Doorgaan naar hoofdnavigatie Doorgaan naar zoeken Ga verder naar hoofdinhoud

Toward Patient-Centric Digital Monitoring of Obstructive Sleep Apnea: Mixed Methods Study

  • James Kenneth Timmis
  • , Kerstin Alexandra Schorr
  • , Rana Yüksel
  • , Tim van den Broek
  • , Sebastiaan Overeem
  • , Dagmar Josine Smid
  • , Willem Johan van den Brink
  • , Nina Leonie Haring (Corresponding author)

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

15 Downloads (Pure)

Samenvatting

BACKGROUND: Obstructive sleep apnea (OSA) is a sleep disorder characterized by repeated breathing disruptions during sleep. Remote patient monitoring (RPM) of OSA is important, yet contemporary methods are limited. Sensor-based digital health technologies (sDHTs) promise a step advance in OSA RPM, but must provide meaningful, actionable, and usable outputs for patients. While the centrality of considering patient views in sDHT development is widely acknowledged, patient perspectives and priorities are rarely assessed.

OBJECTIVE: This study aimed to identify patient-prioritized health aspects and preferences for digital measures and RPM to enhance OSA care quality and patient experience, guided by the digital measures that matter framework.

METHODS: We used a mixed methods design combining quantitative and qualitative approaches. Individuals with a formal OSA diagnosis and persistent sleep problems (n=223) completed a survey in which they ranked items related to treatment burdens and health priorities, and responded to open-ended questions about restoring previous quality-of-life elements and desired health goals. To gain deeper qualitative insights, we conducted semistructured interviews with patients with OSA, patient advocates, and health care professionals (n=11), focusing on follow-up care, attitudes toward sDHTs and RPM, and preferences for future OSA-related sDHTs and metrics. Quantitative data were analyzed using bootstrap-aggregated Borda counts (broad support) and Plackett-Luce modeling (intense prioritization), while qualitative data from surveys and interviews were analyzed thematically.

RESULTS: Key meaningful aspects of health included the improvement of subjective sleep quality (top-ranked burden; health goal for 46.5%, 93/200 of participants), an increase in daytime energy (quality-of-life aspect to restore for 35.6%, 72/202 and health goal for 25.5%, 51/200 of participants), and physical activity (quality-of-life aspect to restore for 24.7%, 50/202 and health goal for 16.5%, 33/200 of participants). Sleep characteristics and daytime energy were priority targets for digital measure development. Smartwatches, sleep mats, and smart rings were preferred modalities for integration into RPM. Participants' priorities for enhancing monitoring included (1) expanding metrics beyond the Apnea-Hypopnea Index (AHI; 36.6%, 52/142), (2) improving measurement accuracy (20.4%, 29/142), and (3) ensuring outputs are meaningful, understandable (18.3%, 26/142), and actionable (9.2%, 13/142). Patients also reported difficulty interpreting RPM data to determine if and when follow-up care is needed and what type of care is appropriate.

CONCLUSIONS: RPM solutions for OSA should expand beyond AHI, ensure accuracy and interpretability, and provide actionable insights to support comprehensive patient-centric management.

Originele taal-2Engels
Artikelnummere82460
Aantal pagina's16
TijdschriftJournal of Medical Internet Research
Volume28
Vroegere onlinedatum15 aug. 2025
DOI's
StatusGepubliceerd - 8 jan. 2026

Bibliografische nota

©James Kenneth Timmis, Kerstin Alexandra Schorr, Rana Yüksel, Tim van den Broek, Sebastiaan Overeem, Dagmar Josine Smid, Willem Johan van den Brink, Nina Leonie Haring. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.01.2026.

Financiering

This research was supported by internal funding from the Netherlands Organization for Applied Scientific Research (TNO). The article processing fee was covered by TNO’s internal funds. No external grants or commercial funding were received for this work. The authors would like to thank Marian Schoone, Suzan Wopereis, Hardy van der Ven, Koen Hogenelst, Elsbeth de Korte, and André Boorsma for their valuable contributions and insightful discussions, which greatly supported the development of this work. Portions of the text were revised with the assistance of the generative AI language model ChatGPT (GPT-5; OpenAI), and all content was subsequently reviewed and approved by the authors. This research was supported by internal funding from the Netherlands Organization for Applied Scientific Research (TNO). The article processing fee was covered by TNO’s internal funds. No external grants or commercial funding were received for this work.

Vingerafdruk

Duik in de onderzoeksthema's van 'Toward Patient-Centric Digital Monitoring of Obstructive Sleep Apnea: Mixed Methods Study'. Samen vormen ze een unieke vingerafdruk.

Citeer dit