Association of chiropractic integration in an Ontario community health centre with prescription opioid use for chronic non-cancer pain: a mixed methods study protocol
Bibliographic record
Abstract
INTRODUCTION: Emerging evidence from a number of primary care centres suggests that integration of chiropractic services into chronic pain management is associated with improved clinical outcomes and high patient satisfaction as well as with reductions in physician visits, specialist referrals use of advanced imaging and prescribing of analgesics. However, formal assessments of the integration of chiropractic services into primary care settings are sparse, and the impact of such integration on prescription opioid use in chronic pain management remains uncertain. To help address this knowledge gap, we will conduct a mixed methods health service evaluation of an integrated chiropractic back pain programme in an urban community health centre in Ontario, Canada. This centre provides services to vulnerable populations with high unemployment rates, multiple comorbidities and musculoskeletal disorders that are commonly managed with prescription opioids. METHODS AND ANALYSIS: We will use a sequential explanatory mixed methods design, which consists of a quantitative phase followed by a qualitative phase. In the quantitative phase, we will conduct a retrospective chart review and evaluate whether receipt of chiropractic services is associated with reduced opioid use among patients already prescribed opioid therapy for chronic pain. We will measure opioid prescriptions (ie, opioid fills, number of refills and dosages) by reviewing electronic medical records of recipients and non-recipients of chiropractic services between 1 January 2014 and 31 December 2020 and use multivariable regression analysis to examine the association. In the qualitative phase, we will conduct in-depth, one-on-one interviews of patients and their general practitioners to explore perceptions of chiropractic integration and its impact on opioid use. ETHICS AND DISSEMINATION: This study was approved by the Hamilton Integrated Research Ethics Board at McMaster University (approval number 2021-10930). The results will be disseminated via peer-reviewed publications, conference presentations and in-person or webinar presentations to community members and healthcare professionals.
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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 | 0.050 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".