Satisfaction with Delivery Services Offered under the Free Maternal Healthcare Policy in Kenyan Public Health Facilities
Bibliographic record
Abstract
Background. Patients’ satisfaction is an individual's positive assessment regarding a distinct dimension of healthcare and the perception about the quality of services offered in that health facility. Patients who are not satisfied with healthcare services in a certain health facility will bypass the facility and are unlikely to seek treatment in that facility. Objective. To determine satisfaction level of mothers with the free maternal services in selected Kenyan public health facilities after the implementation of the free maternal healthcare policy. Methods. Data was collected through a quantitative exit survey questionnaire. The respondents were mothers who had delivered in the health facilities and were waiting to leave the health facilities after discharge. The sample included 2,216 mothers in 77 public health facilities across 14 counties in Kenya under tier 3 and tier 4 categories. The number of respondents to be interviewed was proportionately arrived at based on each health facility’s bed capacity. Results. The study established a satisfaction rate of 54.5% among the beneficiaries of the free maternal healthcare services in the country. Mothers benefiting from the free delivery services were satisfied with communication by the healthcare workers, staff availability in the delivery rooms, availability of staff in the wards, and drug and supplies availability (>56%) but unsatisfied with consultation time, cleanliness, and privacy in the wards (<56%). High education levels and lengthy stay in healthcare facilities were negatively associated with the satisfaction with the free delivery services ( P<0.05 ). Conclusion. There is a high satisfaction with the free maternal healthcare services in Kenya. However, the implementation of the free maternal healthcare policy was associated with low privacy, poor hygiene, and low consultation time in the health facilities. Therefore there is need to address these service gaps so as to attract more mothers to deliver in public health facilities.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| 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".