title: Predictors of 30 day hospital readmission in patients with type 2 diabetes: a retrospective, case-control, database study.
abstract: 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.
authors.affiliation: Former employee of Eli Lilly and Company , Indianapolis, IN , USA.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Eby
authors.forename: Christine
authors.initials: C
authors.lastname: Hardwick
authors.forename: Maria
authors.initials: M
authors.lastname: Yu
authors.forename: Steve
authors.initials: S
authors.lastname: Gelwicks
authors.forename: Ketra
authors.initials: K
authors.lastname: Deschamps
authors.forename: Jin
authors.initials: J
authors.lastname: Xie
authors.forename: Tom
authors.initials: T
authors.lastname: George
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D016208:Databases, Factual; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000628:therapy*; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010359:Patient Readmission; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D014481:United States; D055815:Young Adult
chemical_list: D007004:Hypoglycemic Agents
keywords: Diabetes mellitus; Hospital readmission; Hospitalization; Regression analysis; Type 2 diabetes mellitus