Frequentie en acceptatie van door beslisondersteuning gegenereerde STOPP/START-signalen bij ouderen met polofarmacie en multimorbiditeit opgenomen in het ziekenhuis

Frequency and acceptance of clinical decision support system generated STOPP/START signals for hospitalised older patients with polypharmacy and multimorbidity Background The Screening Tool of Older Persons’ Prescriptions (STOPP)/Screening Tool to Alert doctors to Right Treatment (START) instrument is a screening tool to evaluate the medication regimen in older people. STOPP/START criteria have been converted into software algorithms and implemented in a clinical decision support system (CDSS) to facilitate their use in clinical practice. Objective To determine the acceptance of CDSS generated STOPP/START signals by a pharmacotherapy team in hospitalised older patients with polypharmacy and multimorbidity. Design and methods Hospitalised multimorbid older patients with polypharmacy assigned to the Dutch intervention arm of the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly) trial were included. Intervention patients received a CDSS-assisted structured medication review. The acceptance of CDSS-generated STOPP/START signals by a pharmacotherapy team and determinants for acceptance were evaluated. Results In 98% of the 203 included patients, at least one STOPP/START signal was generated. Overall, 43.1% of all 1059 signals were accepted. STOPP signals (51.5%) were more likely than START signals (39.1%) to be accepted per patient (mean difference: 12.4%; 95% confidence interval 4.7-20.1). A history of falls was positively associated with acceptance (+11.8%) while prior hospitalization (−10.7%), decreased renal function (−11.2%) and long hospital stay (−9.0%) were negatively associated with acceptance. Conclusion About half of the generated STOPP/START signals were accepted by the pharmacotherapy team. The nature of the signal was a better predictor for acceptance than patient or setting related factor

Identification of behaviour change techniques in deprescribing interventions: a systematic review and meta-analysis

Aims Methods Deprescribing interventions safely and effectively optimize medication use in older people. However, questions remain about which components of interventions are key to effectively reduce inappropriate medication use. This systematic review examines the behaviour change techniques (BCTs) of deprescribing interventions and summarizes intervention effectiveness on medication use and inappropriate prescribing. MEDLINE, EMBASE, Web of Science and Academic Search Complete and grey literature were searched for relevant literature. Randomized controlled trials (RCTs) were included if they reported on interventions in people aged >= 65 years. The BCT taxonomy was used to identify BCTs frequently observed in deprescribing interventions. Effectiveness of interventions on inappropriate medication use was summarized in meta-analyses. Medication appropriateness was assessed in accordance with STOPP criteria, Beers' criteria and national or local guidelines. Between-study heterogeneity was evaluated by I-squared and Chi-squared statistics. Risk of bias was assessed using the Cochrane Collaboration Tool for randomized controlled studies. Results Conclusions Of the 1561 records identified, 25 studies were included in the review. Deprescribing interventions were effective in reducing number of drugs and inappropriate prescribing, but a large heterogeneity in effects was observed. BCT clusters including goals and planning; social support; shaping knowledge; natural consequences; comparison of behaviour; comparison of outcomes; regulation; antecedents; and identity had a positive effect on the effectiveness of interventions. In general, deprescribing interventions effectively reduce medication use and inappropriate prescribing in older people. Successful deprescribing is facilitated by the combination of BCTs involving a range of intervention components