Interventions to improve care coordination between primary healthcare and oncology care providers: a systematic review
Bibliographic record
Abstract
Coordination of patient care between primary care and oncology care providers is vital to care quality and outcomes across the cancer continuum, yet it is known to be challenging. We conducted a systematic review to evaluate current or new models of care and/or interventions aimed at improving coordination between primary care and oncology care providers for patients with adult breast and/or colorectal cancer. MEDLINE, EMBASE, CINAHL, Cochrane Library Database of Systematic Reviews, and the Centre for Reviews and Dissemination were searched for existing English language studies published between January 2000 and 15 May 2015. Systematic reviews, meta-analyses, randomised controlled trials (RCTs) and non-randomised studies were included if they evaluated a specific model/intervention that was designed to improve care coordination between primary care and oncology care providers, for any stage of the cancer continuum, for patients with adult breast and/or colorectal cancer. Two reviewers extracted data and assessed risk of bias. Twenty-two studies (5 systematic reviews, 6 RCTs and 11 non-randomised studies) were included and varied with respect to the targeted phase of the cancer continuum, type of model or intervention tested, and outcome measures. The majority of studies showed no statistically significant changes in any patient, provider or system outcomes. Owing to conceptual and methodological limitations in this field, the review is unable to provide specific conclusions about the most effective or preferred model/intervention to improve care coordination. Imprecise results that lack generalisability and definitiveness provide limited evidence to base the development of future interventions and policies. TRIAL REGISTRATION NUMBER: CRD42015025006.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".