Mutu Dimensi Jaminan Pelayanan Kesehatan dalam Peningkatan Kepuasan Pelanggan di RSU DR. H. Koesnadi Bondowoso
Bibliographic record
Abstract
The main focus of KARS 2012 hospital accreditation is the quality of patient care and safety. The decreasing of Satisfaction Index of Public in Stroke Pojok RSU room dr. H. Koesnadi Bondowoso from the fourth quarter of 2016 by 78.1% and in the first quarter of 2017 to 76.63% showed a decrease in customer satisfaction ever treated in the space. So with this research is expected to know the assessment of the community as a service user stroke corner about the quality of service received. This research is a qualitative study with case study approach conducted from April to December 2017. This research focuses on assurance dimension as one dimension of health service by using three assessment indicators, covering the ability of officer in giving service, actions to be performed and the preservation of patient privacy. The main informants in this study were 10 people from the patient's family who were being treated and the additional informant was 2 nurse stroke corner. From this research, it is found that officer of stroke corner has different ability and skill, stroke corner officer always keep patient privacy and officer always ask permission (inform concent) before doing action. In conclusion that most informants expressed satisfaction with the service guarantee provided by the stroke corner room. Keyword: Stroke, Stroke Corner, Satisfaction, Assurance
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 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".