Harmonizing allergy care–integrated care pathways and multidisciplinary approaches
Bibliographic record
Abstract
There is a wide time gap between the publication of evidence and the application of new knowledge into routine clinical practice. The consequence is sub-optimal outcomes, particularly concerning for long-term relapsing/remitting conditions such as allergic diseases. In response, there has been a proliferation of published guidelines which systematically review evidence for the gold-standard management of most allergic disorders. However, this has not necessarily been followed by improved outcomes, partly due to a lack of coordination across the patient pathway. This has become known as the "second translational gap". A proposed solution is the development and implementation of integrated care pathways (ICPs) to optimize patient outcomes, with the notion that evidence-based medicine requires evidence-based implementation. ICP implementation is shown to improve short-term outcomes for acute conditions and routine surgery, including reduced length of hospital stay, improved documentation and improved patient safety. However, this improvement is not reflected in patient experience or patient-centered functional outcomes. The implementation of life-long, cost-effective interventions within comprehensive pathways requires a deep appreciation for complexity within allergy care. We promote an evidence-based methodology for the implementation of ICPs for allergic disorders in which all stakeholders in allergy care are positioned equally and encouraged to contribute, particularly patients and their caregivers. This evidence-based process commences with scoping the unmet needs, followed by stakeholder mapping. All stakeholders are invited to meetings to develop a common vision and mission through the generation of action/effect diagrams which helps build concordance across the agencies. Dividing the interventions into achievable steps and reviewing with plan/do/study/act cycles will gradually modify the pathway to achieve the best outcomes. While the management guidelines provide the core knowledge, the key component of implementation involves education, training, and support of all healthcare professionals (HCPs), patients and their caregivers. The pathways should define the level of competence required for each clinical task. It may be useful to leave the setting of care delivery or the specific HCP involved undefined to account for variable patterns of health service delivery as well as local socioeconomic, ethnic, environmental, and political imperatives. In all cases, where competence is exceeded, it is necessary to refer to the next stage in the pathway. The success and sustainability of ICPs would ideally be judged by patient experience, health outcomes, and health economics. We provide examples of successful programs, most notably from Finland, but recommend that further research is required in diverse settings to optimize outcomes worldwide.
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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 | 0.084 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.006 | 0.035 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".