A systematic review and qualitative analysis of geriatric models of care for rural and remote populations
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
INTRODUCTION: Much is known about the healthcare needs of rural and remote communities; however, understanding how to best deliver geriatric models of care in these settings has received less attention. The purpose of this systematic review was to identify necessary key components of existing models of geriatric care serving rural or remote populations. METHODS: A systematic literature review was conducted using MEDLINE, CINAHL and EMBASE databases to identify articles that described models of geriatric care serving rural or remote populations. A qualitative case study and key component analysis approach was used to identify necessary model components. RESULTS: Eight articles were included. We identified eight distinct components that may improve the successful delivery of models of geriatric care serving rural or remote populations. Environmental assessments were done in six of eight models. Model integration with the local healthcare system, local provider leadership, and local provider education in geriatrics were present in five of eight models. Three of eight models used high-risk screening principles and included geriatrician consultation. One model described active community engagement, and one used telemedicine. CONCLUSION: Future geriatric care delivery models designed to serve rural or remote populations are encouraged to use an evidence-based framework based on eight distinct model characteristics found in the literature that aim to support the ideal provision of effective and accessible geriatric medical care.
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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) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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