Abstract
Background: Case management provides a process and structure in health care systems that influence and control quality of care while reducing costs. A quality indicator of widespread concern is 30-day readmission of patients. There is significant initiative to drive down hospital readmission rates through development and/or redesign of case management models.
Purpose: To examine the relationship of a collaborative case management model on hospital readmission rates among patients aged 65 years and older.
Methodology and Sample: A retrospective chart review of patients discharged alive (n = 978) was conducted to evaluate and compare 2 care management models on hospital readmission rates. Demographic data, diagnosis, insurance carrier, admission source, discharge disposition, and incidence of readmission were collected using a structured data extraction tool. Logistic regression was used to identify predictors of readmission within 30 days of hospital discharge.
Results: The sample was elderly (mean age = 79.5 years), White (88.8%), and primarily female (60%). Mean length of stay between pre- and postmodel groups was not statistically different (p = .2). The model contained 6 independent variables (gender, payer, admission source, discharge disposition, diagnosis, and length of stay) and none were statistically significant, [chi]2 (1, n = 978) = 1.97, p = .58. The analysis indicates that group characteristics did not distinguish who would get readmitted on the basis of independent variables measured.
Implications for Case Management Practice: Age, gender, admit source, diagnosis, length of stay, and discharge disposition are not significant predictors of readmissions. Hospital case management programs may want to consider structuring processes to support patient adherence. Additional research is needed in this area.