Evidence map›Paper›PMID 37422162›Full record

ArticleJournal of the American College of Radiology : JACR2023

Patient, Provider, and Practice Characteristics Predicting Use of Diagnostic Imaging in Primary Care: Cross-Sectional Data From the National Ambulatory Medical Care Survey.

Sue Y Yi, Anand K Narayan, Randy C Miles, Maria D Martin Rother, Jessica B Robbins, Efren J Flores, Andrew B Ross

Abstract read
In one paragraph

Article in Journal of the American College of Radiology : JACR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

7 authors.

Sue Y YiDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. Electronic address: https://twitter.com/SueYYiii.
Anand K NarayanVice Chair of Equity, Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin; Assistant Editor of JACR and Vice Chair, ACR Patient and Family Centered Care Outreach Committee. Electronic address: https://twitter.com/AnandKNarayan.
Randy C MilesChief of Breast Imaging, Department of Radiology, Denver Health, Denver, Colorado. Electronic address: https://twitter.com/RMilesMD.
Maria D Martin RotherDirector of Diversity and Inclusion, Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. Electronic address: https://twitter.com/DanielaMartinMD.
Jessica B RobbinsVice Chair of Faculty Development and Enrichment, Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. Electronic address: https://twitter.com/JRobbinsMD.
Efren J FloresMassachusetts General Hospital, Boston, Massachusetts, and Associate Chair, Equity, Inclusion and Community Health, Massachusetts General Brigham Enterprise Radiology, Boston, Massachusetts; Associate Editor of JACR. Electronic address: https://twitter.com/EJFloresMD.
Andrew B RossFellowship Director-Musculoskeletal Imaging and Intervention, Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, CSC, Madison, Wisconsin 53792. Electronic address: ARoss@uwhealth.org.

Funding

Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
Health Opportunities & Promoters to Enhance Screening for Lung Cancer (Hopes for Lung Cancer)K08CA270430 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Efren Flores · 2023 to 2026
$1.1M
NCI NIH HHS K08 CA270430NIGMS NIH HHS T32 GM140935
6 · The paper itself

Abstract

objectiveTo determine imaging utilization rates in outpatient primary care visits and factors influencing likelihood of imaging use.

methodsWe used 2013 to 2018 National Ambulatory Medical Care Survey cross-sectional data. All visits to primary care clinics during the study period were included in the sample. Descriptive statistics on visit characteristics including imaging utilization were calculated. Logistic regression analyses evaluated the influence of a variety of patient-, provider-, and practice-level variables on the odds of obtaining diagnostic imaging, further subdivided by modality (radiographs, CT, MRI, and ultrasound). The data's survey weighting was accounted for to produce valid national-level estimates of imaging use for US office-based primary care visits.

resultsUsing survey weights, approximately 2.8 billion patient visits were included. Diagnostic imaging was ordered at 12.5% of visits with radiographs the most common (4.3%) and MRI the least common (0.8%). Imaging utilization was similar or greater among minority patients compared with White, non-Hispanic patients. Physician assistants used imaging at higher rates than physicians, in particular CT at 6.5% of visits compared with 0.7% for doctors of medicine and doctors of osteopathic medicine (odds ratio 5.67, 95% confidence interval 4.07-7.88).

conclusionDisparities in rates of imaging utilization for minorities seen in other health care settings were not present in this sample of primary care visits, supporting that access to primary care is a path to promote health equity. Higher rates of imaging utilization among advanced-level practitioners highlight an opportunity to evaluate imaging appropriateness and promote equitable, high-value imaging among all practitioners.

Indexed as

Ambulatory CareHealth PromotionCross-Sectional StudiesDiagnostic ImagingHealth Care SurveysHumansPrimary Health CareUnited StatesAdvanced practice providershealth equityimaging utilizationprimary care

Identifiers

PMID37422162
PMCPMC11318093

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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.