Challenges and Opportunities for Person Centered Integrated Care Through the Life Course
Bibliographic record
Abstract
Objective: To examine the opportunities and challenges in achieving person centered integrated care through the life course. Methods: Critical literature review and evidence based analysis of person-centered integrated care through the life course, combined with expert consultation. The World Health Organization’s “Global Framework on Integrated People-Centred Health Services” is used as a basis. Results: Using the approach of the life cycle allows connection of persons’ current health status to their sociocultural, biological, and psychological context. Person centered medicine has as its central precept the relationship between the health professional and person seeking care. This principle is the link to primary health care, which is built on a lasting relationship with individuals and populations in their social context. The patient’s medical home provides one promising model of how health services can be organized to support the full achievement of person centered integrated care. Re-orientation of the health professional education towards generalism, and the development of metrics for measurement of person centered integrated care are required. In 2016 the global crisis in refugees is a particularly prominent challenge for the delivery of person centered integrated care. Conclusion: Universal health coverage can provide equitable access to person centered integrated care throughout the life course. Specialized expertise and skills are important for caring for persons with specific conditions at particular times in the life course. When care is well-integrated, transitions of care are smooth and the critical paradigm of person-centeredness is retained.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.029 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".