551R eadmission to hospital and death are adverse patient outcomes that are serious, common and costly.1,2 Several studies suggest that focused care after discharge can improve post-discharge outcomes.3-7 Being able to accurately predict the risk of poor outcomes after hospital discharge would allow health care workers to focus post-discharge interventions on patients who are at highest risk of poor post-discharge outcomes. Further, policy-makers have expressed interest in either penalizing hospitals with relatively high rates of readmission or rewarding hospitals with relatively low expected rates. 8 To implement this approach, a validated method of standardizing readmission rates is needed. 9Two validated models for predicting risk of readmission after hospital discharge have been published. 10,11 However, these models are impractical to clinicians. Both require arealevel information (e.g., neighbourhood socio-economic status and community-specific rates of admission) that is not readily available. Getting this information requires access to detailed tables, thereby making the model impractical. Second, both models are so complex that risk estimates cannot be attained from them without the aid of special software. Although these models have been used by health-system planners in the United Kingdom, we are unaware of any clinicians who use them when preparing patients for hospital discharge.Our primary objective was to derive and validate a clinically useful index to quantify the risk of early death or unplanned readmission among patients discharged from hospital to the community. Methods Study designWe performed a secondary analysis of a multicentre prospective cohort study conducted between

Among patients receiving opioids for nonmalignant pain, the daily dose is strongly associated with opioid-related mortality, particularly at doses exceeding thresholds recommended in recent clinical guidelines.

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clinicaltrials.gov Identifier: NCT01108172.

U rgent, unplanned hospital readmissions are increasingly being used to measure institutional or regional quality of care. 1−4 The public reporting of readmissions and their use in considerations for funding suggest a belief that readmissions indicate the quality of care provided by particular institutions. However, urgent readmissions are an informative metric only if we know what proportion of them are avoidable. If they are rarely avoidable, they would be a poor gauge of the quality of patient care.Current estimates of the proportion of urgent readmissions that are avoidable are unreliable. In a systematic review of 34 studies that reviewed how many readmissions were avoidable, 3 of the studies relied solely on combinations of administrative diagnostic codes, and most used undefined or subjective criteria. 5 In addition, most of the studies were conducted at a single centre and used only one reviewer. The proportion of readmissions deemed avoidable varied widely, from 5.1% 6 to 78.9%, 7 which reflected in part the lack of standardized and reliable methods to identify avoidable readmissions.We conducted a multicentre prospective cohort study to elicit judgments from multiple practising physicians who used standard implicit review methods to determine whether urgent re admissions were potentially avoidable. We analyzed these judgments using a latent class analysis. We also measured the proportion of readmissions deemed avoidable and compared hospital-specific proportions of all-cause and avoidable readmissions. Methods Study designThis was a secondary analysis of a multicentre prospective cohort study involving patients discharged to the community after elective or urgent Research CMAJ Background: Urgent, unplanned hospital readmissions are increasingly being used to gauge the quality of care. We re viewed urgent readmissions to determine which were potentially avoidable and compared rates of allcause and avoidable readmissions. Incidence of potentially avoidable urgent readmissions and their relation to all-cause urgent readmissions

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