Evidence map›Paper›PMID 37637353›Full record

ArticleCritical care explorations2023

Implementation of a Virtual Interprofessional ICU Learning Collaborative: Successes, Challenges, and Initial Reactions From the Structured Team-Based Optimal Patient-Centered Care for Virus COVID-19 Collaborators.

Simon Zec, Nika Zorko Garbajs, Yue Dong, Ognjen Gajic, Christina Kordik, Lori Harmon, Marija Bogojevic, Romil Singh, Yuqiang Sun, Vikas Bansal and 15 more

Open access · goldAbstract read
In one paragraph

Article in Critical care explorations, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

25 authors at 7 institutions in 1 country.

Simon ZecDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Nika Zorko GarbajsDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Yue DongDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Ognjen GajicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Christina KordikSociety of Critical Care Medicine, Mount Prospect, IL.
Lori HarmonSociety of Critical Care Medicine, Mount Prospect, IL.
Marija BogojevicDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Romil SinghDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Yuqiang SunDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Vikas BansalDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Linh VuDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Kelly CawcuttDepartment of Internal Medicine, Division of Infectious Diseases, University of Nebraska Medical Center, Omaha, NE.
John M LitellDepartment of Emergency Medicine, Hennepin Healthcare, Minneapolis, MN.
Sarah RedmondCenter for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
Eleanor FitzpatrickSurgical Intensive Care Unit, Thomas Jefferson University Hospital, Philadelphia, PA.
Kirstin J KoodaDepartment of Pharmacy, Mayo Clinic, Rochester, MN.
Michelle BiehlDepartment of Critical Care Medicine and Pulmonary Medicine, Respiratory Institute, Cleveland Clinic, Cleveland, OH.
Neha S DangayachNeurocritical Care Division, Mount Sinai Health System, New York, NY.
Viren KaulDepartment of Pulmonary and Critical Care Medicine, Crouse Health/State University of New York Upstate Medical University, Syracuse, NY.
June M ChaeDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Aaron LeppinCenter for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
Mathew SiubaDepartment of Critical Care Medicine and Pulmonary Medicine, Respiratory Institute, Cleveland Clinic, Cleveland, OH.
Rahul KashyapDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Allan J WalkeyPulmonary Center, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Evans Center of Implementation and Improvement Sciences, Boston University School of Medicine, Boston, MA.
Alexander S NivenDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Mayo Clinic in Arizona · USPulmonary Associates · USSociety of Critical Care Medicine · USHennepin Healthcare Research Institute · USJapan Society · USSound Shore Medical Center · USUniversity of Nebraska Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Initial Society of Critical Care Medicine Discovery Viral Infection and Respiratory illness Universal Study (VIRUS) Registry analysis suggested that improvements in critical care processes offered the greatest modifiable opportunity to improve critically ill COVID-19 patient outcomes.

objectivesThe Structured Team-based Optimal Patient-Centered Care for Virus COVID-19 ICU Collaborative was created to identify and speed implementation of best evidence based COVID-19 practices. DESIGN SETTING AND

participantsThis 6-month project included volunteer interprofessional teams from VIRUS Registry sites, who received online training on the Checklist for Early Recognition and Treatment of Acute Illness and iNjury approach, a structured and systematic method for delivering evidence based critical care. Collaborators participated in weekly 1-hour videoconference sessions on high impact topics, monthly quality improvement (QI) coaching sessions, and received extensive additional resources for asynchronous learning. MAIN OUTCOMES AND MEASURES: Outcomes included learner engagement, satisfaction, and number of QI projects initiated by participating teams.

resultsEleven of 13 initial sites participated in the Collaborative from March 2, 2021, to September 29, 2021. A total of 67 learners participated in the Collaborative, including 23 nurses, 22 physicians, 10 pharmacists, nine respiratory therapists, and three nonclinicians. Site attendance among the 11 sites in the 25 videoconference sessions ranged between 82% and 100%, with three sites providing at least one team member for 100% of sessions. The majority reported that topics matched their scope of practice (69%) and would highly recommend the program to colleagues (77%). A total of nine QI projects were initiated across three clinical domains and focused on improving adherence to established critical care practice bundles, reducing nosocomial complications, and strengthening patient- and family-centered care in the ICU. Major factors impacting successful Collaborative engagement included an engaged interprofessional team; an established culture of engagement; opportunities to benchmark performance and accelerate institutional innovation, networking, and acclaim; and ready access to data that could be leveraged for QI purposes. CONCLUSIONS AND RELEVANCE: Use of a virtual platform to establish a learning collaborative to accelerate the identification, dissemination, and implementation of critical care best practices for COVID-19 is feasible. Our experience offers important lessons for future collaborative efforts focused on improving ICU processes of care.

Indexed as

COVID-19critical carelearning collaborativequality improvementsevere acute respiratory syndrome coronavirus 2

Identifiers

PMID37637353
PMCPMC10456981
OpenAlexW4379472630

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.