Evidence map›Paper›PMID 30899905›Full record

ArticleMayo Clinic proceedings. Innovations, quality & outcomes2019

Provider Survey on Automated Clinical Decision Support for Cardiovascular Risk Assessment.

Alisha P Chaudhry, Sujith Samudrala, Francisco Lopez-Jimenez, Jane L Shellum, Rick A Nishimura, Rajeev Chaudhry, Hongfang Liu, Adelaide M Arruda-Olson

Open access · goldAbstract read
In one paragraph

Article in Mayo Clinic proceedings. Innovations, quality & outcomes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Alisha P ChaudhryDepartment of Cardiovascular Medicine, Mayo Clinic and Mayo Foundation, Rochester, MN.
Sujith SamudralaDepartment of Cardiovascular Medicine, Mayo Clinic and Mayo Foundation, Rochester, MN.
Francisco Lopez-JimenezDepartment of Cardiovascular Medicine, Mayo Clinic and Mayo Foundation, Rochester, MN.
Jane L ShellumCenter for Translational Informatics and Knowledge Management, Mayo Clinic and Mayo Foundation, Rochester, MN.
Rick A NishimuraDepartment of Cardiovascular Medicine, Mayo Clinic and Mayo Foundation, Rochester, MN.
Rajeev ChaudhryDepartment of Internal Medicine and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic and Mayo Foundation, Rochester, MN.
Hongfang LiuDepartment of Health Science Research, Mayo Clinic and Mayo Foundation, Rochester, MN.
Adelaide M Arruda-OlsonDepartment of Cardiovascular Medicine, Mayo Clinic and Mayo Foundation, Rochester, MN.
Mayo Clinic · US

Funding

Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement - Dr. Timothy Curry)UL1TR002377 · NCATS · MAYO CLINIC ROCHESTER · PI VESNA D GAROVIC · 2017 to 2026
$78.4M
Novel Informatics Approaches for Ascertainment of PAD Status and Adverse OutcomesK01HL124045 · NHLBI · MAYO CLINIC ROCHESTER · PI ARRUDA-OLSON, ADELAIDE MARIA MARTINS · 2015 to 2019
$820k
NCATS NIH HHS UL1 TR002377NHLBI NIH HHS K01 HL124045
6 · The paper itself

Abstract

objectiveTo investigate provider opinions regarding a clinical decision support (CDS) system for cardiovascular risk assessment and for the creation of a replacement system.

methodsFrom March to April 2018, an invitation letter with a link to a self-administered web-based survey was sent via e-mail to 279 providers with primary appointment in the Department of Cardiovascular Medicine, Mayo Clinic, Rochester. The e-mail was sent to providers on March 8, 2018 and the survey closed on April 16, 2018.

resultsOne hundred providers responded to the survey yielding an overall response rate of 35.8%. Of these, 52 (52%) indicated they had used the cardiovascular (CV) risk profile CDS system and were classified as users and prompted to continue the survey. Among users, 42 (80.8%) indicated use of the CDS was either important (25; 48.1%) or very important (17; 32.7%) in their clinical practice; 45 (86.5%) responded that the system was very easy (17; 32.7%) or easy (28; 53.8%) to use. In addition, 48 (96.0%) users indicated that the CV risk profile supported their thought process at the point-of-care; 47 (97.9%) users indicated similar functionalities should be implemented into the new electronic health record system and 41 (85.4%) users reported new functionalities should also be incorporated.

conclusionsFor most users, the CDS system was easy to use and supported clinical thought process at the point-of-care. Users also felt their practice was supported and should continue to be supported by CDS systems providing individualized patient information at the point-of-care.

Indexed as

CDS, clinical decision supportCV, cardiovascularEHR, electronic health record

Identifiers

PMID30899905
PMCPMC6410336
OpenAlexW2917244870

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.