A Systematic Review on International Health Policy and Services Research: A Bibliometric Analysis
Bibliographic record
Abstract
Abstract Background: The number of research publications on health policy and services has been strikingly increasing. This study aimed to reveal the current status and trends of global research on health policy and services and provide insights for health policy and services research. Methods: Based on the Social Science Citation Index (SSCI) database, research on health policy and services published between 1999 and 2018 were identified. The published journals, temporal trends, collaboration between countries/territories and research institutions, and hotspots in health policy and services’ research were analyzed using bibliometric analysis. Results : The number of health policy and services publications has been continuously increasing since 1999, especially after 2008. Health Affairs, Medical Care, and Health Services Research were the most active journals in this field. Scholars from the United States (US), the United Kingdom (UK) and Canada have published more related publications than other countries. Further, The US produced the largest number of independent and collaborative articles, and it took a central position in the collaboration network and had the greatest number of prolific institutions. Harvard University was the largest contributor of single-institution and collaborative publications and occupied a key position in collaborative networks. A keywords analysis demonstrated that medicare, quality of care, and primary care have always been researched hotspots in this field. The rankings of implementation, patient safety, and disparities have risen the most, suggesting a new research trend in the field since the 21st century. Conclusions: Our study identified the temporal and spatial characteristics, academic collaborations, and hotspots in scientific research output in the area of health policy and services. It can provide insights for health policy and services research and global health governance.
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 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 | 0.095 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.290 | 0.358 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.008 |
| Insufficient payload (model declined to judge) | 0.000 | 0.006 |
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; both teacher heads agree on what is shown here.
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".