TY - JOUR
T1 - Validation of ACCESS
T2 - An automated tool to support self-management of COPD exacerbations
AU - Boer, Lonneke M.
AU - van der Heijden, Maarten
AU - van Kuijk, Nathalie M.E.
AU - Lucas, Peter J.F.
AU - Vercoulen, Jan H.
AU - Assendelft, Willem J.J.
AU - Bischoff, Erik W.
AU - Schermer, Tjard R.
N1 - Funding Information:
We would like to thank all patients who participated in this study for their commitment to the study, as well as all team members, especially Marleen Kolenbrander and Samantha van der Hoogen, the nurses, pulmonary nurses, and pulmonologists, of the rehabilitation department of Dekkerswald, and Heleen van der Niet and Netty Plat, pulmonary nurses of the outpatient clinic of the Radboudumc. Furthermore, we would like to thank Jeanine Antons, MD, for her contribution to the design of the present study, and Professor Yvonne Heijdra, MD, Dr Johan Molema, MD, and all the health care professionals of the expert panel for their contribution to the development of ACCESS. This study was funded by the Netherlands Organization for Health Research and Development, Boehringer Ingelheim, and the Radboud University Medical Center. None of the funding bodies had any role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
Publisher Copyright:
© 2018 Boer et al.
PY - 2018
Y1 - 2018
N2 - Background: To support patients with COPD in their self-management of symptom worsening, we developed Adaptive Computerized COPD Exacerbation Self-management Support (ACCESS), an innovative software application that provides automated treatment advice without the interference of a health care professional. Exacerbation detection is based on 12 symptom-related yes-or-no questions and the measurement of peripheral capillary oxygen saturation (SpO 2 ), forced expiratory volume in one second (FEV 1 ), and body temperature. Automated treatment advice is based on a decision model built by clinical expert panel opinion and Bayesian network modeling. The current paper describes the validity of ACCESS. Methods: We performed secondary analyses on data from a 3-month prospective observational study in which patients with COPD registered respiratory symptoms daily on diary cards and measured SpO 2 , FEV 1 , and body temperature. We examined the validity of the most important treatment advice of ACCESS, ie, to contact the health care professional, against symptom- and event-based exacerbations. Results: Fifty-four patients completed 2,928 diary cards. One or more of the different pieces of ACCESS advice were provided in 71.7% of all cases. We identified 115 symptom-based exacerbations. Cross-tabulation showed a sensitivity of 97.4% (95% CI 92.0-99.3), specificity of 65.6% (95% CI 63.5-67.6), and positive and negative predictive value of 13.4% (95% CI 11.2-15.9) and 99.8% (95% CI 99.3-99.9), respectively, for ACCESS’ advice to contact a health care professional in case of an exacerbation. Conclusion: In many cases (71.7%), ACCESS gave at least one self-management advice to lower symptom burden, showing that ACCES provides self-management support for both day-to-day symptom variations and exacerbations. High sensitivity shows that if there is an exacerbation, ACCESS will advise patients to contact a health care professional. The high negative predictive value leads us to conclude that when ACCES does not provide the advice to contact a health care professional, the risk of an exacerbation is very low. Thus, ACCESS can safely be used in patients with COPD to support self-management in case of an exacerbation.
AB - Background: To support patients with COPD in their self-management of symptom worsening, we developed Adaptive Computerized COPD Exacerbation Self-management Support (ACCESS), an innovative software application that provides automated treatment advice without the interference of a health care professional. Exacerbation detection is based on 12 symptom-related yes-or-no questions and the measurement of peripheral capillary oxygen saturation (SpO 2 ), forced expiratory volume in one second (FEV 1 ), and body temperature. Automated treatment advice is based on a decision model built by clinical expert panel opinion and Bayesian network modeling. The current paper describes the validity of ACCESS. Methods: We performed secondary analyses on data from a 3-month prospective observational study in which patients with COPD registered respiratory symptoms daily on diary cards and measured SpO 2 , FEV 1 , and body temperature. We examined the validity of the most important treatment advice of ACCESS, ie, to contact the health care professional, against symptom- and event-based exacerbations. Results: Fifty-four patients completed 2,928 diary cards. One or more of the different pieces of ACCESS advice were provided in 71.7% of all cases. We identified 115 symptom-based exacerbations. Cross-tabulation showed a sensitivity of 97.4% (95% CI 92.0-99.3), specificity of 65.6% (95% CI 63.5-67.6), and positive and negative predictive value of 13.4% (95% CI 11.2-15.9) and 99.8% (95% CI 99.3-99.9), respectively, for ACCESS’ advice to contact a health care professional in case of an exacerbation. Conclusion: In many cases (71.7%), ACCESS gave at least one self-management advice to lower symptom burden, showing that ACCES provides self-management support for both day-to-day symptom variations and exacerbations. High sensitivity shows that if there is an exacerbation, ACCESS will advise patients to contact a health care professional. The high negative predictive value leads us to conclude that when ACCES does not provide the advice to contact a health care professional, the risk of an exacerbation is very low. Thus, ACCESS can safely be used in patients with COPD to support self-management in case of an exacerbation.
KW - Automated device
KW - COPD
KW - Diagnostic accuracy
KW - Exacerbations
KW - Health
KW - Mobile health
KW - Self-management
KW - Software application
KW - Telehealth
KW - Treatment advice
UR - http://www.scopus.com/inward/record.url?scp=85055155126&partnerID=8YFLogxK
U2 - 10.2147/COPD.S167272
DO - 10.2147/COPD.S167272
M3 - Article
C2 - 30349231
SN - 1176-9106
VL - 13
SP - 3255
EP - 3267
JO - International journal of chronic obstructive pulmonary disease
JF - International journal of chronic obstructive pulmonary disease
ER -