Cost of managing an episode of relapse in multiple sclerosis in the United States
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to determine the direct medical US cost of managing multiple sclerosis relapses. METHODS: Direct data analysis and cost modeling were employed to derive typical resource use profiles and costs in 2002 US dollars, from the perspective of a third-party payer responsible for comprehensive health-care. The location and scope of health care services provided over a 90-day period were used to define three levels of relapse management. Hospitalization and resulting subsequent care was defined as high intensity management. A medium level of intervention was defined as either use of the emergency room, an observational unit, or administration of acute treatments, such as intravenous methylprednisolone in an outpatient or home setting. The lowest intensity of care comprised physician office visits and symptom-related medications. Data were obtained from many sources including all payer inpatient, ambulatory and emergency room databases from several states, fee schedules, government reports, and literature. All charges were adjusted using cost-to-charge ratios. RESULTS: Average cost per person for high management level was 12,870 dollars, based on analysis of 4,634 hospital cases (mean age 48 years, 73% female). Hospital care comprised 71% of that cost. At discharge, 36% required inpatient sub-acute care, rehabilitation or home care. The typical cost per moderate episode was 1,847 dollars and mild episode 243 dollars. CONCLUSIONS: Management strategies leading to a reduction in the frequency and severity of a relapse, less reliance on inpatient care, or increased access to steroid infusions in the home, would have a substantial impact on the economic consequences of managing relapses.
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 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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".