Identifying Type 1 and Type 2 Diabetic Cases Using Administrative Data: A Tree-Structured Model

J Diabetes Sci Technol. 2011 May 1;5(3):486-93. doi: 10.1177/193229681100500303.


Background: To date, few administrative diabetes mellitus (DM) registries have distinguished type 1 diabetes mellitus (T1DM) from type 2 diabetes mellitus (T2DM).

Objective: Using a classification tree model, a prediction rule was developed to distinguish T1DM from T2DM in a large administrative database.

Methods: The Medical Archival Retrieval System at the University of Pittsburgh Medical Center included administrative and clinical data from January 1, 2000, through September 30, 2009, for 209,647 DM patients aged ≥18 years. Probable cases (8,173 T1DM and 125,111 T2DM) were identified by applying clinical criteria to administrative data. Nonparametric classification tree models were fit using TIBCO Spotfire S+ 8.1 (TIBCO Software), with model size based on 10-fold cross validation. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of T1DM were estimated.

Results: The main predictors that distinguished T1DM from T2DM are age <40 years; International Classification of Disease, 9th revision, codes of T1DM or T2DM diagnosis; inpatient oral hypoglycemic agent use; inpatient insulin use; and episode(s) of diabetic ketoacidosis diagnosis. Compared with a complex clinical algorithm, the tree-structured model to predict T1DM had 92.8% sensitivity, 99.3% specificity, 89.5% PPV, and 99.5% NPV.

Conclusion: The preliminary predictive rule appears to be promising. Being able to distinguish between DM subtypes in administrative databases will allow large-scale subtype-specific analyses of medical care costs, morbidity, and mortality.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Algorithms
  • Data Collection
  • Databases, Factual
  • Decision Trees
  • Diabetes Mellitus, Type 1 / classification
  • Diabetes Mellitus, Type 1 / diagnosis*
  • Diabetes Mellitus, Type 2 / classification
  • Diabetes Mellitus, Type 2 / diagnosis*
  • Female
  • Humans
  • Inpatients
  • Male
  • Medical Records
  • Middle Aged
  • Outpatients
  • Pennsylvania
  • Registries