Evidence map›Paper›PMID 42044630›Full record

ArticleJMIR cancer2026

Patient and Provider Experiences With Precision Oncology: Qualitative Descriptive Study at the Department of Veterans Affairs.

Daniel Becker, Kenneth Csehak, Alexander Barbaro, Christian Miller, Antoinette Vo, Stefanie Roman, Danil Makarov, Scott Sherman, Allison Squires

Abstract read
In one paragraph

Article in JMIR cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Daniel BeckerVA NYHHS (Veterans Affairs New York Harbor Healthcare System), New York, NY, United States.ORCID 0000-0001-7230-8432
Kenneth CsehakNYU Langone, 550 First Avenue, New York, NY, 10016, United States, 1 212-263-2868.ORCID 0000-0003-0953-057X
Alexander BarbaroNorthwell Health, New York, NY, United States.ORCID 0009-0001-3262-2248
Christian MillerNYU Langone, 550 First Avenue, New York, NY, 10016, United States, 1 212-263-2868.ORCID 0000-0001-5736-9712
Antoinette VoVA NYHHS (Veterans Affairs New York Harbor Healthcare System), New York, NY, United States.ORCID 0009-0008-1095-0364
Stefanie RomanVA NYHHS (Veterans Affairs New York Harbor Healthcare System), New York, NY, United States.ORCID 0000-0002-0778-1239
Danil MakarovVA NYHHS (Veterans Affairs New York Harbor Healthcare System), New York, NY, United States.ORCID 0000-0002-0565-9272
Scott ShermanVA NYHHS (Veterans Affairs New York Harbor Healthcare System), New York, NY, United States.ORCID 0000-0003-1752-7303
Allison SquiresNYU Langone, 550 First Avenue, New York, NY, 10016, United States, 1 212-263-2868.ORCID 0000-0002-5238-2122

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Precision oncology (PO) improves and extends the lives of patients living with cancer, but multiple studies have documented its underuse in practice. Specifically, studies note a significant lack of PO use within the Veterans Affairs (VA) medical system. A paucity of implementation of PO in oncologic practice poses a significant barrier to providing the most up-to-date guideline-based care. Objective: While several studies have explored determinants of PO use, we sought to contribute to the body of knowledge by additionally focusing on the unique perspectives of patients, as well as conducting a comprehensive study within the VA medical system, the United States' largest single-payer health care system. We conducted interviews with both patients and providers at multiple VA sites to identify and characterize barriers and facilitators of PO use in clinical care. Methods: Using a qualitative descriptive approach, we conducted semistructured interviews with 17 patients with cancer and 16 oncology providers recruited from multiple VA sites. Cancer types included prostate, gastrointestinal, and lung. Data were analyzed via a team-based coding approach using directed content analysis. Data were coded and then aggregated into themes and mapped to the Theoretical Domains Framework (TDF) and Behavior Change Wheel sources of behavior (Capability, Opportunity, and Motivation) based on the consensus of the study team. Results: The patient sample consisted of 17 all-male veterans seen at VA oncology clinics in 2022. Participants predominantly self-identified as White (n=9, 52.9%) or Black (n=6, 35.3%), and the majority (n=11, 64.7%) held a high school degree or a higher level of education. The provider sample consisted of 16 physicians, all of whom held MD degrees and practiced oncology. The provider sample represented 6 states, was 50% (8/16) female, and participants averaged 14 years in their current position. The overarching theme was the "Precision Oncology Feedback Loop," which captured the essence of the complex processes involved in facilitating PO care in the VA system. The TDF and Behavior Change Wheel helped categorize findings to identify where issues in the feedback loop could facilitate or generate barriers to care. Conclusions: Our findings expand on the current literature by highlighting both patient and provider experiences across key TDF domains (Environmental Context and Resources, Knowledge, Memory, and Attention). The conceptual model produced by the analysis illustrates the complexities associated with the implementation. Our findings support the design of multilevel interventions that target increased knowledge or education, improved workflow, and ease of communication to enhance PO delivery.

Indexed as

Health PersonnelMedical OncologyNeoplasmsPrecision MedicineVeteransAgedFemaleHumansMaleMiddle AgedQualitative ResearchUnited StatesUnited States Department of Veterans Affairshealth equityhealth servicesoncologyprecision oncologyqualitative

Identifiers

PMID42044630
PMCPMC13120791

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.