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)

Background To understand what is needed to achieve a successful Danish home-based reablement service from the perspective of reablement professionals. Methods Semi-structured interviews and observations were conducted with nine professionals within a municipal visitation unit in the Northern Denmark Region. Thematic analysis was used to analyze the interviews. Results Four major themes emerged during this study: “Heterogeneity of clients and mixed attitudes towards the reablement intervention”, “Shared understanding and acknowledging the need for help as the first step in reablement”, “Commitment and motivation are essential for successful reablement”, and “Homecare helpers as most important team players”. The findings indicate that the clients had both mixed characteristics and attitudes about participating in the reablement intervention. Essential factors for successful reablement included a shared understanding of the reablement intervention, commitment, and motivation in terms of client involvement and staff group collaboration. Conclusions Shared understanding of the reablement intervention, commitment, and motivation was found to be essential factors and the driving forces in relation to successful reablement.

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The aim of the present study was to evaluate patient-related perspectives from a five-week test of the implementation of a COPD prediction algorithm. The test intended to discover and avoid potential errors prior to testing the COPD prediction algorithm in a two-armed randomized controlled trial (RCT). The COPD prediction algorithm aims to predict exacerbations in COPD based on home measurements. In the present study, the algorithm was implemented in a currently deployed telehealth system. Five weeks after implementation, six interviews were conducted, including five interviews with patients with COPD and one interview with a specialized COPD nurse. The participants were overall satisfied with the telehealth system including the COPD prediction algorithm. However, technical issues must be addressed before the COPD prediction algorithm is ready to be tested in the RCT. Moreover, communication with the monitoring nurses should be clearer based on the COPD nurse’s experiences. In conclusion, the participants were satisfied with the integration of the COPD prediction algorithm in the telehealth system. The identification of technical issues shows the importance of including a technical test period in a similar trial setup.