Evidence map›Paper›PMID 38085196›Full record

ArticleAmerican journal of preventive medicine2024

Association of Electronic Self-Scheduling and Screening Mammogram Completion.

Kimberly J Waddell, Keshav Goel, Sae-Hwan Park, Kristin A Linn, Amol S Navathe, Joshua M Liao, Caitlin McDonald, Catherine Reitz, Jake Moore, Steve Hyland and 1 more

Abstract read
In one paragraph

Article in American journal of preventive medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Reply.Journal of the American College of Radiology : JACR · 2025
    Article
  5. Using Self-Scheduling to Improve Screening Mammography Completion Rates.Journal of the American College of Radiology : JACR · 2025
    Article
  6. Observational
  7. Review
  8. Article
  9. Article
  10. 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

11 authors.

Kimberly J WaddellPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Corporal Michael J. Cresencz VA Medical Center, Philadelphia, PA. Electronic address: Kimberly.Waddell@pennmedicine.upenn.edu.
Keshav GoelPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Sae-Hwan ParkCenter for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA.
Kristin A LinnCenter for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania.
Amol S NavathePerelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Corporal Michael J. Cresencz VA Medical Center, Philadelphia, PA.
Joshua M LiaoLeonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Department of Medicine, University of Washington, Seattle, WA.
Caitlin McDonaldCenter for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia, PA.
Catherine ReitzCenter for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia, PA.
Jake MoorePerelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Steve HylandPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Shivan J MehtaPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA; Center for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia, PA.

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
I-SCREEN: Increasing Screening for Cancer using a Randomized Evaluation of EHR-based NudgesR61AG068947 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LIAO, JOSHUA M, MEHTA, SHIVAN JATIN · 2020 to 2021
$624k
NCI NIH HHS K08 CA234326NIA NIH HHS R33 AG068947NIA NIH HHS R61 AG068947
6 · The paper itself

Abstract

introductionThe purpose of this study was to evaluate if an electronic health record (EHR) self-scheduling function was associated with changes in mammogram completion for primary care patients who were eligible for a screening mammogram using U.S. Preventive Service Task Force recommendations.

methodsThis was a retrospective cohort study (September 1, 2014-August 31, 2019, analyses completed in 2022) using a difference-in-differences design to examine mammogram completion before versus after the implementation of self-scheduling. The difference-in-differences estimate was the interaction between time (pre-versus post-implementation) and group (active EHR patient portal versus inactive EHR patient portal). The primary outcome was mammogram completion among all eligible patients, with completion defined as receiving a mammogram within 6 months post-visit. The secondary outcome was mammogram completion among patients who received a clinician order during their visit.

resultsThe primary analysis included 35,257 patient visits. The overall mammogram completion rate in the pre-period was 22.2% and 49.7% in the post-period. EHR self-scheduling was significantly associated with increased mammogram completion among those with an active EHR portal, relative to patients with an inactive portal (adjusted difference 13.2 percentage points [95% CI 10.6-15.8]). For patients who received a clinician mammogram order at their eligible visit, self-scheduling was significantly associated with increased mammogram completion among patients with an active EHR portal account (adjusted difference 14.7 percentage points, [95% CI 10.9-18.5]).

conclusionsEHR-based self-scheduling was associated with a significant increase in mammogram completion among primary care patients. Self-scheduling can be a low-cost, scalable function for increasing preventive cancer screenings.

Indexed as

Early Detection of CancerPreventive Health ServicesElectronic Health RecordsHumansMammographyRetrospective Studies

Identifiers

PMID38085196
PMCPMC10922640

What OpenQuestion holds

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Registered trials

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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.