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Hypoglycemic Therapeutic Decision Making in Type 2 Diabetes Mellitus

The purpose of this project is to conduct an analysis of data from electronic health records in order to better understand the therapeutic decision-making process physicians follow when prescribing drugs for the treatment of type 2 diabetes mellitus. Furthermore, the analysis explores the differences between patients who receive different therapies and concomitant therapies related to underlying patient characteristics, including BMI, age, gender, blood pressure, co-morbid conditions, and renal function, instead of attempting to control for all of these variables.

Specific Aim 1: Evaluate patient level differences in an inception cohort of individuals with new onset type 2 diabetes mellitus, cared for by clinicians within one or more DARTNet Institute networks using electronic health record data with a focus on initial treatment decisions, stepped care approaches and initiation of insulin within 24 months of treatment initiation.

Specific Aim 2: Evaluate patient differences and practice patterns in two cohorts of individuals with evidence of at least 5 years since the initial diagnosis of T2DM; one of which initiated insulin within 5 years of their initial diagnosis and one which did not with analytical attention to glycemic control, number of oral medications required and patterns of use prior to insulin initiation and after 5 years of treatment.


Funded by an independent research grant provided by Sanofi USA, $179,127, Wilson Pace, PI

Dataset Description

Type of Patients Included N Data Elements
Persons of age > 18, with a diagnosis (defined by ICD-9 code) on diabetes (any type) and/or one A1c > 6 143,057
  • Year of birth
  • Gender
  • Current smoking status
  • Alcohol use
  • Height/weight
  • HbA1c
  • Urine protein/creatinine ratio
  • Lipid panel
  • Creatinine
  • Glucose
  • All medications
  • All diagnosis codes (active and inactive) (ICD-9)
  • Blood pressure
  • Estimated GFR
  • Insurance coverage
  • Death status
  • Hospitalizations
  • Hypo- and hyper-glycemic events
  • Complications from diabetes
  • Race/ethnicity