Kajian Literatur Sistematis: Skema Pengendalian Biaya dalam Asuransi Kesehatan Nasional di Beberapa Negara
Bibliographic record
Abstract
AbstrakPengendalian biaya merupakan salah satu dari beberapa strategi untuk memastikan keseimbangan finansial dari skema asuransi kesehatan nasional. Beberapa model pengendalian biaya yang umum digunakan secara global yaitu seperti cost-sharing, capping, dan sebagainya. Review ini dilakukan dengan tujuan untuk menentukan biaya dan dampak dari implementasi skema kebijakan sebagai instrumen pengendalian biaya di berbagai negara. Review sistematis dilakukan dengan mengambil data dari beberapa database yaitu Proquest, Pubmed, dan Cochrane Library dengan intervensi utamanya yaitu menggunakan metode cost-sharing. Hasil dari review difokuskan pada skema pengendalian biaya dari perspektif pemerintah, yaitu lingkup asuransi sosial yang dapat berupa modifikasi sistem pembayaran, cost-sharing, capping/quota, dan waiting period. Berdasarkan salah satu studi di Kanada, dapat dilihat bahwa dihasilkan dampak yang signifikan pada sistem kesehatan, mengurangi pengeluaran dan penggunaan obat yang tidak esensial, serta secara tidak langsung meningkatkan efisiensi pasar obat melalui kepedulian peserta dalam penggunan obat. Dalam penelitian ini dapat disimpulkan bahwa implementasi dari skema pengendalian biaya dapat mengurangi risiko bahaya dari perspektif peserta dengan kontribusi tambahan pada penggunaan pelayanan kesehatan. AbstractCost-containment is one of several strategies to ensure the financial sustainability of the National Health Insurance scheme. Several cost-containment models were commonly globally, such as cost-sharing, capping, and others. This review aims to determine the costs and impacts of implemented policy schemes as cost-containment instruments in various countries. We performed a systematic review from several primary databases (Proquest, Pubmed, and Cochrane Library) with the primary intervention are the cost-sharing methods. The results of our review focused on the cost containment scheme from the government perspective, in which the context of social insurance can be a modification of payment systems, cost-sharing, capping/quota, and waiting period. From one of the studies in Canada, we can see that the result has a significant impact on the health system, reducing the expenditure and the use of drugs that are not essential, and also indirectly improve the technical efficiency of the drug market through the care of participants in drug utilisation. In this research, it can be concluded that the implementation of cost containment schemes can reduce the moral hazard risk from the perspective of participants with additional contributions to the utilisation of healthcare services
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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 | 0.009 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.005 |
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".