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dc.contributor.authorKargiannakis, M.*
dc.contributor.authorFitzsimmons, D.A.*
dc.contributor.authorBentley, C.L.*
dc.contributor.authorMountain, Gail*
dc.date.accessioned2017-05-08T15:55:23Z
dc.date.available2017-05-08T15:55:23Z
dc.date.issued2017-03-22
dc.identifier.citationKargiannakis M, Fitzsimmons DA, Bentley CL et al (2017) Does telehealth monitoring identify exacerbations of chronic pulmonary disease and reduce hospitalisations? An analysis of systems data. JMIR Medical Informatics. 5(1).en_US
dc.identifier.urihttp://hdl.handle.net/10454/11920
dc.descriptionYesen_US
dc.description.abstractBackground: The increasing prevalence and associated cost of treating chronic obstructive pulmonary disease (COPD) is unsustainable. Health care organizations are focusing on ways to support self-management and prevent hospital admissions, including telehealth-monitoring services capturing physiological and health status data. This paper reports on data captured during a pilot randomized controlled trial of telehealth-supported care within a community-based service for patients discharged from hospital following an exacerbation of their COPD. Objective: The aim was to undertake the first analysis of system data to determine whether telehealth monitoring can identify an exacerbation of COPD, providing clinicians with an opportunity to intervene with timely treatment and prevent hospital readmission. Methods: A total of 23 participants received a telehealth-supported intervention. This paper reports on the analysis of data from a telehealth monitoring system that captured data from two sources: (1) data uploaded both manually and using Bluetooth peripheral devices by the 23 participants and (2) clinical records entered as nursing notes by the clinicians. Rules embedded in the telehealth monitoring system triggered system alerts to be reviewed by remote clinicians who determined whether clinical intervention was required. We also analyzed data on the frequency and length (bed days) of hospital admissions, frequency of hospital Accident and Emergency visits that did not lead to hospital admission, and frequency and type of community health care service contacts—other than the COPD discharge service—for all participants for the duration of the intervention and 6 months postintervention. Results: Patients generated 512 alerts, 451 of which occurred during the first 42 days that all participants used the equipment. Patients generated fewer alerts over time with typically seven alerts per day within the first 10 days and four alerts per day thereafter. They also had three times more days without alerts than with alerts. Alerts were most commonly triggered by reports of being more tired, having difficulty with self-care, and blood pressure being out of range. During the 8-week intervention, and for 6-month follow-up, eight of the 23 patients were hospitalized. Hospital readmission rates (2/23, 9%) in the first 28 days of service were lower than the 20% UK norm. Conclusions: It seems that the clinical team can identify exacerbations based on both an increase in alerts and the types of system-generated alerts as evidenced by their efforts to provided treatment interventions. There was some indication that telehealth monitoring potentially delayed hospitalizations until after patients had been discharged from the service. We suggest that telehealth-supported care can fulfill an important role in enabling patients with COPD to better manage their condition and remain out of hospital, but adequate resourcing and timely response to alerts is a critical factor in supporting patients to remain at home.en_US
dc.description.sponsorshipThis project was funded by the National Institute for Health Collaboration for Leadership in Applied Health Research and Care Yorkshire and Humber (CLAHRC YH).en_US
dc.language.isoenen_US
dc.rights© Melissa Kargiannakis, Deborah A Fitzsimmons, Claire L Bentley, Gail A Mountain. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 22.03.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.en_US
dc.subjectInformation systems; Telemedicine; Pulmonary disease; Chronic obstructive; Triggers and rules; Information integration; Decision support systems; Information retrievalen_US
dc.titleDoes telehealth monitoring identify exacerbations of chronic pulmonary disease and reduce hospitalisations? An analysis of systems dataen_US
dc.status.refereedYesen_US
dc.date.Accepted2017-02-03
dc.date.application2017-03-22
dc.typeArticleen_US
dc.type.versionPublished versionen_US
dc.identifier.doihttps://doi.org/10.2196/medinform.6359
refterms.dateFOA2018-07-26T09:28:49Z


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