The Impact of National Health Insurance Scheme Policy on the Enrollees in Federal Medical Center Keffi, Nasarawa State, Nigeria
Bibliographic record
Abstract
This study examined the implementation of the National Health Insurance Scheme (NHIS) as a social health insurance on the enrollees in Federal Medical Center Keffi(FMC Keffi) of Nasarawa State, Nigeria to the ascertain the effectiveness of the policy on the enrollees. The survey depended on both primary and secondary sources of information for data for the study. Simple percentage was adopted as the method of data analysis. As at the first quarter of 2018 a total population of 15,086 enrollees drawn from all the Health Maintenance Organizations have Memorandum of Understanding with FMC Keffi, with a monthly encounter average of 1,257. Thus, the sample size was determined by Taro Yamme's model and 390 enrollees were randomly selected for the survey. The study revealed that most enrollees face a wide range of challenges in terms of access to quality healthcare service delivery such as; waiting time to see doctors, non-availability of prescribed drugs, sometime lack of prescription sheets. The challenges of non-availability of drugs is largely due to the prescription of branded drugs especially at Specialist Clinics, which are not covered on NHIS, however for drugs which are covered on the scheme and are not available, FMC Keffi made provision for out-sourcing from nearby pharmacies within 24 hours, for the patients. The management of FMC Keffi, also make refund for out-of-pocket spending to patient who could not wait for the out-sourcing. The study recommends that for the enrollees to effectively benefit from this policy all government hospitals and other private hospitals which meet the requirement should be accredited in order to make access to quality healthcare service delivery reachable and affordable at all times for the enrollees amongst others.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".