ArticleBJGP open2025
Inhaled corticosteroids for COVID-19: a real-world data analysis on guideline adherence.
Article in BJGP open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe recommendation to consider prescribing inhaled corticosteroids (ICSs) to a subgroup of vulnerable patients with COVID-19 was added to the Dutch medical guideline on 2 November 2021, and was also adopted by other countries during the pandemic.
aimTo evaluate the adherence of GPs to this guideline, and whether the quality of real-world data is sufficient to study the effect of revised guidelines on prescribing behaviour. DESIGN &
settingA retrospective cohort study using Dutch primary care data from the Extramural Leiden University Medical Center (LUMC) Academic Network database, containing patient data of 129 general practices in the Leiden - The Hague area.
methodWe performed an interrupted time series analysis to measure the effect of the new recommendation on the prescription rate of ICSs, accounting for general trends and seasonal fluctuations.
resultsBetween 1 July 2020 and 1 August 2022, 131 482 patients had 164 098 COVID-19 consultations. During this period, 1709 patients received 2094 ICS prescriptions for COVID-19. After the guideline update, there was an instantaneous decrease in prescription rate (incidence risk ratio [IRR] 0.47, 95% confidence intervals [CI] = 0.32 to 0.69). Prescription rate in the subgroup of vulnerable patients did not change significantly (IRR 0.93, 95% CI = 0.66 to 1.32), while less vulnerable patients were prescribed significantly fewer ICSs (IRR 0.29, 95% CI = 0.14 to 0.59).
conclusionThe revision to the COVID-19 guideline had significant impact on GPs' prescribing behaviour soon after publication: prescription rate remained constant for vulnerable patients, while less vulnerable patiens received ICS prescriptions significantly less often. Using electronic health records it is feasible to assess changes in guideline adherence using interrupted time series.
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