Enhancing Self-Management of T2DM with In-Home Technology

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T2DM92% of all diabetes10% of adults 20% of adults > 65 years of ageHigh costTreatment, managementComplications. Optimum management requires patients to take volitional control of a process that is automatic in healthy individualsSelf-regulation/Control processes take place in ?real world" se

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Enhancing Self-Management of T2DM with In-Home Technology

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1. Enhancing Self-Management of T2DM with In-Home Technology Edith Burns, MD Medical College of Wisconsin Milwaukee, WI

2. T2DM 92% of all diabetes 10% of adults 20% of adults > 65 years of age High cost Treatment, management Complications

3. Optimum management requires patients to take volitional control of a process that is automatic in healthy individuals Self-regulation/Control processes take place in “real world” settings- day-to-day life at home, work

5. T2DM is a “chaotic” disease Multiple factors contribute to acute fluctuations in blood glucose levels Individual SMBG measures at any given point in time may provide ambiguous feedback Can we teach patients to learn to use SMBG more effectively to become better self managers of a chaotic disease?

6. Study Design Test an automated reminder and feedback system (ASMM) Randomized, prospective, “usual care” control System provides reminders AND feedback

7. Qualities Desired in the Assisted-Self-Management Monitor (ASMM) Physical Properties Home-based Small footprint Limited components Installation Ease of use Simple docking system “Hidden” technology Ability to individualize Reminders PCP & participant-determined schedule Patient “controls” the technology 1) “untrained” installers 2) I’m using the device, not the device using me!1) “untrained” installers 2) I’m using the device, not the device using me!

9. Qualities Desired in the Assisted-Self-Management Monitor (ASMM), continued Feedback Timely – importance of what the results mean at the time Scheduled measures Unscheduled measures Symptoms? Relationship to management behaviors (timing) Diet Exercise Overall control Trend data Minimizes “catastrophizing” of single readings

13. Co-Investigators & Research Team Jeffrey Whittle, MD Paul Knudson, MD Sergei Tarima, PhD Bambi Wessel, MS Alexis Dye, MA Stephen Flax, PhD Joan Pleuss, CDE, RD Colin Strub, BS Kristin Wiescorek, BS Howard Leventhal, PhD1

15. SUMMARY Increasing frequency and consistency of SMBG led to improved glycemic control Higher baseline depression scores had higher baseline HbA1c and showed greater improvement over time Improvement in HbA1c was not correlated to baseline cognitive function

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