Service Quality Perspectives and Satisfaction in Health Care Systems-A study of select hospitals in Hyderabad
Bibliographic record
Abstract
Liberalization, Privatization and Globalization (LPG) has brought unprecedented changes in the economic, trade and industrial scenario. LPG environment has exposed various organizations including the service sectors to the challenges of competition; service quality, cost and the competitive environment will help organizations to modernize. The impact of globalization and its implications for our country's health care sector has rightly received wide attention and has been the subject of various health conclaves. With the state-of- the art medical procedures, equipment and facilities now available in India, patients from developed countries like Canada and Britain are choosing Indian Hospitals. Today India is not only well poised to meet the health care challenges of the millennium but also equipped with the talent and strength to contribute in further developing the health and economy of the world.Health is Wealth, the old saying still holds true. It is increasingly being recognized that good health is an important contributor to the productivity and economic growth at the same time it is first and foremost and an end itself. Perhaps, health care industry is one industry, which never faces a recession. Entry of private participants in the health insurance will enhance the accessibility of health care facilities to millions thus providing the right kind of health care services at affordable cost.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".