Healthcare Utilization and Costs of Systemic Lupus Erythematosus by Disease Severity in the United States
Bibliographic record
Abstract
OBJECTIVE: To quantify healthcare utilization and costs by disease severity for patients with systemic lupus erythematosus (SLE) in the United States. METHODS: We conducted descriptive analyses of Humedica electronic health record (EHR) data from 2011 to 2015 (utilization analysis) and integrated Optum administrative claims/Humedica EHR data from 2012 to 2015 (cost analysis) for patients with SLE. All-cause utilization outcomes examined were hospitalizations, outpatient visits, emergency department (ED) visits, and prescription drug use. Analyses of costs stratified by disease severity were limited to patients enrolled in an Optum-participating health insurance plan for ≥ 1 year after the earliest observed SLE diagnosis date. Costs were converted to 2016 US dollars (US$). RESULTS: Healthcare utilization was evaluated in 17,257 patients with SLE. Averaged over the 2011-2015 study period, 13.7% of patients had ≥ 1 hospitalization per year, 25.7% had ≥ 1 ED visit, and 94.4% had ≥ 1 outpatient visit. Utilization patterns were generally similar across each year studied. Annually, 88.0% of patients had ≥ 1 prescription, including 1.3% who used biologics. Biologic treatment doubled between 2011 (0.7%) and 2015 (1.4%). Cost analyses included 397 patients. From 2012 to 2015, patients with severe SLE had mean annual costs of $52,951, compared with $28,936 and $21,052 for patients with moderate and mild SLE, respectively. Patients with severe SLE had increased costs in all service categories: inpatient, ED, clinic/office visits, and pharmacy. CONCLUSION: Patients from the US with SLE, especially individuals with moderate or severe disease, utilize significant healthcare resources and incur high medical costs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".