Utilization of Ambulatory Physician Encounters, Emergency Room Visits, and Hospitalizations by Systemic Lupus Erythematosus Patients: A 13‐Year Population Health Study
Bibliographic record
Abstract
OBJECTIVE: To determine total physician encounters, emergency room (ER) visits, and hospitalizations in an incident cohort of systemic lupus erythematosus (SLE) cases and matched control patients over 13 years. METHODS: A retrospective cohort study was performed utilizing administrative health care data from approximately 1 million people with access to universal health care. Using International Classification of Diseases, Ninth and Tenth Revisions diagnostic codes, 7 SLE case definitions were used. Each case was matched by age and sex to 4 randomly selected controls. Data included physician billings, ER visits, and hospital discharges over 13 years. RESULTS: The number of incident SLE cases varied from 564 to 4,494 depending on the case definition used. The mean age varied from 47.7 to 50.6 years and the proportion of females from 78.0% to 85.1%. SLE utilization of physicians was highest in the index year, and declined significantly thereafter for all case definitions. By the fourth year, encounters with subspecialty physicians fell by 60% (rheumatologists), 50% (internists), and 31% (other physicians). In contrast, visits to family physicians fell by only 9%. Visits to the ER and hospital admissions for SLE cases were also more frequent early in the disease course and fell significantly over the study for both ER visits (all case definitions) and hospitalizations (2 of 7 case definitions). CONCLUSION: In SLE patients, health care utilization is highest in the first few years following the diagnosis, which is also the time of maximal involvement by rheumatologists. Utilization declines over time, and encounters with patients' family physicians predominate over those of other physician groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".