What Gets in the Way of Person-Centred Care for People with Multimorbidity? Lessons from Ontario, Canada
Bibliographic record
Abstract
Person-centred care is becoming a key component of quality in health systems worldwide. Although the term can mean different things, it typically entails paying attention to the needs and background of health system users, involving them in decisions that affect their health, assessing their care goals and implementing a coordinated plan of care that aligns with their unique circumstances. The importance of practising a person-centred approach in care delivery dominates policy and research rhetoric worldwide, yet competing goals set by policy planners to save money, eliminate waste and sustain the healthcare system challenge the implementation of such an approach. In this commentary, we begin by exploring the concept of person-centred care and its importance among people who frequently use healthcare, such as those with multimorbidity. We then provide a brief overview of the evolution of Ontario's healthcare system and its emphasis on achieving cost savings. In doing so, we illustrate the implications for health system users, particularly people with multimorbidity, their carers and formal care providers. Finally, we reflect on examples of innovations that are striving to deliver person-centred care, despite a constrained healthcare environment. While a step in the right direction, we conclude that these "one-off" strategies are unsustainable in the absence of supporting policy levers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".