Evidence map›Paper›PMID 35903155›Full record

ArticleOpen forum infectious diseases2022

Implementation of Outpatient Infectious Diseases E-Consults at a Safety Net Healthcare System.

Richard J Medford, Madison Granger, Madison Pickering, Christoph U Lehmann, Christian Mayorga, Helen King

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

6 authors at 3 institutions in 1 country.

Richard J MedfordDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0001-9814-8043
Madison GrangerUniversity of Texas Southwestern Medical School, Dallas, Texas, USA.ORCID https://orcid.org/0000-0002-6909-7774
Madison PickeringClinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Christoph U LehmannClinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0001-9559-4646
Christian MayorgaDivision of Digestive and Liver Diseases, Parkland Health and Hospital System, Dallas, Texas, USA.
Helen KingDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Parkland Health & Hospital System · USThe University of Texas Southwestern Medical Center · USUniversity of Chicago · US

Funding

UT Southwestern Center for Translational MedicineUL1TR003163 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2021 to 2025
$39.3M
NCATS NIH HHS UL1 TR003163
6 · The paper itself

Abstract

Background: Safety net healthcare systems have high patient volumes and significant demands for specialty care including infectious diseases (ID) consultations. Electronic ID consults (E-consults) can lessen this burden by providing an alternative to face-to-face ID referrals and decreasing financial, time, and travel constraints on patients. This system could increase access to ID care for patients in limited-resource settings. Methods: We described characteristics of all outpatient ID E-consults at Parkland Health in Dallas, Texas, from March 2018 to February 2021. We used modeling to determine which characteristics influenced conversion of E-consults to clinic visits and integrated these data into a predictive model for face-to-face conversion. Results: For 725 E-consults, common E-consult topics included 118 (16%) latent tuberculosis, 116 (16%) syphilis, and 76 (10%) gastrointestinal infections. Nearly two-thirds of E-consults (456 [63%]) were requested by primary care providers. The majority (78%) were resolved without a face-to-face ID visit. Osteomyelitis, nontuberculous mycobacterial, and gastrointestinal questions frequently required face-to-face visits at rates of 65%, 49%, and 32%, respectively. Our logistic regression model predicted the need for a face-to-face visit with 80% accuracy and an area under the receiver operating characteristic curve of 0.72. Conclusions: An outpatient ID E-consult program at a safety net healthcare system was an effective tool to provide timely input on common ID topics. E-consults were requested by a range of providers, and most were completed without a face-to-face visit. Predictive modeling identified important characteristics of E-consults and predicted conversion to face-to-face visits with reasonable accuracy.

Identifiers

PMID35903155
PMCPMC9315945
OpenAlexW4285731428

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.