Abstract
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 language | English |
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Title of host publication | Proceedings 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 publication | IADIS International Conference e-Health 2012 |
Editors | Mário Macedo |
Pages | 231-235 |
Publication status | Published - 2012 |
MoE publication type | A4 Article in a conference publication |
Event | IADIS International Conference e-Health 2012 - Lissabon, Portugal Duration: 17 Jul 2012 → 19 Jul 2012 |
Conference
Conference | IADIS International Conference e-Health 2012 |
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Country/Territory | Portugal |
City | Lissabon |
Period | 17/07/12 → 19/07/12 |
Keywords
- remote patient monitoring
- telehealth
- adherence
- clustering