John Steiner, MD, MPH

SUPREME - DM has developed a comprehensive, longitudinal clinical registry of a population of approximately 1.1 million insured patients with diabetes mellitus. The project has developed a similar database of all members without diabetes from 11 integrated healthcare delivery systems. These databases can be used for surveillance and research. The registry covers the period from 2005-2012, draws from demographic and clinical data elements in Electronic Health Records (EHRs) and other system databases, captures patient-reported data where it is already being routinely collected, and adds calculated data on medication adherence. The SUPREME-DM Network is comprised of a multi-disciplinary network of nearly 30 diabetes researchers from both the HCSRN and academic centers.  

 

In September 2013, the SUPREME-DM Network was awarded additional funding from AHRQ to: 

  • Collaborate with a broad array of stakeholders to prioritize critical themes and topics for CER and patient-centered outcomes research (PCOR) to prevent and treat diabetes; 

  • Develop and test specific enhancements to the SUPREME-DM DataLink that expand its capacity to address stakeholder priorities for research to improve diabetes prevention and treatment; and 

  • Develop a 5-year plan to sustain the capacity of the SUPREME-DM Network and its DataLink to address high-priority themes and topics for CER and PCOR.

This work will develop the DataLink according to the priorities of multiple stakeholders by translating those priorities into specific improvements in data content and governance that, in turn, will facilitate research with the goal of improving outcomes for individuals who live with diabetes.

 

QUICK FACTS

  • PI: John F. Steiner, MD, MPH of Kaiser Permanente Colorado's Institute for Health Research

  • Funding agency: Agency for Healthcare Research and Quality (AHRQ)

  • Year funded: 2010

  • Number of related studies funded, since inception:  5

  • Website: supreme-dm.org

 

PARTICIPATING RESEARCH CENTERS

 

ADDITIONAL PARTNERS

SUPREME-DM also partners with the Centers for American Indian and Alaska Native Health (CAIANH) at the University of Colorado at Denver’s Colorado School of Public Health.  CAIANH is funding a sub-study called, “Processes and Outcomes of Diabetes Care for American Indians and Alaskan Natives within Integrated Health Care Delivery Systems.”

 

KEY ACTIVITIES

  • DataLink: develop a comprehensive, longitudinal clinical registry of a population of approximately 1.1 million insured patients with diabetes mellitus, and a similar database of all members without diabetes from 11 integrated healthcare delivery systems that covers the period 2005-2012.

  • Prevention study: this comparative effectiveness observational study involved women with recent gestational diabetes to understand the effectiveness of various communication, counseling, and referral strategies.

  • Treatment study: this comparative effectiveness study conducted a trial to evaluate the effectiveness of brief counseling on “early non-adherence” with newly prescribed medications

  • Natural Language Processing (NLP): patient-reported and NLP-derived measures are being examined as potential mediators or modifiers of treatment effectiveness in the Prevention and Treatment studies.

  • Continuation Study - Sustaining a Learning Research Network: gather an array of key stakeholders, including members of the patient community, to prioritize critical themes and topics for CER and patient-centered outcomes research to prevent and treat diabetes. Using the themes identified, the team will develop and test specific enhancements to the SUPREME-DM DataLink with the goal to expand its capacity to address stakeholder priorities. Finally, five-year sustainability plan will be developed.

 

UNIQUE ASSETS & CAPABILITIES

The SUPREME-DM DataLink contains the largest privately-insured diabetes patient cohort ever assembled in the United States.  Using this resource, we are able to study: 
  • How closely providers are following ADA recommendations for persons newly identified with diabetes

  • How using different laboratory definitions affects diagnosing patients with chronic kidney disease

  • Methodological processes such as testing imputation of hemoglobin A1c in a diabetic population

  • Drug burden in this population.

Additional analyses are ongoing.