Electronic health record-based assessment of oral corticosteroid use in a population of primary care patients with asthma: an observational study
Bibliographic record
Abstract
BACKGROUND: Oral corticosteroid prescriptions are often used in clinical studies as an indicator of asthma exacerbations. However, there is rarely the ability to link a prescription to its associated diagnosis. The objective of this study was to characterize patterns of oral corticosteroid prescription orders for asthma patients using an electronic health record database, which links each prescription order to the diagnosis assigned at the time the order was placed. METHODS: This was a retrospective cohort study of the electronic health records of asthma patients enrolled in the Geisinger Health System from January 1, 2001 to August 23, 2010. Eligible patients were 12-85 years old, had a primary care physician in the Geisinger Health System, and had asthma. Each oral corticosteroid order was classified as being prescribed for an asthma-related or non-asthma-related condition based on the associated diagnosis. Asthma-related oral corticosteroid use was classified as either chronic or acute. In patient-level analyses, we determined the number of asthma patients with asthma-related and non-asthma-related prescription orders and the number of patients with acute versus chronic use. Prescription-level analyses ascertained the percentages of oral corticosteroid prescription orders that were for asthma-related and non-asthma-related conditions. RESULTS: Among the 21,199 asthma patients identified in the electronic health record database, 15,017 (70.8%) had an oral corticosteroid prescription order. Many patients (N = 6,827; 45.5%) had prescription orders for both asthma-related and non-asthma-related conditions, but some had prescription orders exclusively for asthma-related (N = 3,450; 23.0%) or non-asthma-related conditions (N = 4,740; 31.6%). Among the patients receiving a prescription order, most (87.5%) could be classified as acute users. A total of 60,355 oral corticosteroid prescription orders were placed for the asthma patients in this study-31,397 (52.0%) for non-asthma-related conditions, 24,487 (40.6%) for asthma-related conditions, and 4,471 (7.4%) for both asthma-related and non-asthma-related conditions. CONCLUSIONS: Oral corticosteroid prescriptions for asthma patients are frequently ordered for conditions unrelated to asthma. A prescription for oral corticosteroids may be an unreliable marker of asthma exacerbations in retrospective studies utilizing administrative claims data. Investigators should consider co-morbid conditions for which oral corticosteroid use may also be indicated and/or different criteria for assessing oral corticosteroid use for asthma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".