Development of a senior-specific, citizen-oriented healthcare service system in South Korea based on the Canadian 48/6 model of care
Bibliographic record
Abstract
BACKGROUND: In the age of aging, Korea's current medical delivery system threatens to increase the number of medical and caring refugees. This study attempts to develop an integrated senior citizen-oriented healthcare service system in which daily care, professional care, and rehabilitation are organically organized between medical institutions and local communities, thereby meeting the daily life needs of the elderly and inducing well-being, wellness, and well-dying. METHODS: To develop the integrated healthcare system, data collection and analyses were conducted through a systematic review, literature review, benchmarking, focus group interviews, and expert consultation. RESULTS: The senior-specific, citizen-oriented healthcare service system developed in this study is designed to screen patients aged 65 or older within 24 h of being admitted, using the Geriatric Screening for Care-10. If there is reason for concern as a result of the screening, further evaluation is performed through assessment. Doctors and nurses create a care plan and a discharge plan based on the results from the screening and assessment. The nurse further uses the screening to monitor the patient's condition before discharge. Based on the screening results at the time of discharge, a transitional care plan is prepared and provided to elderly patients and/or their families. This process enables a systematic link between medical institutions and community resources, aiming for the continuous management of health issues. It also establishes a multidisciplinary treatment plan that considers patients and their families so that diseases common to the elderly are diagnosed and treated promptly. CONCLUSIONS: The most important issue for the elderly is to be able to live healthily and independently for the rest of their lives through well-being, wellness, and well-dying. The senior-specific, citizen-oriented healthcare service proposed in this study is an integrated medical treatment system for elderly users the implementation of which requires the daily care, professional care, and rehabilitation of elderly members of society to be organically organized according to the role of the patients, their families, and the caregiver.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".