A scoping review of adult chronic kidney disease clinical pathways for primary care
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) affects ∼10% of the adult population. The majority of patients with CKD are managed by primary care physicians, and despite the availability of effective treatment options, the use of evidence-based interventions for CKD in this setting remains suboptimal. Clinical pathways have been identified as effective tools to guide primary care physicians in providing evidence-based care. We aimed to describe the availability, characteristics and credibility of clinical pathways for adult CKD using a scoping review methodology. METHODS: We searched Medline, Embase, CINAHL and targeted Internet sites from inception to 31 October 2014 to identify studies and resources that identified adult CKD clinical pathways for primary care settings. Study selection and data extraction were independently performed by two reviewers. RESULTS: From 487 citations, 41 items were eligible for review: 7 published articles and 34 grey literature resources published between 2001 and 2014. Of the 41 clinical pathways, 32, 24 and 22% were from the UK, USA and Canada, respectively. The majority (66%, n = 31) of clinical pathways were static in nature (did not have an online interactive feature). The majority (76%) of articles/resources reported using one or more clinical practice guidelines as a resource to guide the clinical pathway content. Few articles described a dissemination and evaluation plan for the clinical pathway, but most reported the targeted end-users. CONCLUSIONS: Our scoping review synthesized available literature on CKD clinical pathways in the primary care setting. We found that existing clinical pathways are diverse in their design, content and implementation. These results can be used by researchers developing or testing new or existing clinical pathways and by practitioners and health system stakeholders who aim to implement CKD clinical pathways in clinical practice.
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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 | 0.043 | 0.187 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.038 | 0.043 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".