A comparative study on the obstetric services utilization by income classes among the National Health Insurance Beneficiaries
Bibliographic record
Abstract
ObjectiveThis study was conducted to compare the trend of obstetrical care service and its performance, different kinds of common obstetrical disease, and different pattern of health care utilization by the classification of income among the National Health Insurance Beneficiaries. MethodsThis study was investigated on the base of data which were drawn from the "nationwide claim database of Korean National Health Insurance Corporation".Data were composed of the total cases related to pregnancy, childbirth, and the puerperium from 2004 to 2008.Subjects were divided into five income classes by the amount of medical insurance premium.Statistical analysis was performed using SAS program. ResultsIn terms of the lowest income class, there was the lowest rate of admission but the highest rate of outpatient visits, which were remarkably increased during the last 2 years.The lowest income group showed higher rate of abortion (O00-O08), ectopic pregnancy and preeclampsia (O10-O16) but there was small number of delivery (O80-O84).The highest income group showed higher rate of multifetal gestation and elderly gravida.As they have higher income, they showed tendency to visit general hospital for admission care or outpatient care. ConclusionThere were significant differences in obstetric services utilization and prevalence of common obstetrical disease according to income class.New strategy of public medical insurance is needed to support different disease category according to the socioeconomic status.Especially, institutional support should be considered for lower income women who are exposed to higher pregnancy complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".