Evidence map›Paper›PMID 40670040›Full record

ArticleBMJ health & care informatics2025

Development and implementation of cancer clinical trial patient screening using an electronic medical record-integrated trial matching system.

Nam Bui, Agnes Nika, Mateo Montoya, Andrea Lopez, Jasmine Newman, Mounica Vaddadi, Rahul Guli, Melissa Rodin, Ashley Robinson, Eben Rosenthal and 4 more

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

14 authors.

Nam BuiStanford Cancer Institute, Stanford, California, USA nambui@stanford.edu.ORCID http://orcid.org/0000-0001-6896-4349
Agnes NikaStanford Cancer Institute, Stanford, California, USA.
Mateo MontoyaXpertDox, Birmingham, Alabama, USA.
Andrea LopezStanford Cancer Institute, Stanford, California, USA.
Jasmine NewmanStanford Cancer Institute, Stanford, California, USA.
Mounica VaddadiStanford HealthCare Cancer Center, Stanford, California, USA.
Rahul GuliStanford HealthCare Cancer Center, Stanford, California, USA.
Melissa RodinStanford HealthCare Cancer Center, Stanford, California, USA.
Ashley RobinsonStanford HealthCare Cancer Center, Stanford, California, USA.
Eben RosenthalVanderbilt University Medical Center, Nashville, Tennessee, USA.
Steven E ArtandiStanford Cancer Institute, Stanford, California, USA.
Sameer AtherXpertDox, Birmingham, Alabama, USA.
Yi PangStanford Cancer Institute, Stanford, California, USA.
Joel NealDepartment of Medicine, Stanford University, Stanford, California, USA.

Funding

Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI MICHAEL KENNEY · 2007 to 2026
$71.4M
NCI NIH HHS P30 CA124435
6 · The paper itself

Abstract

objectivesClinical trial enrolment is critical for the development and approval of novel cancer therapeutics, but patient identification and recruitment to clinical trials remains low and multiple trials accrue slowly or fail to meet accrual goals. Informatics solutions may facilitate clinical trial screening, ideally improving patient engagement and enrolment. Our objective is to develop and implement a system to efficiently screen queried patients for available clinical trials.

methodsAt Stanford, we designed and implemented a personalised clinical trial matching system, integrating our electronic medical record, clinical trials management system and a third-party software-based solution to directly connect providers with clinical research coordinators and appropriate trials.

resultsOver 3 years of a staged rollout, significant increases in clinical trial screening requests and subsequent enrolment have been observed. The total number of screening referrals increased from 20 in the first year to 236 in the third year. Enrolment related to screening referrals, the 'conversion rate', ranged from 16% to 26% of referred patients.

conclusionClinical trial matching systems can increase awareness of available trials and provide a mechanism to increase clinical trial accrual, especially when implemented at the point of care for easy access at treatment decision points. Here, we describe the process of creating and implementing a bespoke clinical trial matching software integrated into the electronic medical record. Having validated the utility of the platform, we will focus on further efforts to drive utilisation through software features.

Indexed as

Clinical Trials as TopicElectronic Health RecordsNeoplasmsPatient SelectionHumansSoftwareBMJ Health InformaticsInformatics

Identifiers

PMID40670040
PMCPMC12273118

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.