Stefan Becker*, Institute for Drug Safety and Department of Nephrology, University Hospital Essen, Essen, Germany Alexander Mertens, Chair and Institute of Industrial Engineering and Ergonomics, RWTH Aachen University, Aachen, Germany Christopher Brandl, Chair and Institute of Industrial Engineering and Ergonomics, RWTH Aachen University, Aachen, Germany Sven Meister, Fraunhofer Institute for Software and Systems Engineering, Dortmund, Germany, Dortmund, Germany Talya Miron-Shatz, Marketing Department, Business School, Ono Academic College, Kiryat Ono, Israel Urs-Vito Albrecht*, Peter L. Reichertz Institute for Medical Informatics, Hannover Medical School, Hannover, Germany Andreas Keck, KECK medical concepts and business management GmbH, Hamburg, Germany Anna Mitchell, Department of Nephrology, University Hospital Essen, Essen, Germany Andreas Kribben, Department of Nephrology, University Hospital Essen, Essen, Germany Eckhard Nagel, Institute for Drug Safety, University Hospital Essen, Essen, Germany Track: Research Presentation Topic: Mobile & Tablet Health Applications Presentation Type: Oral presentation Submission Type: Single Presentation Building: Sol Principe Room: B - Gibralfaro Date: 2014-10-10 09:00 AM – 09:45 AM Last modified: 2014-09-10

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Background:
Drug adherence is a problem in the management of patients with chronic conditions. Numerous mobile applications try to support users in their regular and correct drug intake. Yet high attrition and digital divide is described in the usage of health-related apps. On developing software for patients it is therefore important to know whether users are likely to login a mobile application by themselves and who may need further assistance.

Objective:
To analyze demographic- and health-related factors associated with “long-term-usage” and “more intense” usage of the mobile application “Medication Plan”.

Methods: Between 2010-2013 the application “Medication Plan” could be downloaded free of charge from the AppleAppStoreTM. Users were able to keep and alter a list of their regular medication. A local push-notification supported the regular intake. Demographic and health-related data were collected via an online questionnaire. This study analyzed data captured on "Medication Plan". Dependent variables were “duration of long-term usage” (defined as >1day and if no activity in app usage was recorded for >10 days users had stopped applying) and “intensity of usage per day” during time of active usage. The unique identifier numbers were irreversibly encrypted and its activity tracked. Associated information was analyzed.

Results:
Overall activity of 1708/1799 users, who fully completed the questionnaire, was recorded between December 2010 and April 2013. 69 % (1183/1708) applied “Medication Plan” more than a day. Of those 1183 users, 74 % were male (872), 15% (182) were <31 years, 48% (567) between 31 and 50 years and 37% (434) >50 years of age. 29% (338) had gained a university degree. 55% (651) stated to be suffering from cardiovascular disease, 7% (79) from diabetes, 5% (64) from lung disease, 5% (58) from liver disease. 70% (826) were taking 3 or less different medications/day and 30% (357) were taking 4 or more medications/day. Variance analysis presented the following effects with respect to duration of usage: sex and educational attainment had no effect. Yet with a mean duration of usage of 23.3 days (SD 36.9) by users < 21 years there was a significant increase over all age cohorts with users of 60 years and above using the application for 103,9 days on average (SD 20.7) (F=2,581; df=5; p=0.025). With regard to usage intensity demografic predictors (sex, age and educational attainment) showed no effect. Usage intensity was directly associated with an increasing number of prescribed medication and increased from on average of 1.87 uses per day (SD 1.83) and 1 drug per day to on average 3.71 uses per day (SD 2.12) for users stating to be taking more than 7 different drugs a day (F=4.017; df=7; p<0.001).

Conclusion: With regard to “long-term” usage and usage intensity, our data show that the often cited threefold “digital divide” between age groups, sexes and according to education levels could not be detected among “long-term” users. Particularly older users and those with more complicated therapeutic drug regimes seemed to have relied on our service. The data show that such technology may indeed be a promising approach to support the treatment of patients with chronic conditions.