Enhancing Self-Management of T2DM with In-Home Technology

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

4. Common-sense Models of Illness • Life experience of acute illness teaches us to use symptoms as indicators of sickness-wellness • In most chronic illnesses, symptoms are unreliable as indicators of disease status • Better to utilize objective measures by performing self-monitoring (e.g., SMBG, BP)

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 Total of 200 participants Four in-home visits; intervention begins at visit 2 after 3 months. Exit interview at 15 months.

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

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

10. Monitor Blood Sugar Readings: Objective Measures NO Symptoms Can do what Need & want To do Dr. Says Test Shows HIGH Blood Sugar Should I take meds, diet to control diabetes if I feel Okay? Answer Okay No Symptoms NO Ask Myself How do I feel? It’s time to test my blood sugar I don’t know my blood sugar level – I can’t feel it Proper timing and consideration is necessary for this to work- DO THE NUMBERS MAKE SENSE?!! If high: Take medication, exercise, etc. Act Plans Take meds, exercise! Act Plan Use the glucometer & computer Monitor & Appraise blood sugar readings

11. Light-blue boxes = computer logic Green boxes = patient input Individualized in logic: 1) scheduled glucose reading times, 2) goals for scheduled time for trend summary Trend summary begins after 10 readings SD based on 25 readings

12. System Demonstration

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 1 Center for Health & Behavior, Rutgers University and UMDNJ, New Brunswick, NJ

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

16. Expanded study to rigorously test this system • Illness cognition, change over time • Reminder function • Expanded feedback • Trends in control • Unscheduled measures • Relating measures to diet and activity