Evidence map›Paper›PMID 34847055›Full record

ArticleJournal of medical Internet research2021

Examination of a Canada-Wide Collaboration Platform for Order Sets: Retrospective Analysis.

Arshia Pedram Javidan, Allan Brand, Andrew Cameron, Tommaso D'Ovidio, Martin Persaud, Kirsten Lewis, Chris O'Connor

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. 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
0.1field-weighted citation impact, top 54% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

7 authors at 3 institutions in 1 country.

Arshia Pedram JavidanDivision of Vascular Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-7541-2857
Allan BrandThink Research, Toronto, ON, Canada.ORCID 0000-0002-9442-2233
Andrew CameronDepartment of Emergency Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.ORCID 0000-0003-0248-8145
Tommaso D'OvidioThink Research, Toronto, ON, Canada.ORCID 0000-0001-9652-2177
Martin PersaudThink Research, Toronto, ON, Canada.ORCID 0000-0003-1789-8614
Kirsten LewisThink Research, Toronto, ON, Canada.ORCID 0000-0002-4691-5615
Chris O'ConnorTrillium Health Partners, Mississauga Site, Mississauga, ON, Canada.ORCID 0000-0003-3164-8603
University of Toronto · CATrillium Health Centre · CAUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnowledge translation and dissemination are some of the main challenges that affect evidence-based medicine. Web 2.0 platforms promote the sharing and collaborative development of content. Executable knowledge tools, such as order sets, are a knowledge translation tool whose localization is critical to its effectiveness but a challenge for organizations to develop independently.

objectiveThis paper describes a Web 2.0 resource, referred to as the collaborative network (TCN), for order set development designed to share executable knowledge (order sets). This paper also analyzes the scope of its use, describes its use through network analysis, and examines the provision and use of order sets in the platform by organizational size.

methodsData were collected from Think Research's TxConnect platform. We measured interorganization sharing across Canadian hospitals using descriptive statistics. A weighted chi-square analysis was used to evaluate institutional size to share volumes based on institution size, with post hoc Cramer V score to measure the strength of association.

resultsTCN consisted of 12,495 order sets across 683 diagnoses or processes. Between January 2010 and March 2015, a total of 131 health care organizations representing 360 hospitals in Canada downloaded order sets 105,496 times. Order sets related to acute coronary syndrome, analgesia, and venous thromboembolism were most commonly shared. COVID-19 order sets were among the most actively shared, adjusting for order set lifetime. A weighted chi-square analysis showed nonrandom downloading behavior (P<.001), with medium-sized institutions downloading content from larger institutions acting as the most significant driver of this variance (chi-gram=124.70).

conclusionsIn this paper, we have described and analyzed a Web 2.0 platform for the sharing of order set content with significant network activity. The robust use of TCN to access customized order sets reflects its value as a resource for health care organizations when they develop or update their own order sets.

Indexed as

COVID-19CanadaHumansRetrospective StudiesSARS-CoV-2evidence-based medicinehealth informaticsknowledge translationorder setsWeb 2.0

Identifiers

PMID34847055
PMCPMC8669583
OpenAlexW3217154976

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.