INNOVATION FUND Innovation, Integration, & Implementation Mental Health and Geriatric Care SHOWCASE 2016 INNOVATION FUND Innovation, Integration, & Implementation Mental Health and Geriatric Care SHOWCASE 2016

Risk of Readmission to Acute Psychiatric Units in Ontario: A Gender-based Analysis

Mental Health and Geriatric Care


Simone Vigod


WCH AFP, Women’s College Hospital, and University of Toronto


Our major output was a validated clinical risk prediction index to identify psychiatric inpatients at risk for early rehospitalisation, the READMIT scale (Vigod et. al., Psych Res, 2015). We are now licensing READMIT to major U.S.-based health care organizations for integration into their behavioural health systems in an effort to identify patients at risk for 30-day readmission so as to deliver targeted interventions that reduce this risk, and meet the U.S. Affordable Care Act qulity standards. To support implementation, I also led a systematic review on transitional care interventions to reduce readmission risk cited > 50 times (Vigod et al, Brit J Psych 2013), work on quality of care indicators for the MOHLTC mental health strategy and on a project measuring mental health performance across Canadian provinces to help improve mental health care delivery in Canada.


Our aim was to create a clinically useful risk index, administered prior to discharge, for determining the probability of psychiatric readmission within 30 days of hospital discharge for general psychiatric inpatients.  We used population-level sociodemographic and health administrative data to develop a predictive model for 30-day readmission among adults discharged from an acute psychiatric unit in Ontario, Canada (2008 to 2011), and converted the final model into a risk index system. We derived the predictive model in one-half of the sample (n=32,749) and validated it in the other half of the sample (n=32,750). Variables independently associated with 30-day readmission (forming the mnemonic READMIT) were: (R) Repeat admissions; (E) Emergent admissions (i.e. harm to self/others); (D) Diagnoses (psychosis, bipolar and/or personality disorder), and unplanned Discharge; (M) Medical comorbidity; (I) prior service use Intensity; and (T) Time in hospital. Each 1-point increase in READMIT score (range 0-41) increased the odds of 30-day readmission by 11% (odds ratio 1.11, 95% CI 1.10-1.12). The index had moderate discriminative capacity in both derivation (C-statistic = 0.631) and validation (C-statistic = 0.630) datasets. Determining risk of psychiatric readmission for individual patients is a critical step in efforts to address the potentially avoidable high rate of this negative outcome. The READMIT index provides a framework for identifying patients at high risk of 30-day readmission prior to discharge, and for the development, evaluation and delivery of interventions that can assist with optimizing the transition to community care for patients following psychiatric discharge.

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