Documentation of guideline adherence in antenatal records across maternal weight categories: a chart review
Bibliographic record
Abstract
BACKGROUND: Documentation in medical records fulfills key functions, including management of care, communication, quality assurance and record keeping. We sought to describe: 1) rates of standard prenatal care as documented in medical charts, and given the higher risks with excess weight, whether this documentation varied among normal weight, overweight and obese women; and 2) adherence to obesity guidelines for obese women as documented in the chart. METHODS: We conducted a chart review of 300 consecutive charts of women who delivered a live singleton at an academic tertiary centre from January to March 2012, computing Analysis of Variance and Chi Square tests. RESULTS: The proportion of completed fields on the mandatory antenatal forms varied from 100% (maternal age) to 52.7% (pre-pregnancy body mass index). Generally, documentation of care was similar across all weight categories for maternal and prenatal genetic screening tests, ranging from 54.0% (documentation of gonorrhea/chlamydia tests) to 85.0% (documentation of anatomy scan). Documentation of education topics varied widely, from fetal movement in almost all charts across all weight categories but discussion of preterm labour in only 20.6%, 12.7% and 13.4% of normal weight, overweight and obese women's charts (p = 0.224). Across all weight categories, documentation of discussion of exercise, breastfeeding and pain management occurred in less than a fifth of charts. CONCLUSION: Despite a predominance of excess weight in our region, as well as increasing perinatal risks with increasing maternal weight, weight-related issues and other elements of prenatal care were suboptimally documented across all maternal weight categories, despite an obesity guideline.
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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 | 0.019 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".