ArticlemedRxiv : the preprint server for health sciences2025
Impact of the COVID-19 Pandemic on Adult Asthma-Related Healthcare Utilization.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Updated by
Authors and funding
9 authors.
Funding
Abstract
backgroundThe COVID-19 pandemic prompted unprecedented changes to chronic disease self-management and healthcare systems worldwide, including shifts in access to services and medications. While children with asthma had decreased exacerbations and healthcare encounters during 2020, the impact of lockdowns on adults with asthma, who faced different challenges during the pandemic than children, are less understood.
objectiveWe sought to characterize changes in adult asthma-related healthcare utilization during the COVID-19 pandemic in 2020 versus prior (2017-2019) and subsequent (2021-2024) years by leveraging electronic health record (EHR) data from a large, multi-hospital health system in a major US city.
methodsWe conducted a retrospective EHR database study of 42,242 adults with asthma who received care at Penn Medicine from 2017 to 2024. We analyzed weekly encounter counts across five encounter types (refill, telemedicine, telephone/audio, outpatient, emergency encounters) and prescriptions for short-acting beta agonists (SABA), inhaled corticosteroids (ICS), and oral corticosteroids (OCS). Generalized linear models assessed changes in asthma-related encounter rate in pandemic (2020) and post-pandemic (2021-2024) periods relative to pre-pandemic (2017-2019). We stratified on weekly intervals that captured transitional timepoints in healthcare utilization in 2020 (Weeks 1-8, 9-18, and 19-52).
resultsIn 2017-2019, there were on average 397 weekly visits for asthma at Penn Medicine; in 2020, the weekly average increased to 481. This change was driven primarily by a surge during the lockdown weeks in refill and telemedicine encounters by 123% and 36,445%, respectively and by a decrease in outpatient visits by 65%. During the lockdown weeks in 2020, asthma related prescriptions of SABA and ICS prescriptions increased 73% and 43%, respectively, compared to pre-pandemic years, while OCS prescriptions decreased by 5%. White patients showed earlier healthcare-seeking responses than other racial groups. Changes persisted in post-pandemic years as the average of weekly asthma-related visits was 445 in 2021-2024. Telemedicine remained 38-76 times higher than pre-pandemic baseline, refills doubled compared to 2017-2019 levels, and outpatient visits remained 35-43% below pre-pandemic levels.
conclusionCOVID-19 transformed adult asthma care delivery and led to sustained increases in virtual care and medication refills potentially due to virtual care compensating for reductions in traditional outpatient encounters.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.