In the International Journal of Chronic Obstructive Pulmonary Disease Lonneke Boer and colleagues described the validity of an innovative software application that provides automated treatment advice to patients with COPD without the interference of a health care professional. This application was developed by the Department of Primary and Community Care in close collaboration with the departments of Pulmonary Diseases and Medical Psychology and the Institute of Computing Sciences of the Radboud University. In this publication, Lonneke and colleagues demonstrated that their application can safely be used in patients with COPD to support self-management in case of an exacerbation.Abstract
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 (SpO2), forced expiratory volume in one second (FEV1), 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.
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 SpO2, FEV1, 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.
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.
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.
Validation of ACCESS: an automated tool to support self-management of COPD exacerbations.
Boer LM, van der Heijden M, van Kuijk NM, Lucas PJ, Vercoulen JH, Assendelft WJ, Bischoff EW, Schermer TR.
Lonneke Boer is member of the theme: Inflammatory diseases.
Related news items
6 million euros to uncover link between metabolic and brain disorders21 January 2020
An important European-funded initiative, coordinated by Radboudumc researchers Barbara Franke, Jan Buitelaar, and Janita Bralten, has been launched to explore how common molecular mechanisms may link metabolic disorders with brain disorders.read more
NWO Open Competition Domain Science - XS grant for Ronald van Rij and Jenny van der Wijst21 January 2020
NWO Domain Science has awarded Ronald van Rij, theme Infectious diseases and global health and Jennny van der Wijst, theme Renal disorders an XS grant. The XS category emphatically strives to encourage curiosity-driven and bold research involving a relatively quick analysis of a promising idea.read more
RIMLS award ceremony proudly presenting the winners16 January 2020
Several RIMLS researchers received an award and bonus during the New Year's drinks. See all photo's and the ENABLE aftermovie.read more
The PRIDE Study Evaluation of online methods of data collection16 January 2020
In Paediatric and Perinatal Epidemiology RIHS researchers Marleen van Gelder and Nel Roeleveld described the recruitment methods and online data collection within the PRIDE Study, the largest Dutch birth cohort study.read more