Fragmentation of care: a major challenge for older people living with multimorbidity
Bibliographic record
Abstract
As the world’s aging population is rising, so too is the prevalence of multimorbidity increasing among older adults. Multimorbidity is therefore a growing public health challenge among the older population. Researchers have reported fragmentation of care to be one of the major problems facing this population. The leading factors responsible for this issue are use of disease-centered approaches and specialism to manage people living with multimorbidity; poor communication between professionals and people with multimorbidity; and poor communication among the professionals caring for these people. Failure to address this problem leads to increased treatment burden, including polypharmacy. There is therefore a need for all healthcare professionals caring for older people living with multimorbidity to address this problem by providing continuous, coordinated person-centered care. For the person-centered care approach to be well-coordinated and continuous, there is a need for effective means of sharing information among healthcare providers, to facilitate inter-professional collaboration; extension of consultation time to better enable healthcare providers to understand the patient's needs; review of organizational frameworks and policies where necessary; and development of new guidelines for the management of multimorbidity.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".