Person-centred Care Coordination in Ontario: A Multimethod Evaluation of Implementation and Impact
Bibliographic record
Abstract
As the number of persons living with complex health and social care needs increases, healthcare systems are faced with the challenge of providing high quality care to these individuals. One approach utilized by many healthcare systems to achieve high quality care for persons living with complex health and social care needs is person-centred care coordination). A gap still exists in our knowledge on how to implement person-centred care coordination in ways that meet individual and family expectations and needs. In addition, more is to be learned about the care experiences of persons receiving person-centred care coordination and their family caregivers.The aim of this dissertation was to fill these gaps by evaluating Health Links by conducting three interconnected studies. In the first study of this dissertation, an implementation evaluation approach was utilized to assess the extent to which the implementation plans of person-centredness, and engagement were operationalized within Health Links. In the second and third studies an impact evaluation approach was employed to assess the care experiences of persons living with complex health and social care needs and their family caregivers after being enrolled in Health Links. In order to assess the care experiences comprehensively, multimethods were used. A patient experience survey was used in the second study and in-depth interviews with enrollees and their caregivers in the third study. The first study concluded that operationalization of implementation plans in network structures like Health Links was faced by numerous challenges. The second study found that the intended components of the Health Links approach (care plan and care coordinator) positively impacted the experience of the enrollees. However, issues with implementation of these components led to a negative care experience. The third study showed that despite being enrolled in an initiative that aimed at delivering person-centred care coordination, persons living with complex health and social care needs and their family caregivers were still shouldering the main burden of care coordination. The findings of the three studies can guide policy makers, planners, implementers, and evaluators on how to better plan, deliver and evaluate person-centred care coordination (integrated patient care) interventions.
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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 | 0.028 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| 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".