PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 20, 2026American Journal of Respiratory and Critical Care Medicine0 citations

A105-12 Demographic and Insurance Status Predict Guideline Directed Asthma Care After Exacerbation

View Full Paper
AHA B HolleyHBH B BhideANA K Nofal

Key Points

  • This analysis aims to identify demographic and insurance-related predictors influencing proper asthma care after an exacerbation.
  • Retrospective analysis using a health system claims database covering demographics and clinical encounters.
  • Examined 314,162 asthma encounters from 2015 to 2024, focusing on lab orders and specialist referrals.
  • Employed logistic regression modeling to assess predictor variables.
  • Older age increases the odds of having eosinophil counts and IgE levels ordered (OR 1.055 and OR 1.012 respectively, p < 0.01).
  • Insured patients were more likely to have eos drawn (OR 1.51) and receive specialty referrals (OR 2.75, p < 0.01).
  • Non-white patients were less likely to have laboratory tests ordered (OR 0.60 for eos and OR 0.64 for IgE, p < 0.01).

Abstract

Abstract Introduction Asthma is the most common respiratory disorder in the United States, with a population prevalence of 7.7%. Asthma exacerbations are associated with considerable cost, morbidity, and mortality. Specialty care with labs for phenotyping are an important part of evidence based management following an exacerbation requiring an ED visit or hospital admission. We sought to determine predictors for obtaining proper labs and attending a pulmonary or allergy appointment following an exacerbation. Methods This was a retrospective, observational analysis using a claims database for a health system that covers the District of Columbia, Baltimore, and other areas of Maryland. We abstracted demographic and insurance data, along with clinical encounters and laboratory values. Our outcome variables were allergy or pulmonary specialist appointments, absolute eosinophil (eos) counts, and Immunoglobulin E (IgE) levels. We modeled sex, age, insurance status, and race to see which variables predicted each outcome. Results There were a total of 314,162 asthma encounters available for analysis between 2015 and 2024. Of these, 63,440 (20.2%) were ED or inpatient visits. Mean age for these patients was 42.5±21.6, 64.1% were female, 20.2% identified as White, and 5.3% were uninsured. While the majority (43,599 (68.7%)) had eos drawn, only 580 (0.8%) had IgE levels ordered. Mean values for eos and IgE were 247±40 cells/uL and 579.6±195 IU/mL respectively. Only 282 (0.4%) were on record as having seen a Pulmonologist or Allergist. In logistic regression modeling, older age increased (OR 1.055 (95% CI: 1.053-1.056; p 0.01) for eos and OR 1.012 (95% CI: 1.008-1.016; p 0.01) for IgE) and decreased (OR 0.985 (95% CI: 0.979-0.990; p 0.01)) the odds of having labs drawn and specialty referral respectively. Those with insurance were more likely to have eos drawn (OR 1.51 (95% CI: 1.40-1.63; p 0.01) and specialty referral (OR 2.75 (95%: 1.13-6.70; p = 0.03)). Non-white patients were less likely to have labs drawn (OR 0.60 (95% CI: 0.57-0.64; p 0.01) for eos and OR (0.64 (95% CI: 0.54-0.78; p 0.01) for IgE). Females were more likely to have eos drawn (OR 1.167 (95% CI: 1.60-1.73; p 0.01)). Conclusions There are demographic factors associated with important lab orders and specialty referrals after asthma exacerbation. Having health insurance also predicts labs and referrals. Our data help identify those at risk for not receiving guideline directed asthma care. This abstract is funded by: None

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Holley et al. (2026) studied this question.

synapsesocial.com/papers/6a0d4ee2f03e14405aa9a0b3https://doi.org/10.1093/ajrccm/aamag162.386
Ask AI
Helpful
Bookmark
Share
View Full Paper