Geriatric Medicine in South Korea: A Stagnant Reality amidst an Aging Population
Bibliographic record
Abstract
In the face of an ever-increasing wave of an aging population, this paper provides an update on the current status of geriatric medicine in Korea, comparing it with global initiatives and suggesting future directions. Older adults require a multifaceted approach, addressing not only comorbidity management but also unmet complex medical needs, nutrition, and exercise to prevent functional decline. In this regard, the World Health Organization's Integrated Care for Older People guidelines underscore the importance of patient-centered primary care in preventing a decline in intrinsic capacity. Despite these societal needs and the ongoing aging process, the healthcare system in Korea has yet to show significant movement or a shift toward geriatric medicine, further complicated by the absence of a primary care system. We further explore global efforts in establishing age-integrative patient-centered medical systems in Singapore, Australia, Canada, the United Kingdom, and Japan. Additionally, we review the unmet needs and social issues that Korean society is currently facing, and local efforts by both government and a private tertiary hospital in Korea. In conclusion, considering the current situation, we propose that the framework of geriatric medicine should form the foundation of the future healthcare system.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".