Quality of care for chronic conditions: identifying specificities of quality aims based on scoping review and Delphi survey
Bibliographic record
Abstract
There is a growing need to implement high quality chronic care to address the global burden of chronic conditions. However, to our knowledge, there have been no systematic attempts to define and specify aims for chronic care quality. To address this gap, we conducted a scoping review and Delphi survey to establish and validate comprehensive specifications. The Institute of Medicine's (IOM) quality of care definition and aims were used as the foundation. We purposively selected articles from the scientific (n=48) and grey literature (n=26). We sought papers that acknowledged and unpacked the plurality of quality in chronic care and proposed or utilised frameworks, studied their implementation, or investigated at least two IOM quality care aims and implementation. Articles were analysed both deductively and inductively. The findings were validated through a Delphi survey involving 49 international chronic care experts with varied knowledge of, and experience in, low-and-middle-income countries. Considering the natural history of chronic conditions and the journey of a person with a chronic condition, we defined and identified the aims of chronic care quality. The six IOM aims apply with specific meanings. We identified a seventh aim, continuity, which relates to the issue of chronicity. The group endorsed our specifications and several participants gave contextualised interpretations and concrete examples. Chronic conditions pose specific challenges underscoring the relevance of tailoring quality of care aims. The next steps require a tailored definition and specific aims to improve, measure and assure the quality of chronic care.
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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 | 0.297 | 0.300 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.025 | 0.015 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".