Patient Satisfaction With the Health Care Services of a Government-Financed Health Protection Scheme in Bangladesh: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Since 2016, the government of Bangladesh has been piloting a health protection scheme known as Shasthyo Surokhsha Karmasuchi (SSK), which specifically targets households living below the poverty line. This noncontributory scheme provides enrolled households access to inpatient health care services for 78 disease groups. Understanding patients' experiences with health care utilization from the pilot SSK scheme is important for enhancing the quality of health care service delivery during the national-level scale-up of the scheme. OBJECTIVE: We aimed to evaluate patient satisfaction with the health care services provided under the pilot health protection scheme in Bangladesh. METHODS: A cross-sectional survey was conducted with the users of the SSK scheme from August to November 2019. Patients who had spent a minimum of 2 nights at health care facilities were selected for face-to-face exit interviews. During these interviews, we collected information on patients' socioeconomic characteristics, care-seeking experiences, and level of satisfaction with various aspects of health care service delivery. To measure satisfaction, we employed a 5-point Likert scale (very satisfied, 5; satisfied, 4; neither satisfied nor dissatisfied, 3; dissatisfied, 2; very dissatisfied, 1). Descriptive statistics, statistical inferential tests (t-test and 1-way ANOVA), and linear regression analyses were performed. RESULTS: We found that 55.1% (241/438) of users were either very satisfied or satisfied with the health care services of the SSK scheme. The most satisfactory indicators were related to privacy maintained during diagnostic tests (mean 3.91, SD 0.64), physicians' behaviors (mean 3.86, SD 0.77), services provided at the registration booth (mean 3.86, SD 0.62), confidentiality maintained regarding diseases (mean 3.78, SD 0.72), and nurses' behaviors (mean 3.60, SD 0.83). Poor satisfaction was identified in the interaction of patients with providers about illness-related information (mean 2.14, SD 1.40), availability of drinking water (mean 1.46, SD 0.76), cleanliness of toilets (mean 2.85, SD 1.04), and cleanliness of the waiting room (mean 2.92, SD 1.09). Patient satisfaction significantly decreased by 0.20 points for registration times of 16-30 minutes and by 0.32 points for registration times of >30 minutes compared with registration times of ≤15 minutes. Similarly, patient satisfaction significantly decreased with an increase in the waiting time to obtain services. However, the satisfaction of users significantly increased if they received a complete course of medicines and all prescribed diagnostic services. CONCLUSIONS: More than half of the users were satisfied with the services provided under the SSK scheme. However, there is scope for improving user satisfaction. To improve the satisfaction level, the SSK scheme implementation authorities should pay attention to reducing the registration time and waiting time to obtain services and improving the availability of drugs and prescribed diagnostic services. The authorities should also ensure the supply of drinking water and enhance the cleanliness of the facility.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".