Evidence map›Paper›PMID 35073207›Full record

ArticleJournal of telemedicine and telecare2024

Development of the electronic consultation long-term care utilization and savings estimator tool to model the potential impact of electronic consultation for residents living in long-term care.

Emiliyan Staykov, Mary Helmer-Smith, Celeste Fung, Peter Tanuseputro, Clare Liddy

Abstract read
In one paragraph

Article in Journal of telemedicine and telecare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Emiliyan StaykovDepartment of Biology, University of Ottawa, Canada.ORCID 0000-0003-2417-1632
Mary Helmer-SmithC.T. Lamont Primary Health Care Research Centre, Bruyère Research Institute, Canada.ORCID 0000-0002-7745-7012
Celeste FungDepartment of Family Medicine, University of Ottawa, Canada.
Peter TanuseputroOttawa Hospital Research Institute, Canada.
Clare LiddyC.T. Lamont Primary Health Care Research Centre, Bruyère Research Institute, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ageing populations have resulted in more patients living in long-term care or nursing homes, where they face challenges to accessing prompt specialist care exacerbated in many cases by physical or cognitive decline. Electronic consultation has demonstrated an ability to improve access to specialist care for vulnerable groups and offers a potential solution to this gap in care. To support electronic consultation's uptake among long-term care homes, we created the electronic consultation long-term care utilization and savings estimator, an Excel-based tool that estimates the number of off-site appointments that patients in a long-term care home could avoid through electronic consultation, along with the consequent time and cost savings. In this brief report, we discuss the electronic consultation long-term care utilization and savings estimator's creation and function, and provide a case study using long-term care data to demonstrate its potential impact. We anticipate the electronic consultation long-term care utilization and savings estimator will be a highly impactful tool and intend to test it in real-world conditions following the relaxation of COVID-19 restrictions.

Indexed as

Cognitive DysfunctionCOVID-19Remote ConsultationCost SavingsHumansLong-Term Carecost analysiscost-effectivenesseHealthevaluationonline healthremote consultationresidential aged caretelehealth

Identifiers

PMID35073207
PMCPMC10988991

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.