Evidence map›Paper›PMID 35402084›Full record

ReviewCurrent dermatology reports2022

Inpatient Teledermatology: a Review.

Joseph Mocharnuk, Trevor Lockard, Corey Georgesen, Joseph C English

Open access · bronzeAbstract readReview
In one paragraph

Review in Current dermatology reports, 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
0.9field-weighted citation impact, top 24% 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, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. Review of Teledermatology: Lessons Learned from the COVID-19 Pandemic.American journal of clinical dermatology · 2024
    Review
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

4 authors at 2 institutions in 1 country.

Joseph MocharnukSchool of Medicine, University of Pittsburgh, Wexford, PA 15090 USA.
Trevor LockardSchool of Medicine, University of Nebraska, Lincoln, USA.
Corey GeorgesenDepartment of Dermatology, University of Nebraska, Lincoln, USA.
Joseph C EnglishDepartment of Dermatology, University of Pittsburgh, Wexford, PA 15090 USA.ORCID 0000-0001-7090-9381
University of Nebraska–Lincoln · USUniversity of Pittsburgh · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose of Review: Inpatient teledermatology is a rapidly growing field with significant potential to add value and streamline patient care. This review summarizes the current literature on inpatient teledermatology, primarily focusing on its diagnostic and clinical management utility as compared to live dermatologic evaluation. Recent Findings: The COVID-19 pandemic has accelerated the adoption of inpatient teledermatology, which has been shown to be comparable to live hospitalist evaluation for triage, diagnosis, and management of hospitalized patients for a wide variety of conditions. Despite its comparative cost-effectiveness and recent changes in reimbursement practices, inpatient teledermatology still lacks sufficient reimbursement incentive for widespread implementation. Summary: Inpatient teledermatology is an effective, efficient, accurate, and cost-effective means of managing the hospital burden of skin disease, especially in areas where access to dermatologic care is limited. It is essential that dermatologists and referring providers comprehend the use and potential pitfalls of inpatient teledermatology to effectively incorporate it into hospital practice.

Indexed as

Dermatology hospitalistsInpatient teledermatologistInpatient teledermatologyStore-and-forward teledermatologyTeledermatology

Identifiers

PMID35402084
PMCPMC8976271
OpenAlexW4223646133

What OpenQuestion holds

Textmetadata
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.