Patient-centered endometriosis care implementation at tertiary and secondary care hospitals in Indonesia
Bibliographic record
Abstract
Background: Endometriosis has a high recurrence rate within five years (40-50 %). High recurrence remarkably reduces Health-Related Quality of Life (HRQOL). Patient-centered endometriosis care (PCEC) is a range of care that respects the patient's preferences and needs while being guided by the patient's values and may provide better treatment for patients. Our study is the first to evaluate the implementation of PCEC in Indonesia. Materials and methods: We evaluated PCEC at Dr. Cipto Mangunkusumo Hospital in Jakarta (Center-1), Raden Mattaher Hospital in Jambi, and dr. Zainoel Abidin Hospital in Aceh (Center-2) from October 2021 to May 2022. Center-1 represented tertiary care, and center-2 represented secondary care. This study used the ENDOCARE Questionnaire (ECQ) instrument, which produced mean important score (MIS), percentage of negative performance (PNP), and patient-centeredness score (PCS) as outcomes. Higher PCS reflects greater patient-centered care of the center. Results: A total of 73 patients were recruited and divided into two groups of centers. Patients from Center-1 had significantly higher patient-centeredness scores vs. patients in centers without the training and guideline: dimension "Respect for patients' values, preferences, and needs" (Center-1 7.33, 6-10, Center-2 6, 6-6; p < 0.001), dimension "Coordination and integration of care" (Center-1 6, 4.44-8.67, Center-2 5.5, 4-6; p = 0.006), dimension "Information, communication, and education" (Center-1 7.14, 6-8.29, Center-2 5.14, 5.14-6; p < 0.001), dimension "Physical comfort" (Center-1 6, 6-8, Center-2 6, 6-6; p = 0.033), dimension "Endometriosis clinical staff" (Center-1 6, 6-9, Center-2 6, 6-6, p = 0.049). Subjects with higher education and experienced endometriosis recurrences statistically had higher patient-centeredness scores. Conclusion: Our findings suggest that endometriosis training and having endometriosis clinical guidelines could improve patients' experience in receiving PCEC. Information for patients should be made simple so they can understand the purpose of the treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".