Emulating a target trial using primary care electronic health records: SGLT-2i medications and Hemoglobin A1c

Sumeet Kalia*, Olli Saarela, Braden O'Neill, Christopher Meaney, Rahim Moineddin, Frank Sullivan, Michelle Greiver

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Substantial effort has been dedicated to conducting randomized controlled experiments to generate clinical evidence for diabetes treatment. Randomized controlled experiments are the gold standard to establish cause and effect. However, due to their high-cost and time-commitment, large observational databases such as those comprised of electronic health record (EHR) data collected in routine primary care may provide an alternative source to address such causal objectives. We used a Canadian primary care repository housed at University of Toronto to emulate a randomized experiment. We estimated the effectiveness of sodium-glucose co-transporter 2 inhibitors (SGLT-2i) medications for patients with diabetes using Hemoglobin A1c (HbA1c) as a primary outcome and marker for glycemic control from 2018 to 2021. We assumed an intention-to-treat analysis for prescribed treatment, with analyses based on the treatment assigned rather than the treatment eventually received. We defined the causal contrast of interest as the net change in HbA1c (%) between the group receiving standard of care versus the group receiving SGLT-2i medications. Using a counterfactual framework, marginal structural models demonstrated a reduction in mean HbA1c with theinitiation of SGLT-2i medications. These findings provided similar effect sizes to those from earlier clinical trials on assessing the effectiveness of SGLT-2i medications.
Original languageEnglish
Pages (from-to)782-789
Number of pages8
JournalAmerican Journal of Epidemiology
Issue number5
Early online date11 Jan 2023
Publication statusPublished - 1 May 2023


  • Randomized controlled trials
  • Marginal structural models
  • Electronic health records
  • Primary care
  • Diabetes
  • Glucose-lowering medications


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