Evidence map›Paper›PMID 39581259›Full record

ArticleContemporary clinical trials2025

Increasing screening for breast cancer using a randomized evaluation of electronic health record nudges: Design and rationale of the I-screen clinical trial.

Kimberly J Waddell, Shivan J Mehta, Joshua M Liao, Kristin A Linn, Saehwan Park, Corinne M Rhodes, Caitlin Brophy, Catherine Reitz, Deborah S Cousins, Keyirah Williams and 4 more

Abstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in Contemporary clinical trials, 2025. 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

14 authors.

Kimberly J WaddellPerelman School of Medicine, University of Pennsylvania, USA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, USA; Leonard Davis Institute for Health Economics, University of Pennsylvania, USA; Center for Health Care Transformation and Innovation, University of Pennsylvania, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA. Electronic address: Kimberly.waddell@pennmedicine.upenn.edu.
Shivan J MehtaPerelman School of Medicine, University of Pennsylvania, USA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, USA; Leonard Davis Institute for Health Economics, University of Pennsylvania, USA; Center for Health Care Transformation and Innovation, University of Pennsylvania, USA.
Joshua M LiaoLeonard Davis Institute for Health Economics, University of Pennsylvania, USA; Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA; Program on Policy Evaluation and Learning, Dallas, TX, USA.
Kristin A LinnPerelman School of Medicine, University of Pennsylvania, USA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, USA; Leonard Davis Institute for Health Economics, University of Pennsylvania, USA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, USA.
Saehwan ParkPerelman School of Medicine, University of Pennsylvania, USA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, USA.
Corinne M RhodesPerelman School of Medicine, University of Pennsylvania, USA.
Caitlin BrophyCenter for Health Care Transformation and Innovation, University of Pennsylvania, USA.
Catherine ReitzCenter for Health Care Transformation and Innovation, University of Pennsylvania, USA.
Deborah S CousinsPerelman School of Medicine, University of Pennsylvania, USA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, USA; Penn Medical Ethics and Health Policy, University of Pennsylvania, USA.
Keyirah WilliamsCenter for Health Care Transformation and Innovation, University of Pennsylvania, USA.
Esther J ThatcherUniversity Hospitals, Cleveland, OH, USA.
Ryan MuskinUniversity Hospitals, Cleveland, OH, USA.
Peter J PronovostUniversity Hospitals, Cleveland, OH, USA; School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Amol S NavathePerelman School of Medicine, University of Pennsylvania, USA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, USA; Leonard Davis Institute for Health Economics, University of Pennsylvania, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA; Penn Medical Ethics and Health Policy, University of Pennsylvania, USA.

Funding

I-SCREEN: Increasing Screening for Cancer using a Randomized Evaluation of EHR-based NudgesR33AG068947 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LIAO, JOSHUA M, MEHTA, SHIVAN JATIN · 2022 to 2024
$1.7M
Behavioral Economics and Population-based Colorectal Cancer ScreeningK08CA234326 · NCI · UNIVERSITY OF PENNSYLVANIA · PI MEHTA, SHIVAN JATIN · 2018 to 2022
$1.3M
NCI NIH HHS K08 CA234326NIA NIH HHS R33 AG068947
6 · The paper itself

Abstract

backgroundRoutine mammogram screening is critical for early detection of breast cancer. However, screening rates are below national targets, with persistent disparities among sub-populations. The purpose of this trial is to examine the effectiveness of a multi-component nudge intervention to increase breast cancer screening among eligible primary care patients.

methodsThis is a two-phase, multisite, pragmatic cluster randomized clinical trial. In the first phase, two concurrent trials (trial A, B) will test the effectiveness of a multi-component nudge intervention that leverages the electronic health record (EHR) for increasing mammogram screening. The second phase includes a replication trial at an additional site. In Trial A, primary care clinics (n = 30) will be randomized 2:1 to a nudge intervention or usual care. Eligible clinicians and patients within the intervention clinics will receive the intervention. Patients identified as high-risk for mammogram non-completion in the intervention arm will be further randomized 1:1 to receive an intensification nudge. In Trial B, primary care clinicians (n = 82) will be randomized 1:1 to a nudge intervention or usual care. The primary outcome is mammogram completion within three months of the eligible visit. ANALYSIS: Outcomes will be evaluated using generalized estimating equations (GEE) to address clinic-level clustering. GEE models will also be fit to evaluate the impact of the intensification nudge on mammogram completion.

conclusionIf successful, this trial provides a blueprint for leveraging scalable multi-component nudge interventions for clinicians and patients to improve cancer screening rates.

Indexed as

Breast NeoplasmsEarly Detection of CancerElectronic Health RecordsMammographyRandomized Controlled Trials as TopicAdultAgedFemaleHumansMiddle AgedMulticenter Studies as TopicPragmatic Clinical Trials as TopicPrimary Health CareResearch DesignBreast cancerBreast cancer screeningElectronic health recordHigh-riskMammogramNudge

Identifiers

PMID39581259
PMCPMC11783373

What OpenQuestion holds

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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.