Initial integration of chiropractic services into a provincially funded inner city community health centre: a program description.
Bibliographic record
Abstract
BACKGROUND: The burden of fees for chiropractic services rendered often falls on the patient and must be provided out-of-pocket regardless of their socioeconomic status and clinical need. Universal healthcare coverage reduces the financial barrier to healthcare utilization, thereby increasing the opportunity for the financially disadvantaged to have access to care. In 2011 the Canadian Province of Manitoba initiated a pilot program providing access to chiropractic care within the Mount Carmel Clinic (MCC), a non-secular, non-profit, inner city community health centre. OBJECTIVE: To describe the initial integration of chiropractic services into a publically funded healthcare facility including patient demographics, referral patterns, treatment practices and clinical outcomes. METHOD: A retrospective database review of chiropractic consultations in 2011 (N=177) was performed. RESULTS: The typical patient referred for chiropractic care was a non-working (86%), 47.3(SD=16.8) year old, who self-identified as Caucasian (52.2%), or Aboriginal (35.8%) and female (68.3%) with a body mass index considered obese at 30.4(SD=7.0). New patient consultations were primarily referrals from other health providers internal to the MCC (71.2%), frequently primary care physicians (76%). Baseline to discharge comparisons of numeric rating scale scores for the cervical, thoracic, lumbar, sacroiliac and extremity regions all exceeded the minimally clinically important difference for reduction in musculoskeletal pain. Improvements occurred over an average of 12.7 (SD=14.3) treatments, and pain reductions were also statistically significant at p<0.05. CONCLUSION: Chiropractic services are being utilized by patients, and referring providers. Clinical outcomes indicate that services rendered decrease musculoskeletal pain in an inner city population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".