A Study Evaluating the Use of Potential Predictors of Readmission in Hospitalized Medicine Patients

Many patients are readmitted to the hospital shortly after discharge. Twenty percent of Medicare beneficiaries discharged were re-hospitalized within 30 days at a cost to Medicare estimated at $17.4 billion. This problem does not only affect the elderly. Medicaid enrollees aged 21-64 had 10.7% 30-day readmission rate. Identifying which patients are at highest risk is important for allocating resources to those high risk individuals. Several studies have attempted to retrospectively identify medical conditions, medications, labs, and vitals associated with increased risk of readmission with different levels of success. Examples of these include the Charlson Comorbidity Index, LACE, and the Comorbidity Polypharmacy Score. Although not always developed for use in predicting readmissions, they have been subsequently associated with this. While these indices examine objective data, it is thought that health beliefs, abilities, and behaviors can also affect the risk of readmissions. Health literacy in particular has been shown to be associated with 30 day readmissions after an acute myocardial infarction and in general medical patients. Low numeracy has been associated with increased risk of 30 day readmission in patients with acute heart failure. Inpatient questionnaires are able to identify patients who are more likely than others to be readmitted. Additionally, objective qualities such as insurance status, comorbidities, and admissions within the past year are predictors of readmission. Due to the unique patient populations at different health systems, an institution-specific approach is necessary to analyze the specific factors contributing to readmission. Therefore, a survey will be used to gauge the most predictive factors of readmissions and ED visits, including objective and subjective sections. After further research and modification, the survey will potentially serve as a tool for clinicians to select the best approach to post-discharge care and follow-up. This pilot will attempt to test a survey for predicting readmission through measurements of health literacy, numeracy, medication adherence, self-efficacy, and tolerance, and in conjunction with co-morbidity indices.