Health system interventions to integrate genetic testing in routine oncology services: A systematic review
Bibliographic record
Abstract
BACKGROUND: Integration of genetic testing into routine oncology care could improve access to testing. This systematic review investigated interventions and the tailored implementation strategies aimed at increasing access to genetic counselling and testing and identifying hereditary cancer in oncology. METHODS: The search strategy results were reported using the PRISMA statement and four electronic databases were searched. Eligible studies included routine genetic testing for breast and ovarian cancer or uptake after universal tumour screening for colorectal or endometrial cancer. The titles and abstracts were reviewed and the full text articles screened for eligibility. Data extraction was preformed using a designed template and study appraisal was assessed using an adapted Newcastle Ottawa Scale. Extracted data were mapped to Proctor's et al outcomes and the Consolidated Framework for Implementation Research and qualitatively synthesised. RESULTS: Twenty-seven studies, published up to May 2020, met the inclusion criteria. Twenty-five studies ranged from poor (72%), fair to good (28%) quality. Most interventions identified were complex (multiple components) such as; patient or health professional education, interdisciplinary practice and a documentation or system change. Forty-eight percent of studies with complex interventions demonstrated on average a 35% increase in access to genetic counselling and a 15% increase in testing completion. Mapping of study outcomes showed that 70% and 32% of the studies aligned with either the service and client or the implementation level outcome and 96% to the process or inner setting domains of the Consolidated Framework for Implementation Research. CONCLUSION: Existing evidence suggests that complex interventions have a potentially positive effect towards genetic counselling and testing completion rates in oncology services. Studies of sound methodological quality that explore a greater breadth of pre and post implementation outcomes and informed by theory are needed. Such research could inform future service delivery models for the integration of genetics into oncology services.
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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 | 0.018 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".