<p>Treatment Patterns and Health Care Costs of Lupus Nephritis in a United States Payer Population</p>
Bibliographic record
Abstract
OBJECTIVE: To describe the characteristics, treatment patterns, health care resource utilization (HCRU), and cost of care for members of a large United States (US) health insurance plan with lupus nephritis (LN). METHODS: A retrospective observational study was conducted using a health insurance plan database to identify adult members with a diagnosis of LN. Medical and pharmacy claims were used to describe demographics, comorbidities, HCRU, and cost patterns over a 12-month follow-up period for each patient, between January 1, 2014, and December 31, 2016. All study variables were examined descriptively. RESULTS: A total of 1039 patients were available for analysis (median age, 47 years; 83% female). The median Charlson Comorbidity Index (CCI) was 3.3. Less than half (41%) of patients received immunosuppressive therapies commonly used to treat LN. Evidence indicated that 58% of the study population were prescribed corticosteroid therapy, in most cases (73%) for more than 60 days. Adverse events known to be associated with corticosteroid therapy were recorded in 58% of patients. Guideline-recommended preventive therapy with hydroxychloroquine was prescribed for 54% of members with LN. Nearly half (47%) of members with LN did not see a nephrologist and more than one-third (36%) did not see a rheumatologist over 1 year of follow-up. Rates of all-cause hospitalization and emergency department (ED) use were 25% and 35%, respectively. The mean all-cause per-member-per-month (PMPM) medical cost for the study population was $2801, with LN-specific costs accounting for $1147 PMPM. CONCLUSION: Patients with LN who are insured through a large US health plan appeared to underutilize outpatient specialist services and guideline-recommended hydroxychloroquine therapy. Corticosteroid use and adverse events known to be associated with corticosteroids were common in this cohort.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".