A systematic review of the effect of waiting for treatment for chronic pain
Bibliographic record
Abstract
In many countries timely access to care is a growing problem. As medical costs escalate health care resources must be prioritized. In this context there is an increasing need for benchmarks and best practices in wait-time management. The Canadian Pain Society struck a Task Force in December 2005 to identify benchmarks for acceptable wait-times for treatment of chronic pain. As part of the mandate a systematic review of the literature regarding the relationship between waiting times, health status and health outcomes for patients awaiting treatment for chronic pain was undertaken. Twenty-four studies met the inclusion criteria for the review. The current review supports that patients experience a significant deterioration in health related quality of life and psychological well being while waiting for treatment for chronic pain during the 6 months from the time of referral to treatment. It is unknown at what point this deterioration begins as results from the 14 trials involving wait-times of 10 weeks or less yielded mixed results with wait-times amounting to as little as 5 weeks, associated with deterioration. It was concluded that wait-times for chronic pain treatment of 6 months or longer are medically unacceptable. Further study is necessary to determine at what stage the deterioration begins from the onset of pain to treatment and the impact of waiting on treatment outcomes. Most important is the need to improve access to appropriate care for patients with chronic pain, an escalating public health care problem with significant human and economic costs.
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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 | 0.013 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".