Factors influencing the long-term use of a web-based disease management program for self-care support of patients with diabetes type 2 as presented at Medicine 2.0'10

1. Factors influencing the long-term use
of a web-based disease management program for self-care
support of patients with diabetes type 2
Nicol Nijland, PhD, University of Twente
Bart Brandenburg, MD, Medicinfo
Lisette van Gemert-Pijnen, PhD, University of Twente
Medicine 2.0’10, 29-30 Nov, Maastricht, the Netherlands

3. Research focus

4. The Diabetescoach
online
support
10-08-2010 01-01-2007

5. The “Who”
Characteristics n (%)
Education (n = 43) Low 5 (12)
Medium 22 (51)
High 16 (37)
Health status (n = 43) Excellent 0 (0)
Very good 6 (14)
Good 25 (58)
Fair 12 (28)
Poor 0 (0)
Diabetes duration (n = 42) 0-2 year 12 (29)
3-6 years 16 (38)
>7 years 14 (33)
Diabetes treatment (n = 43) No treatment 2 (5)
Diet 4 (9)
Diet & tablets 37 (86)
Diet, tablets & insulin 0 (0)
Diet & insulin 0 (0)

6. Statement 1: Motivate the unmotivated
eHealth technologies (eHts) will have most effect on
unmotivated & unhealthy care consumers
We need to find ways to reach people who need eHts
the most; those with the greatest need for care

7. The “What”
Main features of the web application
Online monitoring
35,2%
Personal data
26,2%
E-mail contact
23,2%
Online education
7,5%
Calendar
5,3%
Personal lifestyle coach
2,5%
Printing feature
1,7%
Total hits (n = 6289)

8. Email message content
Total messages Patients’ messages Nurses’ messages
(n = 323) (n = 130) (n = 193)
Statements Statements Statements
Content categories (%) (%) (%)
Measurementsa (32.2) (32.3) (33.2)
Top 3 Administrative communicationb (31.3) (19.2) (39.9)
Affective communicationc (30.7) (29.2) (32.6)
DiabetesCoach remarksd (15.2) (21.5) (10.9)
Medication usee (13.0) (9.2) (16.1)
Physical symptomsf (9.0) (14.6) (5.2)
Use of DiabetesCoach functionalitiesg (7.4) (2.3) (10.9)
Lifestyle supporth (6.2) (10.8) (4.1)
Current eventsi (5.6) (4.6) (6.2)
Otherj (6.2) (7.7) (5.2)

9. Patients’ messages
monitoring My blood sugar has been a bit higher these days. Do
you think we should do something?
affective At least I am relieved that it has nothing to do with
my diabetes!
administrative
I would like to reschedule our appointment

10. Nurses’ messages
administrative Unfortunately, I will not be present at the practice
next week.
monitoring
Weight and blood pressure look great! Keep going
on!
affective
How are you? Take care

11. Statement 2: Dialogue support
Technology use (adherence) will be enhanced through
dialogue support
More research is needed on which type of dialogue support
works best for whom…
- patients with short-term vs. long-term care needs
- purpose of the communication: task-focused vs. affective

12. Long-term use
60 Barriers to long-term use:
Mean number of hits
§ Lack of push factors
50
§ Usability problems
§ Ceiling effect
40
30
20
10
0
07/07
08/07
09/07
10/07
11/07
12/07
01/08
02/08
03/08
04/08
05/08
06/08
07/08
08/08
09/08
10/08
11/08
12/08
01/09
02/09
03/09
04/09
05/09
06/09
Practice 1 (n=19) Practice 2 (n=24) Practice 3 (n=7) Average practices (n=50)

13. Statement 3: Fixed vs. free use
The effects of technology use will be stronger…
….on patients who log-in every month (fixed use)
….than on patients who log on only once in a while (free use)

15. Usage profiles
Highly active
Freq. log-ins: 45-191
Low active
Freq. log-ins: 10-96
Inactive
Freq. log-ins: 0-56

16. Hardcore users vs. nonusage dropouts
DiabetesCoach Enrollees
(n = 50)
Discontinued users Continuous users
Dropouts 32%
32% 68%
Low active users Hardcore users
38% 30%

17. Statement 4: Methods
Most attrition measures perform survival analysis, like Kaplan
Meier (cut-off measure). However, such measures could not be
used in our study because they only provide insights into…
the drop in usage and not in the pattern of usage
Cut-off measures are not adequate with free-to-use technologies

18. Thank you
Questions?
n.nijland@utwente.nl
ww.ehealthresearchcenter.org/wiki