READMIT Clinical Risk Index: Identifying Risk Factors to Reduce 30-day Psychiatric Readmissions

Abstract Problem: There has been a growing concern in the past decades over the increase in community-based adults who require readmission to psychiatric care shortly after discharge. It is estimated that nearly half of discharged psychiatric patients will be readmitted within twelve months after discharge. This has been primarily attributed to the absence of screening tools and resources to assists behavioral healthcare providers in identifying socio-demographic factors contributing to readmissions. Screening tools like the READMIT Clinical Risk Index identify patients at risk for psychiatric readmission. This quality improvement project aims to identify socio-demographic factors that lead to 30-day readmission rates through the implementation of the READMIT Clinical Risk Index. Methods: This quality improvement project used a retrospective chart review with a purposive convenience sample of 96 behavioral health electronic medical records. Data was collected through a two-step process. The first set of data collected patient demographics selecting age, whether participant is black, length of stay, has depression, housing status at discharge, discharged with medication, and has friend support. The second set of data collection captured READMIT scores. Results: Multiple regression (b =- 0.20, p \u3c .001) demonstrated age to be the primary predictor of an individual’s likelihood of 30-day readmission post-discharge. Every one-year increase in age is associated with a 0.20 decline in individuals READMIT scores. Implications for practice: Providers can identify high risk patients when READMIT Index tool is implemented appropriately. Creating an opportunity for developing, evaluating, and delivering interventions that integrate individuals into their communities more successfully