Exploring the lack of continuity of care in older cancer patients under China's ‘integrated health system’ reform
Bibliographic record
Abstract
BACKGROUND: Continuity of care is essential to older patients' health outcomes, especially for those with complex needs. It is a key function of primary healthcare. Despite China's policy efforts to promote continuity of care and an integrated healthcare system, primary healthcare centres (PHCs) are generally very underused. OBJECTIVES: To explore the experience and perception of continuity of care in older cancer patients, and to examine how PHCs play a role in the continuity of care within the healthcare system in China. METHODS: A qualitative study using semi-structured interviews was conducted in two tertiary hospitals in Nantong city, Jiangsu province, China. A combination of deductive and inductive analysis was conducted thematically. RESULTS: Interviews with 29 patients highlighted three key themes: no guidance for patients in connecting with different levels of doctors, unmet patients' needs under specialist-led follow-up care, and poor coordination and communication across healthcare levels. This study clearly illustrated patients' lack of personal awareness and experience of care continuity, a key issue despite China's drive for an integrated healthcare system. CONCLUSION: The need for continuity of care at each stage of cancer care is largely unmeasured in the current healthcare system for older patients. PHCs offer benefits which include convenience, less burdened doctors with more time, and lower out-of-pocket payment compared to tertiary hospitals, especially for patients with long-term healthcare needs. However, addressing barriers such as the absence of integrated medical records and unclear roles of PHCs are needed to improve the crucial role of PHCs in continuity of care.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".