Healthcare utilization and costs for spinal conditions in Ontario, Canada - opportunities for funding high-value care: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND CONTEXT: An important step in improving spinal care is understanding how current health-care resources and associated cost are being utilized and distributed across a health-care system. PURPOSE: Our objective was to examine the magnitude and distribution of direct health care costs for spinal conditions across physician type and hospital setting. DESIGN/SETTING: Cross-sectional analysis of administrative health data for the fiscal year 2013-2014 from the province of Ontario, Canada. PATIENT SAMPLE: Adult population aged 18+ years (N=10,841,302). OUTCOME MEASURES: Person visit rates and total number of people and visits by specific care settings were calculated for all spinal conditions as well as stratified by nontrauma and trauma-related conditions. Variation in rates by age and sex was examined. The proportion of patients seeing physicians of different specialties was calculated for each condition grouping. Direct medical costs were estimated and their percentage distribution by care setting calculated for nontrauma and trauma-related conditions. Additionally, costs for spinal imaging overall and stratified by type of scan were determined. METHODS: Administrative health databases were analyzed, including data on physician services, emergency department visits, and hospitalizations. ICD-9 and -10 diagnostic codes were used to identify nontraumatic (degenerative or inflammatory) and traumatic spinal disorders. A validated algorithm was used to estimate direct medical costs. RESULTS: Overall, 822,000 adult Ontarians (7.6%) made 1.6 million outpatient physician visits for spinal conditions; the majority (1.1 million) of these visits were for nontrauma conditions. Approximately, 86% of outpatient visits were in primary care. Emergency Department (ED) visits for nontrauma spinal conditions (130,000 out of 156,000 ED visits) accounted for 2.8% of all ED visits in the province. Total costs for spine-related care were $264 million (CDN) with 64% of costs due to nontrauma conditions. For these nontrauma conditions, ED visits cost $28 million for 130,000 visits ($215 per visit). For $32 million spent in primary care, 890,000 visits were made ($36 per visit). Spine imaging costs were $66.5 million, yielding a combined total of $330 million in health care spending for spinal conditions. CONCLUSIONS: Spinal conditions place a large and costly burden on the health-care system. The disproportionate annual cost associated with ED visits represents a potential opportunity to redirect costs to fund more clinically and cost-effective models of care for nontraumatic spinal conditions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".