Strengthening breast cancer services in Vietnam: a mixed-methods study
Bibliographic record
Abstract
BACKGROUND: Incidence of breast cancer has increased in Vietnam over the past two decades, but little data exists to inform policy and planning. This study examined the organisation and delivery of breast cancer services in Vietnam in order to address the lack of data on detection, diagnosis and treatment. METHODS: We gathered quantitative and qualitative data using an adapted survey-based Service Availability and Readiness Assessment (SARA) tool and semi-structured interviews from healthcare providers in 69 healthcare facilities about the experience and challenges of delivering breast cancer services. We conducted our study across four levels of the health system in three provinces in Vietnam. RESULTS: The analysis of our data show that a number of areas require strengthening particularly in relation to service availability and service readiness. Firstly, healthcare providers across all levels of the health system reported that service provision was constrained by a lack of resources both in relation to health infrastructure and training for healthcare providers. Secondly, access to timely diagnosis and treatment is limited due to services only being available at the top two levels of the health system. Women living outside the immediate vicinity of such facilities tend to find access more costly and time-consuming, and there is a need to investigate the social, economic, geographic and cultural barriers that may prevent women from accessing services. CONCLUSIONS: Our study suggests that there is a need to strengthen lower levels of the Vietnamese health system in relation to the detection of breast cancer. Provision of some services such as clinical breast examination, advice on self-examination, and conducting ultrasound tests (supported with appropriate training and capacity-building of healthcare providers) at commune and district levels of the health system may reduce the overcrowding and service-delivery burden experienced in provincial and national-level hospitals. Empowering lower levels of the health system to conduct breast cancer screening, which is currently undertaken on an ad hoc basis through higher-level facilities, is likely to improve access to services for women.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".