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dc.contributor.authorGokalp, Hulya
dc.contributor.authorde Folter, Joost
dc.contributor.authorVerma, Vivek
dc.contributor.authorFursse, Joanna
dc.contributor.authorJones, Russell
dc.contributor.authorClarke, Malcolm
dc.date.accessioned2020-06-21T13:06:00Z
dc.date.available2020-06-21T13:06:00Z
dc.date.issued2018
dc.identifier.issn1530-5627
dc.identifier.issn1556-3669
dc.identifier.urihttps://doi.org/10.1089/tmj.2017.0322
dc.identifier.urihttps://hdl.handle.net/20.500.12712/11299
dc.descriptionWOS: 000451834200001en_US
dc.descriptionPubMed: 30129884en_US
dc.description.abstractObjective: To investigate the potential of an integrated care system that acquires vital clinical signs and habits data to support independent living for elderly people with chronic disease. Materials and Methods: We developed an IEEE 11073 standards-based telemonitoring platform for monitoring vital signs and activity data of elderly living alone in their home. The platform has important features for monitoring the elderly: unobtrusive, simple, elderly-friendly, plug and play interoperable, and self-integration of sensors. Thirty-six (36) patients in a primary care practice in the United Kingdom (mean [standard deviation] age, 82 [10] years) with congestive heart failure (CHF) or chronic obstructive pulmonary disease (COPD) were provided with clinical sensors to measure the vital signs for their disease (blood pressure [BP] and weight for CHF, and oxygen saturation for COPD) and one passive infrared (PIR) motion sensor and/or a chair/bed sensor were installed in a patient's home to obtain their activity data. The patients were asked to take one measurement each day of their vital signs in the morning before breakfast. All data were automatically transmitted wirelessly to the remote server and displayed on a clinical portal for clinicians to monitor each patient. An alert algorithm detected outliers in the data and indicated alerts on the portal. Patient data have been analyzed retrospectively following hospital admission, emergency room visit or death, to determine whether the data could predict the event. Results: Data of patients who were monitored for a long period and had interventions were analyzed to identify useful parameters and develop algorithms to define alert rules. Twenty of the 36 participants had a clinical referral during the time of monitoring; 16 of them received some type of intervention. The most common reason for intervention was due to low oxygen levels for patients with COPD and high BP levels for CHF. Activity data were found to contain information on the well-being of patients, in particular for those with COPD. During exacerbation the activity level from PIR sensors increased slightly, and there was a decrease in bed occupancy. One subject with CHF who felt unwell spent most of the day in the bedroom. Conclusions: Our results suggest that integrated care monitoring technologies have a potential for providing improved care and can have positive impact on well-being of the elderly by enabling timely intervention. Long-term BP and pulse oximetry data could indicate exacerbation and lead to effective intervention; physical activity data provided important information on the well-being of patients. However, there remains a need for better understanding of long-term variations in vital signs and activity data to establish intervention protocols for improved disease management.en_US
dc.language.isoengen_US
dc.publisherMary Ann Liebert, Incen_US
dc.relation.isversionof10.1089/tmj.2017.0322en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectageingen_US
dc.subjectassistive technologyen_US
dc.subjectchronic diseaseen_US
dc.subjectdecision makingen_US
dc.subjecthabitsen_US
dc.subjectintegrated careen_US
dc.subjectpervasive careen_US
dc.subjecttelehealthen_US
dc.subjecte-healthen_US
dc.subjecttelecareen_US
dc.subjecttelemetryen_US
dc.subjectelderly careen_US
dc.subjectactivities of daily livingen_US
dc.subjectwell-beingen_US
dc.subjecttelemedicineen_US
dc.titleIntegrated Telehealth and Telecare for Monitoring Frail Elderly with Chronic Diseaseen_US
dc.typereviewen_US
dc.contributor.departmentOMÜen_US
dc.identifier.volume24en_US
dc.identifier.issue12en_US
dc.identifier.startpage940en_US
dc.identifier.endpage957en_US
dc.relation.journalTelemedicine and E-Healthen_US
dc.relation.publicationcategoryDiğeren_US


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