Risk Factor Analysis of Hospital Readmissions at St. Petersburg General Hospital

Decreased readmission rates are largely seen as an indicator of effective care and improved resource management. The case management team at St. Petersburg General Hospital in St. Petersburg, Florida identified chronic obstructive pulmonary disease (COPD) exacerbation, pneumonia, and sepsis as 3 of the leading diagnoses on index admission that later led to 30-day readmissions. By examining patients with these 3 diagnoses on index admission, we decided to investigate potential readmission risk factors including patient age, sex, race, body mass index (BMI), length of stay during the index admission, insurance type during index admission, discharge placement after index admission, coronary artery disease, heart failure, and type 2 diabetes.

We conducted a retrospective study with data from 4180 patients at St. Petersburg General Hospital from 2016 through 2019 with index admission diagnoses of COPD exacerbation, pneumonia, and sepsis. A univariate analysis was conducted on patient sex, race, BMI, length of stay during the index admission, health insurance type during the index admission, discharge placement after the index admission, presence of coronary artery disease, presence of heart failure, and presence of type 2 diabetes. Subsequently, a bivariate analysis was run on these variables in relation to 30-day readmissions. Then a multivariable analysis was completed using binary logistic regression and pairwise analysis to determine the significance between variables within the categories of discharge disposition and insurance type.

Of the 4180 patients included in this study, 926 (22.2%) were readmitted within 30 days of discharge. In the bivariate analysis race, BMI, mean length of stay during the index admission, coronary artery disease, heart failure, and type 2 diabetes were not significantly associated with readmission. The bivariate analysis revealed that patients discharged to skilled nursing facilities had the highest readmission rates (28%), followed by home care (26%) (P = .001). Medicaid patients (24%) and Medicare patients (23%) demonstrated higher read-mission rates than those with private insurance (17%) (P = .001). Readmitted patients were slightly younger (62.14 vs. 63.69 years; P = .02) in the bivariate analysis. However, in the multi-variable analysis, only patients with type 2 diabetes and patients with non-private insurance were associated with increased readmission rates. Pairwise analysis of the variables within insurance and discharge disposition categories demonstrates decreased readmission for individuals with Private/Other when compared to other insurance subtypes and decreased readmission for Other when compared to discharge disposition subtypes.

Our data demonstrate that hospital readmissions are associated with a diagnosis of type 2 diabetes and having a non-private insurance status. Our findings lead us to suggest further investigation into changes in hospital policies and procedures for these groups that will aim to decrease readmission rates in the future.