Policy of Primary Health Center as First Level Health Facility for Participants of Social Health Insurance Provider Sidoarjo – Indonesia
Bibliographic record
Abstract
In 2012 there were 200 cases of public service disputes to be criminalized in East Java. They occured as a logical consequence of Act Number 14 Year 2008 leading to some consequences that public service is required to give satisfaction to the society The problem of health services in Indonesia cannot be separated from the low competence of the medical personnel, infrastructure and medical equipment, human resources, and complex regulations which are not easy to implement. Due to the problem above, a research focused on such policies to improve the capacity building by optimizing the role of Primary Health Center (PHC) as First Level Health Facility (FLHF) especially for Participants Social Health Insurance Provider (SHIP) is highly considered to carry out. The Social Health Insurance Provider is a legal entity established to administer the Health Insurance program, and the Primary Health Center is a health service facility that organizes some efforts on public and individual health at the first level. In ensuring the satisfaction of adequate services, FLHF has been working with PHC as the implementer of health services for SHIP participants. Because of it, PHC becomes the forefront to provide the health services to the community, especially, to SHIP participants. To increase the satisfaction of SHIP participants, it is necessary to note and find some ways out to the problems related to the improvement of Human Resources, Health Facilities, Service system, Information and supervision.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".