The Effect of Back Pain on Health Care Utilization and Costs
Bibliographic record
Abstract
Introduction: We assessed the effect of self-reported back pain on health care utilization and costs in a population-based sample of Ontario adults.
 Methods: We conducted a population-based matched cohort study of Ontarian respondents aged ≥18 years of Canadian Community Health Survey (CCHS) from 2003-2012. CCHS data were individually linked to health administrative data to measure health care utilization and costs up to 2018. We propensity-score matched (hard-matched on sex) adults with self-reported back pain to those without back pain, accounting for sociodemographic, health-related, and behavioural factors. We evaluated back pain-specific and all-cause health care utilization and costs from healthcare payer perspective adjusted to 2018 Canadian dollars. Poisson and linear (log-transformed) models were used to assess healthcare utilization rates and costs. 
 Results: After propensity-score matching, we identified 36,806 pairs (21,054 for women, 15,752 for men) of CCHS respondents with and without back pain (mean age 51 years; SD=18). Compared to propensity-score matched adults without back pain, adults with back pain had two times the rate of back pain-specific visits (women: rate ratio [RR] 2.06, 95% CI 1.88-2.25; men: RR 2.32, 95% CI 2.04-2.64), 1.1 times the rate of all-cause physician visits (women: RR 1.12, 95% CI 1.09-1.16; men: RR 1.10, 95% CI 1.05-1.14), and 1.2 times the costs (women: 1.21, 95% CI 1.16-1.27; men: 1.16, 95% CI 1.09-1.23). Incremental annual per-person costs were higher in adults with back pain versus those without (women: $395, 95% CI $281-$509; men: $196, 95% CI $94-$300), corresponding to $532 million for women and $227 million CAD for men annually in Ontario.
 Conclusions: Adults with back pain had considerably higher health care utilization and costs compared to adults without back pain. These findings provide the most recent, comprehensive, and high-quality estimates of the health system burden of back pain to inform healthcare policy and decision-making. New strategies to reduce the substantial burden of back pain are warranted.
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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 | 0.030 | 0.003 |
| 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".