The Cost-effectiveness of Spinal Cord Stimulation in the Treatment of Failed Back Surgery Syndrome
Bibliographic record
Abstract
OBJECTIVES: Healthcare policy makers and payers require cost-effectiveness evidence to inform their treatment funding decisions. Thus, in 2008, the United Kingdom's National Institute of Health and Clinical Excellence analyzed the cost effectiveness of spinal cord stimulation (SCS) compared with conventional medical management (CMM) and with reoperation and recommended approval of SCS in selected patients with failed back surgery syndrome (FBSS). We present previously unavailable details of the National Institute of Health and Clinical Excellence analysis and an analysis of the impact on SCS cost effectiveness of rechargeable implanted pulse generators (IPGs). METHODS: We used a decision analytic model to examine the cost effectiveness of SCS versus CMM and versus reoperation in patients with FBSS. We also modeled the impact of nonrechargeable versus rechargeable IPGs. RESULTS: The incremental cost-effectiveness of SCS compared with CMM was pound5624 per quality-adjusted life year, with 89% probability that SCS is cost effective at a willingness to pay threshold of pound20,000. Compared with reoperation, the incremental cost-effectiveness of SCS was pound6392 per quality-adjusted life year, with 82% probability of cost-effectiveness at the pound20,000 threshold. When the longevity of an IPG is 4 years or less, a rechargeable (and initially more expensive) IPG is more cost-effective than a nonrechargeable IPG. DISCUSSION: In selected patients with FBSS, SCS is cost effective both as an adjunct to CMM and as an alternative to reoperation. Despite their initial increased expense, rechargeable IPGs should be considered when IPG longevity is likely to be short.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".