Bibliographic record
Abstract
Objectives: To explore the practical barriers to, and implications of, incorporating genomic technologies in the primary care setting. In evaluating the primary care mission and anticipated role of genomic medicine in conversation with one another, I discuss the ways in which the primary care philosophy problematizes innovations afforded to clinical medicine through whole genome sequencing. I discuss these themes in relation to the evaluation frameworks that must precede full integration, specifically the Analytic validity, Clinical validity, Clinical Utility and Ethical, legal social considerations (ACCE) model. Finally, my analysis will consider the added ethical nuances for integrating genomic medicine in the wake of new standards for healthcare delivery in the U.S.Methods: I review the literature concerning 1) models for evaluating the applicability of emerging genomic technologies in the primary care setting, namely the ACCE model proposed by the Center for Disease Control, and 2) anticipated changes to primary care delivery through proposed healthcare legislation.Results: Three main facets of primary care delivery problematize full integration of genomic medicine in clinical practice. They include: primary care providers' propensity to maintain therapeutic relationships with patients over the lifecourse, acuity to community health patterns, and gaps in genetic/genomic-specific knowledge among practicing clinicians. Implementation of genomic medicine requires that technologies be adaptable to the heterogeneity of the primary care clinic, in both the diverse populations it serves and broad spectrum of resource availability.Conclusions: The rapid pace at which genomic technology has fundamentally altered the direction of medical research scene is extraordinary to say the least. The potential benefits for incorporating these innovations depict a clinical landscape that predicts and prevents disease before it manifests, and cares for patients using treatments that are tailored to their own genetic person. The primary care arena presents unique challenges to the evaluation, diffusion and translation of genomic technologies. Yet the same aspects that present limitations also reinforce the reasons why the primary care setting is a critical forum in which to operationalize genomic medicine in practice. With so much dialogue generated around ushering in a new era of medicine, it is unclear whether this is celebrating the novelty of the genomic revolution, or the reinvigoration of a longstanding clinical tradition in patient-centered primary care.
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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 | 0.118 | 0.151 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.087 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.016 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".