Exploring the inclusion of dental providers on interprofessional healthcare teams treating patients with chronic obstructive pulmonary disease: a rapid review
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the world. Emerging concepts like One Health, integrated care models for COPD, and associations between oral and respiratory health are innovative ways to approach COPD treatment. This study explored contemporary evidence on the inclusion of dental providers on interprofessional healthcare teams treating patients with COPD. The first objective was to explore the current state of interprofessional care for COPD, and the second objective was to explore dentistry used in interprofessional care. A rapid review was conducted from January–June 2020 using Scopus and PubMed. Upon assessing for duplication and relevance, 85 articles were included for Objective 1, and 194 for Objective 2. The literature suggests that when dental providers are included on interprofessional healthcare teams, treatment outcomes for patients with multi-morbid, chronic disease such as COPD, are improved. The papers collected for review suggest that educational and clinical programs should implement interprofessional collaboration when treating chronic diseases. Healthcare teams can utilize the expertise of professionals outside the traditional medical field to better understand patients’ needs. Healthcare administration should consider a One Health approach when developing COPD treatment guidelines. We believe our results are transferable to the Canadian healthcare system. The collaborative nature and holistic philosophy of a One Health approach provides a novel way to develop policies and procedures that can effectively address the burden of COPD.
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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 | 0.016 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".