Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
87 participants
INTERVENTIONAL
2015-06-30
2017-09-30
Brief Summary
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Detailed Description
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Recently, the Radboud University has developed the "Adaptive Computerized COPD Exacerbation Self-management Support" (ACCESS) system. This software application integrates objective parameters, such as spirometry, pulse-oximetry, temperature, and self-reported symptom worsening into a Bayesian network model resulting in a weighted exacerbation risk prediction. Patients are able to monitor themselves at any given moment. The ACCESS system not only predicts whether an exacerbation is imminent, but also provides ad hoc tailored advice without interference of a healthcare professional.
Objective: In this project the primary aim is to assess the (cost-)effectiveness of the ACCESS system in the support of exacerbation self-management in patients with COPD.
Study design: A multicenter, pragmatic, two-arm, randomized controlled trial with a follow-up of 12 months per participant.
Study population: Patients with COPD, \> 40 years old, with 2 or more self-reported symptom based exacerbations in the previous year.
Intervention: After a short self-management educational session on exacerbations, participants are randomized to either 1) exacerbation self-management support through the use of a paper exacerbation action plan (control group); or 2) exacerbation self-management support through the use of the ACCESS system (intervention group).
Participants in the intervention group are instructed to use ACCESS when they notice a change in COPD symptoms. Participants in the control group are instructed to use their paper action plan when they notice a change in COPD symptoms.
Main study parameters/endpoints:
Primary aim: to increase the number of exacerbation-free weeks. Secondary aims: to improve exacerbation self-management, exacerbation-management related self-efficacy, and quality of life. To decrease ER visits, hospital admissions and COPD related costs.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
SUPPORTIVE_CARE
NONE
Study Groups
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ACCESS
ACCESS is used when participants experience more COPD symptoms.
ACCESS
The ACCESS system consists of a smartphone, a pulse-oximeter, a spirometer and a forehead thermometer. Questions concerning changes in symptoms, physical limitations and emotions are answered by touch screen on the smartphone, complemented by measurements of the pulse-oximeter, spirometer and thermometer. Based on this information, the system calculates the current risk of an exacerbation and, when applicable, the participant will receive personalized instructions about which actions to take in order to manage the exacerbation. Participants are instructed to use ACCESS in case of symptom worsening.
paper plan
Paper exacerbation action plan is used when participants experience more COPD symptoms.
No interventions assigned to this group
Interventions
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ACCESS
The ACCESS system consists of a smartphone, a pulse-oximeter, a spirometer and a forehead thermometer. Questions concerning changes in symptoms, physical limitations and emotions are answered by touch screen on the smartphone, complemented by measurements of the pulse-oximeter, spirometer and thermometer. Based on this information, the system calculates the current risk of an exacerbation and, when applicable, the participant will receive personalized instructions about which actions to take in order to manage the exacerbation. Participants are instructed to use ACCESS in case of symptom worsening.
Eligibility Criteria
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Inclusion Criteria
* at least 2 self-reported exacerbations in the previous 12 months, i.e. a change for ≥ 2 consecutive days in either ≥ 2 major symptoms (dyspnea, sputum purulence, sputum amount) or any 1 major symptom plus any ≥ 1 minor symptoms (colds, wheeze, sore throat, cough).
Exclusion Criteria
* unable to communicate in the Dutch language;
* difficulties using a smartphone;
40 Years
ALL
No
Sponsors
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Radboud University Medical Center
OTHER
Responsible Party
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Principal Investigators
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Tjard Schermer, PhD
Role: PRINCIPAL_INVESTIGATOR
head of research unit
Locations
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Radboud University Medical Centre, Department of Primary and Community Care
Nijmegen, , Netherlands
Countries
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References
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van der Heijden M, Lucas PJ, Lijnse B, Heijdra YF, Schermer TR. An autonomous mobile system for the management of COPD. J Biomed Inform. 2013 Jun;46(3):458-69. doi: 10.1016/j.jbi.2013.03.003. Epub 2013 Mar 15.
Bischoff EW, Boer LM, Molema J, Akkermans R, van Weel C, Vercoulen JH, Schermer TR. Validity of an automated telephonic system to assess COPD exacerbation rates. Eur Respir J. 2012 May;39(5):1090-6. doi: 10.1183/09031936.00057811. Epub 2011 Sep 15.
Bischoff EW, Hamd DH, Sedeno M, Benedetti A, Schermer TR, Bernard S, Maltais F, Bourbeau J. Effects of written action plan adherence on COPD exacerbation recovery. Thorax. 2011 Jan;66(1):26-31. doi: 10.1136/thx.2009.127621. Epub 2010 Oct 30.
van der Heijden M, Velikova M, Lucas PJ. Learning Bayesian networks for clinical time series analysis. J Biomed Inform. 2014 Apr;48:94-105. doi: 10.1016/j.jbi.2013.12.007. Epub 2013 Dec 18.
van der Heijden M, Lucas PJ. Describing disease processes using a probabilistic logic of qualitative time. Artif Intell Med. 2013 Nov;59(3):143-55. doi: 10.1016/j.artmed.2013.09.003. Epub 2013 Oct 7.
Boer L, Bischoff E, van der Heijden M, Lucas P, Akkermans R, Vercoulen J, Heijdra Y, Assendelft W, Schermer T. A Smart Mobile Health Tool Versus a Paper Action Plan to Support Self-Management of Chronic Obstructive Pulmonary Disease Exacerbations: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2019 Oct 9;7(10):e14408. doi: 10.2196/14408.
Liu M, Stella F, Hommersom A, Lucas PJF, Boer L, Bischoff E. A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity. Artif Intell Med. 2019 Apr;95:104-117. doi: 10.1016/j.artmed.2018.10.002. Epub 2019 Jan 22.
Other Identifiers
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NL49741 .091.14
Identifier Type: -
Identifier Source: org_study_id
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