Evidence map›Paper›PMID 33461562›Full record

ArticleBMC women's health2021

Client perceptions of the BreastScreen Australia remote radiology assessment model.

Deborah Smith, Karen Johnston, Karen Carlisle, Rebecca Evans, Robyn Preston, Jessamy Beckett, Danielle Geddes, Helen Naess, Melissa Poole, Sarah Larkins

Abstract read
In one paragraph

Article in BMC women's health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. COVID-19 Remote Consultation Services and Population in Health Inequity-Concentrating Territories: A Scoping Review.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2021
    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

10 authors.

Deborah SmithCollege of Medicine and Dentistry, James Cook University, Douglas, QLD, 4811, Australia. Deb.Smith@jcu.edu.au.ORCID 0000-0003-4729-7166
Karen JohnstonCollege of Medicine and Dentistry, James Cook University, Douglas, QLD, 4811, Australia.
Karen CarlisleCollege of Medicine and Dentistry, James Cook University, Douglas, QLD, 4811, Australia.
Rebecca EvansCollege of Medicine and Dentistry, James Cook University, Douglas, QLD, 4811, Australia.
Robyn PrestonSchool of Health, Medical and Applied Sciences, Central Queensland University, Townsville, QLD, 4810, Australia.
Jessamy BeckettBreastScreen NSW, PO Box 41, Alexandria, NSW, 1435, Australia.
Danielle GeddesBreastScreen NT, PO Box 40596, Casuarina, NT, 0811, Australia.
Helen NaessBreastScreen Queensland, Level 1, 15 Butterfield St, Herston, QLD, 4006, Australia.
Melissa PooleBreastScreen Queensland, Level 1, 15 Butterfield St, Herston, QLD, 4006, Australia.
Sarah LarkinsCollege of Medicine and Dentistry, James Cook University, Douglas, QLD, 4811, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelehealth and teleradiology are increasingly used around the world to facilitate health care provision when the health care provider and clients are separated by distance. The BreastScreen Australia Remote Radiology Assessment Model (RRAM) is an initiative developed to address the challenges of inadequate access to a local radiological workforce in regional Australia. With the growth in telehealth innovations more broadly, the RRAM represents a departure from the traditional onsite model where a radiologist would be co-located with practice staff during assessment clinics. Understanding client satisfaction is an important consideration with new models. This article explores client perceptions of the RRAM including awareness, satisfaction with experiences, confidence in the quality of care being received, and preferences regarding models of service delivery.

methodsClients in four BreastScreen services across three Australian states and territories were invited to provide feedback on their experiences of the RRAM. Brief face-to-face interviews based on a survey were conducted at the conclusion of assessment clinic visits. Clients also provided feedback through surveys completed and returned by post, and online.

results144 clients completed the survey regarding their experiences of the RRAM. The majority were aged between 50 and 59 years (55/144, 38.2%). Most had attended a BreastScreen service for either screening or assessment on a total of two to five occasions (85/142, 59.9%) in the past. Nearly all women who attended a RRAM clinic expressed satisfaction with their experience (142/143, 99.3%). Clients were aware that the radiologist was working from another location (131/143, 91.6%) and the majority believed there wouldn't be any difference in the care they received between the RRAM and the onsite model (120/142, 84.5%). Clients generally had no particular preference for either the onsite or RRAM model of service delivery.

conclusionsClients' high satisfaction with their clinic experiences, high confidence in care being received, and the majority having no preference for either the onsite or remote model indicates their acceptance of the RRAM. Client acceptance of the model supports continuation of the RRAM at these sites and expansion. Findings may inform future telehealth innovations where key health care team members are working remotely.

Indexed as

RadiologyRural Health ServicesTelemedicineAustraliaFemaleHumansMiddle AgedPerceptionBreast cancerBreastscreen assessmentModels of service deliveryPatient preferencesPatient satisfactionRemote radiologyRural and remoteTelehealthTelemedicineTeleradiology

Identifiers

PMID33461562
PMCPMC7812334

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.