
The calculated sample size was low as clustering had not been considered. This led to consequences for the investigation of the study hypotheses, as only falls were significantly reduced in the intervention group, and it cannot be fully excluded that the intervention could not have entailed a significant impact on the primary endpoint or on other secondary outcomes when using a cluster-considering sample size. However, despite of the failed achievement of statistical significance for most of the endpoints, conclusions can be drawn from the significant results (reduction of falls). Moreover, as mentioned above, several previous studies using comparable interventions found similar results in terms of missing impact on mortality and hospitalisations; thus, the inadequate sample size might probably have been not the only or not the primary cause for not achieving significance in the primary endpoint.
The documentation of the time of occurrence was complete only for mortality while for the other patient-related events (hospitalisations, falls, fractures) considerable documentation gaps emerged. Therefore, a use of time-to-event analyses was not feasible for these outcomes nor for the primary endpoint. By using binary outcomes the rates of occurrence are investigated, but not potential differences regarding the time of occurrence; this leads to an information loss which has to be considered another limitation of the study.
OTC-medications were not included in the analysis because the electronic data extraction was possible only for prescribed drugs which were the only drugs recorded in the EHRs. OTC-drugs only could have been collected by questioning the participating patients; however, older-aged patients not always remember all drugs they are taking and brown bag medication reviews with each patient were not feasible within the logistic constraints of the study and have also shown limitations of accuracy [63]. Thus, a reliable and complete determination of OTC-drugs was not possible in this study and was therefore a priori excluded.
However, as in Italy most continuously taken drugs are only available on prescription, the exclusion of OTC-drugs should not have entailed a substantial bias. We also excluded PRN-medications, thus, some drugs possibly interacting with diseases or other medications could have been missed as well.
We did not evaluate the specific causes for hospitalisations and mortality e.g. differentiation between ADE-related events or other causes. Quantifying the number of drug-related events could have provided a better description of the potential link between polypharmacy exposure and hospitalisations respectively mortality.
Inter-rater agreement between experts’ recommendations was relatively high (≥66%) and the same three drug classes were most frequently valued as inappropriate by all experts. However, these findings also indicate that experts’ appraisal and recommendations regarding drugs vary to some extent depending on the professional and clinical background.
We did not assess the GPs’ experience or satisfaction regarding the intervention. Yet, this could be an interesting subject for future studies to e.g. qualitatively investigate the GPs’ experiences about a similar intervention and thus to possibly improve its degree of implementation.
Blinding of study participants was not possible due to the nature of the intervention. Yet, allocation concealment was assured as baseline data were collected before randomisation.
Inhomogeneity of some baseline characteristics across the study groups was not avoidable due to the size of the study sample and because of heterogeneity among patients and practices. Randomisation at a patient level could probably help to achieve a better balance of baseline covariates between the study groups, nevertheless, cluster-randomisation in our study was necessary to avoid contamination effects.
Both the GP and the patient sample were consecutively recruited to reduce the risk of selection bias. Yet, we enrolled only community-living patients who visited the GP office. The GP sample was small and thus not fully representative. Generalisability is also limited by the fact that our findings derive from a specific Italian region and patterns of polypharmacy might differ in other countries, as well as in populations with different baseline characteristics (e.g. with high-grade cognitive impairment). However, as stated above, our results are confirmed by other studies with comparable interventions deriving from different European countries; thus, we postulate that our results and implications might be applicable also to other national circumstances.