Evidence map›Paper›PMID 42229883›Full record

ArticleJMIR medical informatics2026

Near-Real-Time Clinical Trial Accrual Dashboard in a National Cancer Institute-Designated Cancer Center: Mixed Methods Implementation Study.

Sam Pepper, Isuru Ratnayake, Mohammod Mahmudur Rahman, Md Robiul Islam Talukder, Md Saiful Islam Saif, Olivia Rippee, Ananda Jayawardhana, Tara Lin, Natalie Streeter, Byron Gajewski and 3 more

Abstract read
In one paragraph

Article in JMIR medical informatics, 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

13 authors.

Sam PepperUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0003-0696-3820
Isuru RatnayakeUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0001-9596-781X
Mohammod Mahmudur RahmanUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0009-0000-4659-9299
Md Robiul Islam TalukderUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0009-0007-6585-3281
Md Saiful Islam SaifUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0009-0008-7066-0262
Olivia RippeeUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0009-0007-3222-4331
Ananda JayawardhanaDepartment of Mathematics and Physics, Pittsburg State University, Pittsburg, KS, United States.ORCID 0000-0002-8582-8880
Tara LinUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0002-0242-6449
Natalie StreeterUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0003-3309-1992
Byron GajewskiUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0001-7589-8247
Jo WickUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0003-3445-3211
Matthew S MayoUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0001-7264-1577
Dinesh Pal MudaranthakamUniversity of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0001-9767-1158

Funding

Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
NCI NIH HHS P30CA168524
6 · The paper itself

Abstract

backgroundClinical trial accrual monitoring is a critical component of trial operations, influencing feasibility, timeliness, and scientific validity. Despite its importance, many National Cancer Institute-designated cancer centers continue to rely on static spreadsheets or manually generated reports that provide delayed and incomplete insight for study teams. These limitations hinder timely identification of recruitment challenges, reduce transparency across stakeholders, and constrain proactive operational decision‑making. Scalable, institution‑wide systems that support near-real‑time accrual oversight remain uncommon in academic settings.

objectiveThis study aimed to design, implement, and operationalize a near-real‑time clinical trial accrual dashboard within a National Cancer Institute-designated cancer center, and to evaluate its use, adoption, and early operational impact on accrual monitoring workflows.

methodsWe developed an enterprise accrual dashboard integrating daily extracts from the institutional clinical trial management system with automated data quality validation and time series accrual forecasting. The system supported multiple stakeholder roles through role‑based access and was deployed within existing governance and oversight workflows. Implementation and evaluation were guided by the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework and the Guidelines and Checklist for the Reporting on Digital Health Implementations framework, with system logs used to assess reach and adoption, and qualitative operational feedback used to characterize use in practice. IMPLEMENTATION (RESULTS): From May 2022 to May 2026, the dashboard was used institution wide for monitoring therapeutic and nontherapeutic trials, logging 1605 unique user sessions across investigators, coordinators, data managers, and leaders. Automated daily validation enabled earlier detection and correction of missing or invalid accrual data, improving the reliability of institutional reporting over time. The dashboard replaced manual monthly reports with continuous monitoring and was incorporated into routine operational and leadership reviews, enabling earlier identification of lagging studies and more timely discussions regarding resource allocation and recruitment strategies. Accrual forecasting models demonstrated stable in sample and out of sample performance and were used to support anticipatory planning rather than prescriptive decision making. Initial increases in data correction workload and user resistance decreased as workflows matured and data transparency became normalized.

conclusionsImplementation of a near-real‑time accrual dashboard within an academic cancer center is feasible and sustainable and can meaningfully improve accrual oversight by strengthening data quality, transparency, and integration into routine workflows. The primary value of such systems lies not only in visualization or analytics but in their ability to shift accrual monitoring from retrospective reporting to proactive, institution‑wide operational review. With appropriate governance and clinical trial management system infrastructure, similar dashboards are transferable to other research centers seeking to modernize trial oversight.

Indexed as

Cancer Care FacilitiesClinical Trials as TopicPatient SelectionDashboard SystemsHumansNational Cancer Institute (U.S.)NeoplasmsUnited Statescancer center operationsclinical trial accrualdata qualityimplementation scienceR Shiny dashboard

Identifiers

PMID42229883
PMCPMC13273207

What OpenQuestion holds

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LicenceCC BY
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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.