Factors Influencing Support for National Health Insurance among Patients Attending Specialist Clinics in Malaysia
Bibliographic record
Abstract
This study was carried out to determine the level of support towards the proposed National Health Insurance scheme among Malaysian patients attending specialist clinics at the National University of Malaysia Medical centre and its influencing factors. The cross sectional study was carried out from July-October 2012. 260 patients were selected using multistage sampling method. 71.2% of respondents supported the proposed National Health insurance scheme. 61.4% of respondents are willing to pay up to RM240 per year to join the National Health Insurance and 76.6% of respondents are of the view that enrollment in NHI should be made compulsory. Knowledge had a positive influence on respondent's support towards National Health Insurance. National Health Insurance when implemented in Malaysia can be used to raise funds for health care financing, increase access to health services and achieve the desired health status. More efforts should be taken to promote the scheme and educate the public in order to achieve higher support towards the proposed National Health Insurance. The cost to enroll in NHI as well as services to be included under the scheme should be duly considered.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".