Clinical implementation of an algorithm for predicting exacerbations in patients with COPD in telemonitoring: a study protocol for a single-blinded randomized controlled trial

Pernille Heyckendorff Secher, Stine Hangaard, Thomas Kronborg, Lisa Korsbakke Emtekær Hæsum, Flemming Witt Udsen, Ole Hejlesen, Clara Bender, Pernille Heyckendorff Secher, Stine Hangaard, Thomas Kronborg, Lisa Korsbakke Emtekær Hæsum, Flemming Witt Udsen, Ole Hejlesen, Clara Bender

Abstract

Background: Acute exacerbations have a significant impact on patients with COPD by accelerating the decline in lung function leading to decreased health-related quality of life and survival time. In telehealth, health care professionals exercise clinical judgment over a physical distance. Telehealth has been implemented as a way to monitor patients more closely in daily life with an intention to intervene earlier when physical measurements indicate that health deteriorates. Several studies call for research investigating the ability of telehealth to automatically flag risk of exacerbations by applying the physical measurements that are collected as part of the monitoring routines to support health care professionals. However, more research is needed to further develop, test, and validate prediction algorithms to ensure that these algorithms improve outcomes before they are widely implemented in practice.

Method: This trial tests a COPD prediction algorithm that is integrated into an existing telehealth system, which has been developed from the previous Danish large-scale trial, TeleCare North (NCT: 01984840). The COPD prediction algorithm aims to support clinical decisions by predicting the risk of exacerbations for patients with COPD based on selected physiological parameters. A prospective, parallel two-armed randomized controlled trial with approximately 200 participants with COPD will be conducted. The participants live in Aalborg municipality, which is located in the North Denmark Region. All participants are familiar with the telehealth system in advance. In addition to the participants' usual weekly monitored measurements, they are asked to measure their oxygen saturation two more times a week during the trial period. The primary outcome is the number of exacerbations defined as an acute hospitalization from baseline to follow-up. Secondary outcomes include changes in health-related quality of life measured by both the 12-Item Short Form Survey version 2 and EuroQol-5 Dimension Questionnaire as well as the incremental cost-effectiveness ratio.

Discussion: This trial seeks to explore whether the COPD prediction algorithm has the potential to support early detection of exacerbations in a telehealth setting. The COPD prediction algorithm may initiate timely treatment, which may decrease the number of hospitalizations.

Trial registration: NCT05218525 (pending at clinicaltrials.gov ) (date, month, year).

Keywords: Chronic obstructive pulmonary disease; Clinical decision support systems; Disease exacerbation; Forecasting; Health literacy; Machine learning; Physiological monitoring; Randomized controlled trial; Telemedicine.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
The telehealth system, Telekit, consists of a tablet, a fingertip pulse oximeter, a blood pressure monitor, and a scale
Fig. 2
Fig. 2
The trial procedure from identification and recruitment to outcome assessments at 6 months

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