Barriers and facilitators to next-generation sequencing use in United States oncology settings: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aim: Next-generation sequencing (NGS) of solid tumors can inform treatment decisions; however, uptake remains low. This objective of this systematic review was to identify barriers to and facilitators of NGS in US oncology settings.Materials & methods: Embase and MEDLINE were searched in March 2023 for articles published from 2012 to 2023 on barriers and facilitators of NGS adoption for solid tumors. Surveys, interviews and observational studies were eligible. Studies on genetic testing for hereditary cancers and non-US studies were excluded. The Motheral scale, Joanna Briggs Institute critical appraisal checklist and McGill Mixed Methods Appraisal Tool were used to assess study quality. Data were synthesized narratively.Results: Twenty-one studies were included. Study participants were clinicians, payers and administrators. Key barriers included complex reimbursement processes and uncertainties around clinical utility. Including recommendations for NGS in clinical practice guidelines was a key facilitator, although insurance policies were often more restrictive than guideline recommendations.Conclusion: Uptake of NGS is increasing but barriers remain. Changes to the current reimbursement frameworks are needed to increase access to NGS. The impact of implementing the 2018 National Coverage Determination, which allows access to NGS for all Medicare beneficiaries with advanced cancer, is not yet evident in the published literature.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it