Clinician agreement and influence of medication-related characteristics on assessment of polypharmacy.

It is not known how clinicians assess polypharmacy or the medication-related characteristics that influence their assessment. The aim of this study was to examine the level of agreement between clinicians when assessing polypharmacy and to identify medication-related characteristics that influence their assessment. Twenty cases of patients with varying levels of comorbidity and polypharmacy were used to examine clinician assessment of polypharmacy. Medicine-related factors within the cases included Beers and STOPP Criteria medicines, falls-risk medicines, drug burden index (DBI) medicines, medicines causing postural hypotension, and pharmacokinetic drug-drug interactions. Clinicians were asked to rate cases on the degree of polypharmacy, likelihood of harm, and potential for the medication list to be simplified. Inter-rater reliability analysis, correlations, and multivariate logistic regression analyses were conducted to identify medicine factors associated with clinicians' assessment. Eighteen expert clinicians were recruited (69.2% response rate). Strong agreement was observed in clinicians' assessment of polypharmacy (intraclass correlation coefficients [ICC] = 0.94), likelihood to cause harm (ICC = 0.89), and ability to simplify medication list (ICC = 0.90). Multivariate analyses demonstrated number of medicines ( P  < 0.0001) and DBI scores ( P  = 0.047) were significantly associated with assessment of polypharmacy. Medicines associated with harm were significantly associated with the number of medicines ( P  = 0.01) and Beers criteria medicines ( P  = 0.003). Ability to simplify the medication regimen was significantly associated with number of medicines ( P  = 0.03) and medicines from the STOPP criteria ( P  = 0.018). Among clinicians, strong consensus exists with regard to assessment of polypharmacy, medication harm, and ability to simplify medications. Definitions of polypharmacy need to take into account not only the numbers of medicines but also potential for medicines to cause harm or be inappropriate, and validate them against clinical outcomes.