Medical Audit of Diabetes Mellitus in Primary Care Setting in Bosnia and Herzegovina
Bibliographic record
Abstract
AIM: To assess the quality of diabetes care provided by family medicine teams in primary health centers in Bosnia and Herzegovina (BH) through a medical audit, addressing the extent to which clinical practice complied with pre-determined explicit criteria of long-term management. METHOD: Retrospective analysis included randomly selected medical records of patients with type 1 or 2 diabetes mellitus treated by 18 family medicine teams at 5 locations in BH, included in the Canadian International Development Agency/World Health Organization project "Strengthening health care systems in BH with focus on primary health care/family medicine model." Audit record form contained 24 questions on sex, age, diabetes type, body mass index (BMI), hypertension, family anamnesis, annual examinations (HbA1C, BMI, lipid profile or total cholesterol, blood creatinine, neurological examination, urinalysis for albuminuria, foot care, and examination of ocular fundus), smoking habits, alcohol consumption, patient education, prescribed insulin and other drugs, and patient's health care-seeking behavior. Standardized and record forms were returned anonymously with 99.3% response rate. RESULTS: Records of 536 patients with diabetes were analyzed (64% women and 87% patients with diabetes mellitus type 2). Family medicine teams showed poor compliance with established criteria for diabetes control. Metabolic control (69.5%) was acceptable, but the level of monitoring complications of diabetes (foot and ocular fundus examined in 53.4% and 53% of patients, respectively) was low. There were also considerable variations in diabetes management between different centers as well as between the teams in the same center. CONCLUSION: The audit revealed deficiencies in the quality of diabetes care and variations in care provision between primary care teams. Clinical guidelines and continuing education about acceptable diabetes care should be developed and implemented in BH.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".