Documentation of Behavioral Health Risk Factors in a Large Academic Primary Care Clinic
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of alcohol, smoking, and physical activity status documentation at a family health team in Toronto, Ontario, and to explore the patient characteristics that predict documentation of these lifestyle risk factor statuses. DESIGN: Manual retrospective review of electronic medical records (EMRs). SETTING: Large, urban, academic family health team in Toronto, Ontario. PARTICIPANTS: Patients over the age of 18 that had attended a routine clinical appointment in March, 2018. MAIN OUTCOME MEASURES: Prevalence and content of risk factor status in electronic medical records for alcohol, smoking, and physical activity. RESULTS: The prevalence of alcohol, smoking, and physical activity documentation was 86.4%, 90.4%, and 66.1%, respectively. These lifestyle risk factor statuses were most often documented in the "risk factors" section of the EMR (83.7% for alcohol, 88.1% for smoking, and 47.9% for physical activity). Completion of a periodic health review within 1 year was most strongly associated with documentation (alcohol odds ratio [OR] 9.79, 95% Confidence Interval [CI] 2.12, 45.15; smoking OR 1.77 95% CI 0.51, 6.20; physical activity OR 3.52 95% CI 1.67, 7.40). CONCLUSION: Documentation of lifestyle risk factor statuses is strongly associated with having a recent periodic health review. If "annual physicals" continue to decline, primary care providers should final additional opportunities to address these key determinants of health.
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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 | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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".