Abstract
Background: Prevention of lung attacks (LAs)/exacerbation is an important treatment goal in both asthma and chronic obstructive pulmonary disease (COPD). However, LAs are often not registered as such in medical records.Objectives: Development and evaluation of CodeX Asthma and COPD.Design: An electronic medical record-based algorithm to identify LAs in Dutch primary care patients with asthma or COPD was developed. The algorithms were evaluated in nine general practices in the Netherlands.Results: A total of 479 LAs (in 1164 patients) were identified with CodeX Asthma in the past year, of which only 16% were registered. CodeX COPD identified 321 LAs (in 242 patients) in the past 3?years, of which two were registered.Conclusion: CodeX algorithms are capable of identifying unrecorded LAs and high-risk/uncontrolled patients in an easy way. This offers primary care providers a simple solution to easily identify and closely manage high-risk patients with asthma or COPD by identifying LAs? frequency and potential under- or overtreatment.
Original language | English |
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Article number | 17534666251329192 |
Number of pages | 8 |
Journal | Therapeutic advances in respiratory disease |
Volume | 19 |
Early online date | 30 Apr 2025 |
DOIs | |
Publication status | E-pub ahead of print - 30 Apr 2025 |
Bibliographical note
We like to thank all participating general practitioners for using the CodeX Asthma or COPD report and sharing the data for research purposes. The following general practitioners participated: R.A. Riemersma, Appingedam; GP Practice Geulle (J. Muris), Geulle; Wind en van der Werf, Hoogezand; R. Boersma, Groningen; Veendokters, Barger-Compascuum; De Held (E. Visser), Groningen; T. Van Pelt, Meppel; de Noord-Ooster (D. Rezelman), Wagenborgen; het Kruispunt (A.F.M. Spreeuw), Vlaardingen.Also, we like to thank Topicus for their collaboration and support in the development of the CodeX reports.
Keywords
- algorithm
- asthma
- cardiopulmonary pathway
- COPD
- exacerbations
- lung attacks
- quality improvement
- treatment optimalization