Exacerbation Self-management in COPD: The ACCESS Study
ACCESS
Adaptive Computerized COPD Exacerbation Self-management Support (ACCESS): A Randomized Controlled Trial
1 other identifier
interventional
87
1 country
1
Brief Summary
Aim is to test the effect of ACCESS ("Adaptive Computerized COPD Exacerbation Self-management Support"), a software application designed to support patients with COPD in self-management of exacerbations.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for not_applicable
Started Jun 2015
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
June 1, 2015
CompletedFirst Submitted
Initial submission to the registry
August 5, 2015
CompletedFirst Posted
Study publicly available on registry
September 17, 2015
CompletedPrimary Completion
Last participant's last visit for primary outcome
August 1, 2017
CompletedStudy Completion
Last participant's last visit for all outcomes
September 1, 2017
CompletedAugust 30, 2017
August 1, 2017
2.2 years
August 5, 2015
August 29, 2017
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Number of exacerbation-free weeks
Measured with the Telephonic EXacerbation Assessment System (TEXAS) \[Bischoff, ERJ, 2012\]
1 year
Secondary Outcomes (7)
Improvement in exacerbation-related self-management behaviour
1 year
Improvement in Quality of Life
1 year
Improvement in Quality of Life
1 year
Improvement in Quality of Life
1 year
Improvement in self-efficacy
1 year
- +2 more secondary outcomes
Study Arms (2)
ACCESS
EXPERIMENTALACCESS is used when participants experience more COPD symptoms.
paper plan
NO INTERVENTIONPaper exacerbation action plan is used when participants experience more COPD symptoms.
Interventions
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
You may qualify if:
- confirmed diagnosis of COPD by spirometry (post-bronchodilator FEV1/FVC \< 0.70);
- 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).
You may not qualify if:
- severe co-morbid conditions that prohibit participation;
- unable to communicate in the Dutch language;
- difficulties using a smartphone;
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Radboud University Medical Centre, Department of Primary and Community Care
Nijmegen, 6500 HB, Netherlands
Related Publications (7)
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.
PMID: 23500485BACKGROUNDBischoff 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.
PMID: 21920893BACKGROUNDBischoff 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.
PMID: 21037270BACKGROUNDvan 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.
PMID: 24361389BACKGROUNDvan 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.
PMID: 24183893BACKGROUNDBoer 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.
PMID: 31599729DERIVEDLiu 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.
PMID: 30683464DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Tjard Schermer, PhD
head of research unit
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- SUPPORTIVE CARE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
August 5, 2015
First Posted
September 17, 2015
Study Start
June 1, 2015
Primary Completion
August 1, 2017
Study Completion
September 1, 2017
Last Updated
August 30, 2017
Record last verified: 2017-08