Consumer subsequent plan for selection of hospital in the perspective of hospital services and expenditure
Bibliographic record
Abstract
Further utilization of hospital facility is influenced by the provision of hospital care and cost of services. This study was conducted among patients of public and private hospitals of Dhaka city, Bangladesh to explore the relationship of further utilization of hospital care and cost of services incurred during previous visits. A total 199 patients of 2 private and 2 public hospitals were included. Of them, 100 (50.25%) were from public and 99 (49.74 %) from private hospitals. Male: female ratio of the respondents was 111:88. The level of services was scored by patients on a 1-5 Likert scale on the aspects of services of doctors, nurses, other staffs; medicine supply; cleanliness; and investigation facilities. Poor people usually sought the services from public hospitals. About three-quarter of the respondents (76.9 %) mentioned that they would avail the facility of same hospital for their further ailment. Seventeen patients (17%) who were treated in government hospitals will not further utilize the services, and this was significantly higher (p-0.02) in the case of patients from private hospitals (29.3%). Regression analysis explored that quality of services (p=-0.000) and cost of services (p=0.001) influenced the plan of future consumption of hospital facility and quality of services having stronger influences. This study concludes that further utilization of the hospital facility was strongly influenced by the quality of services and next to that is cost of services. So we recommend for best and successive utilization of hospital services to improve facilities and minimization of cost are the essential needs.South East Asia Journal of Public Health Vol.6(1) 2016: 14-19
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.037 | 0.003 |
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".