Research in Integrated Health Care and Publication Trends from the Perspective of Global Informatics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Integrated care has gained popularity in recent decades and is advocated by the World Health Organization. This study examined the global progress, current foci, and the future of integrated care. METHODS: We conducted a scientometric analysis of data exported from the Web of Science database. Publication number and citations, co-authorship between countries and institutions and cluster analysis were calculated and clustered using Histcite12.03.07 and VOS viewer1.6.4. RESULTS: We retrieved 6127 articles from 1997 to 2016. We found the following. (1) The United States, United Kingdom, and Canada had the most publications, citations, and productive institutions. (2) The top 10 cited papers and journals were crucial for knowledge distribution. (3) The 50 author keywords were clustered into 6 groups: digital medicine and e-health, community health and chronic disease management, primary health care and mental health, healthcare system for infectious diseases, healthcare reform and qualitative research, and social care and health policy services. CONCLUSIONS: This paper confirmed that integrated care is undergoing rapid development: more categories are involved and collaborative networks are being established. Various research foci have formed, such as economic incentive mechanisms for integration, e-health data mining, and quantitative studies. There is an urgent need to develop performance measurements for policies and models.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it