Predictors of 30 day hospital readmission in patients with type 2 diabetes: a retrospective, case-control, database study

Objective: To assess factors predictive of all-cause, 30 day hospital readmission among patients with type 2 diabetes in the United States.

Methods: A retrospective, case-control study using deidentified Humedica electronic health record data was conducted to identify patients ≥18 years old with ≥6 months of data prior to index hospitalization (pre-period) and ≥30 days of data after discharge (post-period). Combined methods of bootstrap resampling and stepwise logistic regression were used to identify factors associated with readmission.

Results: Among 52,070 patients with type 2 diabetes and an initial hospitalization for any reason, 5201 (10.0%) patients were readmitted within 30 days and 46,869 (90.0%) patients showed no evidence of readmission. Diabetic treatment escalation; race; type 2 diabetes diagnosis prior to the index stay; pre-period heart failure; and number of pre-period, inpatient healthcare visits were among the strongest predictors of 30 day readmission. From a receiver-operating characteristic plot (mean area under curve of 0.693), the predictive accuracy of the final logistic regression model is considered modest. This result might be due to the unavailability of some variables or data.

Conclusions: These results highlight the importance of the appropriate recognition of and treatment for type 2 diabetes, prior to and during hospitalization and following discharge, in order to impact a subsequent hospitalization. In our analysis, escalation of diabetic treatments (especially those escalated from having no records of anti-diabetic medications to treatment with insulin) was the strongest predictor of 30 day readmission. Limitations of this study include the fact that hospitalizations and other encounters, outside the Humedica network, were not captured in this analysis.