Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 13 min ago
Peer-reviewedCC BY-NC-ND 4.0NPJ Primary Care Respiratory Medicine

Digital inhaler data in routine asthma care: defining a minimal dataset for clinical decision support (AURORA): a modified delphi study

  • Mechteld B. R. Wiertz1,2
  • Amber A. Eikholt2,3
  • Anneke ten Brinke4
  • Els J. M. Weersink5
  • Irene van der Weerdt6
  • Johannes C. C. M. in ’t Veen7,8
  • Kornelis W. Patberg1
  • Martijn Goosens9
  • Niels H. Chavannes10
  • Sandra Been-Buck11
  • Titia Klemmeier11
  • Huib A. M. Kerstjens3,12
1 more authors
  • Job F. M. van Boven2,3,13
13 affiliations
  1. 1Isala Medical Centre, Department of Pulmonology, Zwolle, The Netherlands
  2. 2University of Groningen, University Medical Centre Groningen, Department of Clinical Pharmacy & Pharmacology, Groningen, The Netherlands
  3. 3Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands
  4. 4Frisius Medical Centre, Department of Pulmonology, Leeuwarden, The Netherlands
  5. 5Amsterdam University Medical Centre, Department of Pulmonology, Amsterdam, the Netherlands
  6. 6COPD and asthma general practitioners advise group (CAHAG), Utrecht, the Netherlands
  7. 7Franciscus Hospital, Centre of Excellence for Asthma and COPD, Rotterdam, the Netherlands
  8. 8Erasmus MC, Department of Pulmonology, Rotterdam, the Netherlands
  9. 9Gelre Hospital, Department of Pulmonology, Apeldoorn, the Netherlands
  10. 10Leiden University Medical Centre, Department of Public Health and Primary Care Medicine, National eHealth Living Lab, Leiden, the Netherlands
  11. 11Department of Pulmonology, Martini Hospital, Groningen, the Netherlands
  12. 12University of Groningen, University Medical Center Groningen, Department of Pulmonology and Tuberculosis, Groningen, the Netherlands
  13. 13Medication Adherence Expertise Centre of the northern Netherlands (MAECON), Groningen, The Netherlands
Read full textPDFDOICite

Abstract

Digital inhalers can assess and support medication adherence and inhalation technique and may predict exacerbations, yet real-world evidence on their use, implementation, and clinical impact remains limited. To date, no standardized registry exists to systematically capture digital inhaler use across the full spectrum of asthma severity. To reach an expert consensus on a minimal and feasible dataset for a registry (AURORA) of asthma patients using digital inhalers. A three-round modified Delphi process was conducted involving 15 Dutch experts in asthma care, medication adherence, digital health, regulatory science, and healthcare policy. In Rounds 1 and 2, candidate variables were evaluated via an online Delphi platform, with predefined consensus thresholds for inclusion and exclusion. Patient perspectives were incorporated through structured interviews. Final consensus was achieved during an online meeting in Round 3 (≥66% agreement required). Of 92 variables considered, 18 were classified as core and 45 as optional. Core variables covered key domains, including patient demographics, asthma control, medication type, digital inhaler characteristics, medication adherence, inhaler technique, and patient satisfaction. Optional variables provide flexibility to support implementation across different healthcare settings. This modified Delphi study established a consensus-based national registry framework specifically focused on digital inhaler use in asthma. The AURORA registry provides a standardized and feasible foundation for generating real-world evidence to support future research, personalized treatment decisions, and the optimization of escalation strategies in routine asthma care.

Related

  1. Defining the clinical benefits of disease-modifying therapy in people living with spinal muscular atrophy who require permanent ventilation: a UK-based modified Delphi consensus process
    Mariacristina Scoto, Chiara Marini-Bettolo, Elaine Chan +17
    eClinicalMedicinePeer-reviewedCC BY-NC-ND 4.0Full textHuman geneticsCrossrefDOAJEurope PMCPMC
  2. An assisted telemedicine model with digital diagnostics and artificial intelligence-supported clinical decision in hard-to-reach rural communities: a community-based mixed-methods study from Rajasthan, India
    Preventive medicine reportsPeer-reviewedCC BY-NC-NDFull textGeneral medicineEurope PMC
  3. Measuring what matters- patient and clinician priorities for clinical decision support interactions: a modified Delphi study.
    Rachel Kurtzman, Mustafa Ozkaynak, Frances Jimenez +5
    BMC medical informatics and decision makingPeer-reviewedCC BY-NC-NDFull textGeneral medicineEurope PMCDOAJ
  4. Community health workers experiences with a digital clinical decision support system for longitudinal hypertension and diabetes care in rural Lesotho: a mixed-methods study
    F. Gerber, F. Raeber, M. Moruthoane +22
    medRxivPreprintCC BYFull textGeneral medicinemedRxiv
  5. Digital twin technology in cardiovascular care: future perspectives for nursing practice, patient management, and clinical decision-making
    Naseema Shafqat, Veena Verma, Saman Naseema
    Frontiers in Cardiovascular MedicinePeer-reviewedCC BY 4.0Full textEpidemiology & public healthCrossref

Cite

BibTeXRIS
BibTeX
@article{wiertz2026digital,
  title = {{Digital inhaler data in routine asthma care: defining a minimal dataset for clinical decision support (AURORA): a modified delphi study}},
  author = {Mechteld B. R. Wiertz and Amber A. Eikholt and Anneke ten Brinke and Els J. M. Weersink and Irene van der Weerdt and Johannes C. C. M. in ’t Veen and Kornelis W. Patberg and Martijn Goosens and Niels H. Chavannes and Sandra Been-Buck and Titia Klemmeier and Huib A. M. Kerstjens and Job F. M. van Boven},
  journal = {NPJ Primary Care Respiratory Medicine},
  year = {2026},
  month = jul,
  doi = {10.1038/s41533-026-00536-z},
  url = {https://doi.org/10.1038/s41533-026-00536-z},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Digital inhaler data in routine asthma care: defining a minimal dataset for clinical decision support (AURORA): a modified delphi study
AU  - Mechteld B. R. Wiertz
AU  - Amber A. Eikholt
AU  - Anneke ten Brinke
AU  - Els J. M. Weersink
AU  - Irene van der Weerdt
AU  - Johannes C. C. M. in ’t Veen
AU  - Kornelis W. Patberg
AU  - Martijn Goosens
AU  - Niels H. Chavannes
AU  - Sandra Been-Buck
AU  - Titia Klemmeier
AU  - Huib A. M. Kerstjens
AU  - Job F. M. van Boven
PY  - 2026
DA  - 2026/07/03
JO  - NPJ Primary Care Respiratory Medicine
DO  - 10.1038/s41533-026-00536-z
UR  - https://doi.org/10.1038/s41533-026-00536-z
AB  - Digital inhalers can assess and support medication adherence and inhalation technique and may predict exacerbations, yet real-world evidence on their use, implementation, and clinical impact remains limited. To date, no standardized registry exists to systematically capture digital inhaler use across the full spectrum of asthma severity. To reach an expert consensus on a minimal and feasible dataset for a registry (AURORA) of asthma patients using digital inhalers. A three-round modified Delphi process was conducted involving 15 Dutch experts in asthma care, medication adherence, digital health, regulatory science, and healthcare policy. In Rounds 1 and 2, candidate variables were evaluated via an online Delphi platform, with predefined consensus thresholds for inclusion and exclusion. Patient perspectives were incorporated through structured interviews. Final consensus was achieved during an online meeting in Round 3 (≥66% agreement required). Of 92 variables considered, 18 were classified as core and 45 as optional. Core variables covered key domains, including patient demographics, asthma control, medication type, digital inhaler characteristics, medication adherence, inhaler technique, and patient satisfaction. Optional variables provide flexibility to support implementation across different healthcare settings. This modified Delphi study established a consensus-based national registry framework specifically focused on digital inhaler use in asthma. The AURORA registry provides a standardized and feasible foundation for generating real-world evidence to support future research, personalized treatment decisions, and the optimization of escalation strategies in routine asthma care.
SN  - 2055-1010
ER  -