Comparison of Family Medicine and General Internal Medicine on Diabetes Management.
Bibliographic record
Abstract
The majority of patients with type 2 diabetes are managed in primary care, either in family medicine (FM) or general internal medicine (GIM). Variances in training, beliefs and practice decisions between FM and GIM may result in differing approaches to diabetes management. This study found that differences do exist in the choice of treatment by FM vs GIM; however, these differences are driven by patient characteristics and does not result in glycemic control disparities. BACKGROUND AND OBJECTIVES: Approach to management of chronic health conditions differs between family medicine (FM) and general internal medicine (GIM). Differences might be due to beliefs, patient case mix, training, and/or experience. This study determined if FM and GIM diabetes management differences exist, and if so, resulted in better or worse glycemic control. METHOD: Electronic medical record data from 2008-2013 were used to identify 976 patients (287 FM and 689 GIM) with type 2 diabetes and prescriptions for metformin. GEE-type regression models were computed to control for repeated measures and estimate the association between primary care specialty and glycemic control, defined as percent of patients with HgA1c<8.5 and average HgA1c. Covariates included demographics, comorbidities, smoking and health care utilization, and diabetes treatment. RESULTS: Compared to FM patients, significantly more GIM patients received a non-metformin medication (35.9% vs 47.2%) and insulin (16.4% vs 23.8%). After adjusting for covariates, FM patients had significantly lower HgA1c values (B = -.47; 95% CI: -0.68, -0.27) and were less likely to have an HgA1c>8.5 (OR=0.55; 95%CI:0.40-0.77). FM vs GIM patients did not differ in degree of HgA1c improvement over time. CONCLUSIONS: FM patients vs GIM patients are less likely to receive a non-metformin and insulin medication. Differences in diabetes management likely correspond to degree of HgA1c control. Choice of treatment appears to reflect patient needs as both FM and GIM patients experienced equal improvement in HgA1c. Primary care specialty differences in beliefs and practices around diabetes management do not result in disparities in patient care.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".