A survey of primary care physician referral to bariatric surgery in Manitoba: access, perceptions and barriers
Bibliographic record
Abstract
Background: There is an important disconnect between surgical programs and primary care physicians (PCP) in the delivery of bariatric care. The objective of this study is to assess PCP knowledge and perception of a provincial bariatric surgery program. Methods: A 32-question, IRB approved, survey was developed by bariatric surgery experts and vetted by local PCPs. A single round of paper surveys was administered to 1,000 PCPs between July and September 2015. Continuous variables were assessed by t -test and categorical variables by Chi-square test. Results: There were 131 survey responses (13.1%). Half (54.2%) of respondents did not feel equipped to counsel their patients on operative management strategies. PCPs counselled on average 11.6%±17.0% of their obese patients on bariatric surgery. Many respondents (58.3%) thought excess weight loss from gastric bypass was less than 40% and most believed there was less than 50% resolution of diabetes (62.4%), hypertension (72.3%), dyslipidemia (77.8%) and obstructive sleep apnea (60.6%). PCPs who referred patients to the bariatric program (71.8%) were more comfortable counselling their patients on bariatric surgery options (56.8% vs. 17.1%, P<0.001) and were more comfortable with post-operative care (67.4% vs. 38.2%, P=0.004). Additionally, these PCPs estimated higher rates of diabetes and hypertension resolution post-bariatric surgery. The predominant perceived barrier to accessing bariatric surgery was wait times (33.3%). Conclusions: PCPs appear to underestimate the efficacy of bariatric surgery in the treatment of obesity and feel ill-equipped to counsel patients. Further education related to bariatric surgery may improve PCP comfort in counselling and long-term follow-up.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".