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Apr 23, 2019

27th European Congress of Psychiatry

19 - FACTORS PREDICTING 30-DAY READMISSION IN PSYCHIATRIC PATIENT POPULATION ON AN INPATIENT UNIT​

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30 Day Readmission

Psychiatric Units

Prediction Model

Abstract

Abstract

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Keywords

30 Day Readmission

Psychiatric Units

Prediction Model

Abstract

Background: Hospital readmission with in thirty day time period has been a major issue in the United States and as per data from Center for Medicare & Medicaid Services, the cost of readmission is estimated to be 26$ billion annually. There is an enormous push to reduce these readmission and in New York. Delivery System Reform Incentive Payment Program (DSRIP) has been established to restructure the health care delivery system with the primary goal of reducing re-admissions by 25% over 5 years with the budget of up to $6.42 billion dollars. DSRIP uses LACE score (Length of stay, Acuity of admission, Co-morbidities & Emergency Department visits in the previous six months) as an assessment tool for determining the high-risk patients for emergent hospitalizations in medicine, but this score has limited validity to psychiatric patients. Relatively new tools developed for psychiatric hospitalization, READMIT score incorporates a weighed scale based on the following factors: repeat admissions, emergent admissions (i.e. harm to self/others), diagnosis (psychosis, bipolar and or personality disorder), unplanned Discharge, medical co-morbidity, prior service use intensity, and time in hospital. In an attempt to provide better outcomes for our patient population BLHC has developed a scale that attempts to incorporate factors specific to its own patient populations. This graded scale was coined ZAC score based on risk factors identified on literature review and with 4 components as shown below and the score range is from 0 to 12. Methods: We scored the available tools LACE, READMIT and ZAC score for 170 patients, who were admitted to our inpatient units, to assess the accuracy of both measures in predicting psychiatric inpatient readmission within 30 days. The sample consisted of consecutively admitted patients to our inpatient psychiatric units at Bronx Lebanon hospital between June 2014 to June 2015 with Medicaid as health insurance and The follow up data was collected using Office of mental health database PSYCKES from New York State Medicaid claims database. Cox Regression analysis was performed for multi-factorial prediction model for 30 day readmission. Results:The readmission rate within 30 days was 28 percent. The variables predicting early readmission were severity of pathology (history of prior hospitalization >= 1 in six months and >=3 in past three years), non compliance (patients on TOO, AOT and ACT teams) and violent behavior (prior to admission, requiring > 2 IM injections within 72 hours). Length of hospitalization was not a predictor for 30 day readmission on multi-factorial analysis. Conclusion: To date, there is no validated tool, used to predict re-admissions in the psychiatric patient population. READMIT & ZAC scores were better in predicting 30 day readmission in psychiatric setting when compared to LACE score. The variables predicting early readmission in our data set were severity of illness, non compliance and violent behavior prior to readmission. Length of hospitalization was not a predictor for 30 day readmission.

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© Copyright 2019 Morressier GmbH.
All rights reserved.