Evidence map›Paper›PMID 31592972›Full record

ArticleJournal of lower genital tract disease2019

Effect of an Electronic Health Record Decision Support Alert to Decrease Excess Cervical Cancer Screening.

Deanna Teoh, Rachel I Vogel, Adam Langer, Jinai Bharucha, Melissa A Geller, Eileen Harwood, Shalini Kulasingam, Genevieve B Melton

Abstract read
In one paragraph

Article in Journal of lower genital tract disease, 2019. 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. Review
  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

8 authors.

Deanna TeohDepartment of Obstetrics, Gynecology & Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN.
Rachel I VogelDepartment of Obstetrics, Gynecology & Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN.
Adam LangerDepartment of Obstetrics, Gynecology & Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN.
Jinai BharuchaDepartment of Obstetrics, Gynecology & Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN.
Melissa A GellerDepartment of Obstetrics, Gynecology & Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN.
Eileen HarwoodSchool of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN.
Shalini KulasingamSchool of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN.
Genevieve B MeltonDepartment of Surgery, Division of Colon & Rectal Surgery, University of Minnesota, Minneapolis, MN.

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Timothy C. Hallstrom · 1998 to 2026
$100.4M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Univ of Minnesota Buidling Interdisciplinary Research Careers in Women's HealthK12HD055887 · NICHD · UNIVERSITY OF MINNESOTA · PI ALLEN, SHARON S, BERGE, JERICA M · 2007 to 2023
$8.6M
NCATS NIH HHS UL1 TR002494NCI NIH HHS P30 CA077598NICHD NIH HHS K12 HD055887
6 · The paper itself

Abstract

objectiveCervical cancer screening is often conducted in excess of current screening guidelines. The objective of this study was to evaluate the effect of an electronic health record (EHR) clinical decision support alert to decrease guideline-nonadherent cervical cancer screening beyond the age limits of screening or posthysterectomy. MATERIALS AND

methodsThe proportion of guideline-nonadherent Pap tests in women younger than 21 years or older than 65 years or posthysterectomy were compared 4 months before and 3 months after implementation of an EHR clinical decision support alert warning providers that a Pap test is not indicated. Providers could cancel the Pap test or override the alert and place the order. Provider characteristics and Pap test indications were summarized by preintervention/postintervention period using descriptive statistics. The proportions of nonindicated Pap tests were compared by intervention period and provider characteristics using generalized estimating equation models.

resultsIn women beyond the screening age limits or posthysterectomy, a total of 388 Pap tests were ordered before intervention, and 313 tests were ordered after intervention. Proportion of guideline-nonadherent tests was similar before (62%) and after intervention (63%); thus, implementation of the clinical decision support alert did not change the proportion of guideline-nonadherent Pap tests ordered (OR = 1.08, 95% CI = 0.77-1.52). It is notable that 52% of guideline-nonadherent tests were ordered by 11 providers. Even when controlling for providers who ordered more than 1 test during the study period, multivariate analysis showed that male providers were more likely to order guideline-nonadherent Pap tests (OR = 2.30, 95% CI = 1.36-3.89); no other differences by provider characteristics were observed.

conclusionsAn EHR clinical decision support alert does not decrease guideline-nonadherent cervical cancer screening. These data suggest efforts to optimize clinical decision support should be focused on other aspects of cervical cancer prevention.

Indexed as

Decision Support TechniquesElectronic Health RecordsProcedures and Techniques UtilizationAdolescentAdultAgedAged, 80 and overEarly Detection of CancerFemaleHumansRetrospective StudiesUterine Cervical NeoplasmsYoung Adult

Identifiers

PMID31592972
PMCPMC6941655

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.