AIMThe aim of the present study was to explore the impact of strategies to reduce polypharmacy on mortality, hospitalization and change in number of drugs. METHODSSystematic review and meta-analysis: a systematic literature search targeting patients ≥65 years with polypharmacy (≥4 drugs), focusing on patient-relevant outcome measures, was conducted. We included controlled studies aiming to reduce polypharmacy. Two reviewers independently assessed studies for eligibility, extracted data and evaluated study quality. RESULTSTwenty-five studies, including 10 980 participants, were included, comprising 21 randomized controlled trials and four nonrandomized controlled trials. The majority of the included studies aimed at improving quality or the appropriateness of prescribing by eliminating inappropriate and non-evidence-based drugs. These strategies to reduce polypharmacy had no effect on all-cause mortality (odds ratio 1.02; 95% confidence interval 0.84, 1.23). Only single studies found improvements, in terms of reducing the number of hospital admissions, in favour of the intervention group. At baseline, patients were taking, on average, 7.4 drugs in both the intervention and the control groups. At follow-up, the weighted mean number of drugs was reduced (À0.2) in the intervention group but increased (+0.2) in controls. CONCLUSIONSThere is no convincing evidence that the strategies assessed in the present review are effective in reducing polypharmacy or have an impact on clinically relevant endpoints. Interventions are complex; it is still unclear how best to organize and implement them to achieve a reduction in inappropriate polypharmacy. There is therefore a need to develop more effective strategies to reduce inappropriate polypharmacy and to test them in large, pragmatic randomized controlled trials on effectiveness and feasibility. British Journal of Clinical PharmacologyBr J Clin Pharmacol (2016) 82 532-548 532

BackgroundPolypharmacy is common in older people and associated with potential harms. The aim of this study was to analyse the characteristics of an older multimorbid population with polypharmacy and to identify factors contributing to excessive polypharmacy in these patients.MethodsThis cross-sectional analysis is based on the PRIMA-eDS trial, a large randomised controlled multicentre study of polypharmacy in primary care. Patients’ baseline data were used for analysis. A number of socioeconomic and medical data as well as SF-12-scores were entered into a generalized linear mixed model to identify variables associated with excessive polypharmacy (taking ≥10 substances daily).ResultsThree thousand nine hundred four participants were recruited. Risk factors significantly associated with excessive polypharmacy were frailty (OR 1.45; 95% CI 1.22–1.71), > 8 diagnoses (OR 2.64; 95% CI 2.24–3.11), BMI ≥30 (OR 1.18; 95% CI 1.02–1.38), a lower SF-12 physical health composite score (OR 1.47; 95% CI 1.26–1.72), and a lower SF-12 mental health composite score (OR 1.33; 95% CI 1.17–1.59) than the median of the study population (≤36.6 and ≤ 48.7, respectively). Age ≥ 85 years (OR 0.83; 95% CI 0.70–0.99) led to a significantly lower risk for excessive polypharmacy. No association with excessive polypharmacy could be found for female sex, low educational level, and smoking. Regarding the study centres, being recruited in the UK led to a significantly higher risk for excessive polypharmacy compared to being recruited in Germany 1/Rostock (OR 1.71; 95% CI 1.27–2.30). Being recruited in Germany 2/Witten led to a slightly significant lower risk for excessive polypharmacy compared to Germany 1/Rostock (OR 0.74; 95% CI 0.56–0.97).ConclusionsFrailty, multimorbidity, obesity, and decreased physical as well as mental health status are risk factors for excessive polypharmacy. Sex, educational level, and smoking apparently do not seem to be related to excessive polypharmacy. Physicians should especially pay attention to their frail, obese patients who have multiple diagnoses and a decreased health-related quality of life, to check carefully whether all the drugs prescribed are evidence-based, safe, and do not interact in an unfavourable way.Trial registrationThis trial has been registered with Current Controlled Trials Ltd. on 31 July 2014 (ISRCTN10137559).Electronic supplementary materialThe online version of this article (10.1186/s12875-018-0795-5) contains supplementary material, which is available to authorized users.

Aim. Testing the effectiveness of peer support additionally to a disease management programme (DMP) for type 2 diabetes patients. Methods. Unblinded cluster-randomised controlled trial (RCT) involving 49 general practices, province of Salzburg, Austria. All patients enrolled in the DMP were eligible, n = 337 participated (intervention: 148 in 19 clusters; control: 189 in 20 clusters). The peer support intervention ran over 24 months and consisted of peer supporter recruitment and training, and group meetings weekly for physical exercise and monthly for discussion of diabetes related topics. Results. At two-year follow-up, adjusted analysis revealed a nonsignificant difference in HbA1c change of 0.14% (21.97 mmol/mol) in favour of the intervention (95% CI −0.08 to 0.36%, p = 0.22). Baseline values were 7.02 ± 1.25% in the intervention and 7.08 ± 1.25 in the control group. None of the secondary outcome measures showed significant differences except for improved quality of life (EQ-5D-VAS) in controls (4.3 points on a scale of 100; 95% CI 0.08 to 8.53, p = 0.046) compared to the intervention group. Conclusion. Our peer support intervention as an additional DMP component showed no significant effect on HbA1c and secondary outcome measures. Further RTCs with a longer follow-up are needed to reveal whether peer support will have clinically relevant effects. Trial Registration. This trial has been registered with Current Controlled Trials Ltd. (ISRCTN10291077).

A group-based peer support programme as an additional component of a DMP in type 2 diabetes is a promising approach to optimize diabetes care and to enhance lifestyle interventions in primary care. Peer support seems to reduce length of hospital stay and could therefore be a cost-effective model.

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