Academic Journal
Development of data processing algorithm to calculate adherence for adults with cystic fibrosis using inhaled therapy - a multi-center observational study within the CFHealthHub learning health system
| العنوان: | Development of data processing algorithm to calculate adherence for adults with cystic fibrosis using inhaled therapy - a multi-center observational study within the CFHealthHub learning health system |
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| المؤلفون: | Sandler, R.D., Lai, L., Dawson, S., Cameron, S., Lynam, A., Sperrin, M., Wildman, M.J., Hoo, Z.H. |
| بيانات النشر: | Taylor and Francis |
| سنة النشر: | 2024 |
| المجموعة: | White Rose Research Online (Universities of Leeds, Sheffield & York) |
| الوصف: | Objectives To develop a robust algorithm to accurately calculate ‘daily complete dose counts’ for inhaled medicines, used in percent adherence calculations, from electronically-captured nebulizer data within the CFHealthHub Learning Health System. Methods A multi-center, cross-sectional study involved participants and clinicians reviewing real-world inhaled medicine usage records and triangulating them with objective nebulizer data to establish a consensus on ‘daily complete dose counts.’ An algorithm, which used only objective nebulizer data, was then developed using a derivation dataset and evaluated using internal validation dataset. The agreement and accuracy between the algorithm-derived and consensus-derived ‘daily complete dose counts’ was examined, with the consensus-derived count as the reference standard. Results Twelve people with CF participated. The algorithm derived a ‘daily complete dose count’ by screening out ‘invalid’ doses (those <60s in duration or run in cleaning mode), combining all doses starting within 120s of each other, and then screening out all doses with duration < 480s which were interrupted by power supply failure. The kappa co-efficient was 0.85 (0.71–0.91) in the derivation and 0.86 (0.77–0.94) in the validation dataset. Conclusions The algorithm demonstrated strong agreement with the participant-clinician consensus, enhancing confidence in CFHealthHub data. Publishingdata processing methods can encourage trust in digital endpoints and serve as an exemplar for other projects. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | text |
| اللغة: | English |
| Relation: | https://eprints.whiterose.ac.uk/210206/1/%21%20submitted.pdf; Sandler, R.D., Lai, L., Dawson, S. et al. (5 more authors) (2024) Development of data processing algorithm to calculate adherence for adults with cystic fibrosis using inhaled therapy - a multi-center observational study within the CFHealthHub learning health system. Expert Review of Pharmacoeconomics & Outcomes Research, 24 (6). pp. 759-771. ISSN 1473-7167 |
| الاتاحة: | https://eprints.whiterose.ac.uk/210206/ https://eprints.whiterose.ac.uk/210206/1/%21%20submitted.pdf |
| Rights: | cc_by_4 |
| رقم الانضمام: | edsbas.7571B8A9 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |