Profiling remotely monitored patients with adherence parameters

Anna-Leena Orsama, Hannu Kaijanranta, Juha Leppänen, Leila Partanen, Tiina Heliö, Jaakko Lähteenmäki

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review


Remote patient monitoring systems provide plenty of structured information about the monitored health variables. We propose a set of parameters that exploits the remotely monitored data to describe patient's monitoring adherence from different viewpoints. The parameters were applied in self-monitored weight and blood pressure data sets of 30 heart failure patients inherited from a clinical trial setting. With the help of the extracted adherence parameters the thirty heart failure patients were clustered into two subgroups with different monitoring profiles: a group of well-performing subjects (n=22) and a group of low-performing subjects (n=8). Beneficial effects of active monitoring were reflected as positive changes in clinical health outcomes and lowered burdening of health care providers among the group of well-performing subjects.
Original languageEnglish
Title of host publicationProceedings of the IADIS International Conference e-Health 2012, EH 2012, Part of the IADIS Multi Conference on Computer Science and Information Systems 2012, MCCSIS 2012
Subtitle of host publicationIADIS International Conference e-Health 2012
EditorsMário Macedo
Publication statusPublished - 2012
MoE publication typeA4 Article in a conference publication
EventIADIS International Conference e-Health 2012 - Lissabon, Portugal
Duration: 17 Jul 201219 Jul 2012


ConferenceIADIS International Conference e-Health 2012


  • remote patient monitoring
  • telehealth
  • adherence
  • clustering

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