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Master of Public Health

Validation of Risk Score in Predicting Early Readmissions in Decompensated Cirrhotic patients: A Model Based on the Administrative Database

AUTHORS

Mumtaz K , Issak A , Porter K , Kelly S , Hanje J , Michaels AJ , Conteh LF , El-Hinnawi A , Black SM , Abougergi MS , . Hepatology (Baltimore, Md.). 2018 9 15; ().

ABSTRACT

INTRODUCTION: The early readmission in patients with decompensated liver cirrhosis leads to enormous burden on healthcare utilization.

METHODS: Retrospective cohort study using the 2013 and 2014 Nationwide Readmission Database (NRD) was conducted. Patients with diagnoses of cirrhosis and at least one feature of decompensation were included. The primary outcome was to develop a validated risk model for early readmission. Secondary outcomes were to study 30-day all cause-readmission rate and most common reasons for readmission. Multivariable logistic regression model was fit to identify predictors of readmissions. Finally, a risk model named as Mumtaz Readmission risk score was developed for prediction of 30-day readmission based on 2013 NRD and validated on 2014 NRD.

RESULTS: A total of 123,011 patients were included. The 30-day readmission rate was 27%. 79.6% of patients were readmitted with liver related diagnoses. Age <65 years, Medicare or Medicaid insurance, non-alcoholic etiology of cirrhosis, ≥3 Elixhauser score, presence of hepatic encephalopathy (HE), ascites, variceal bleeding, hepatocellular carcinoma, paracentesis, hemodialysis and discharge against medical advice were independent predictors of 30-day readmission. This validated model enabled patients with decompensated cirrhosis to be stratified into low (<20%), medium, (20-30%) and high (>30%) risk of 30-day readmissions.

CONCLUSION: One third of patients with decompensated cirrhosis are readmitted within 30 days of discharge. The use of simple risk scoring model with high generalizability, based on demographics, clinical features and interventions can bring refinement to the prediction of 30-day readmission in high risk patients. Mumtaz readmission risk score highlights the need for targeted interventions in order to decrease rates of readmission within this population. This article is protected by copyright. All rights reserved.

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