Evidence map›Paper›PMID 38939047›Full record

ArticleNeurology. Clinical practice2024

Reducing Door-to-Puncture Times for Mechanical Thrombectomy in a Large Tertiary Hospital.

Zhenghong Liu, Man Qing Leong, Nanlan Li, Miqi Mavis Teo, Wei-Li Rachel Leong, Steve Chen Pong Wong, Jing Si Chew, Seyed Ehsan Saffari, Yee Hau Pang, Ghim Song Chia

Abstract read
In one paragraph

Article in Neurology. Clinical practice, 2024. 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. 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.

Zhenghong LiuDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0003-3361-3818
Man Qing LeongDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0002-6299-1685
Nanlan LiDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0009-0009-3886-2400
Miqi Mavis TeoDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0003-2759-2563
Wei-Li Rachel LeongDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0003-2329-4235
Steve Chen Pong WongDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0003-2936-4054
Jing Si ChewDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0009-0000-6871-0496
Seyed Ehsan SaffariDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0002-6473-4375
Yee Hau PangDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0002-3957-471X
Ghim Song ChiaDepartment of Emergency Medicine (ZL), Singapore General Hospital; Inpatient Operations (MQL), Changi General Hospital; Office of Clinical Informatics (NL), Woodlands Health; Division of Anaesthesiology and Peiroperative Medicine (MMT, W-LRL); Department of Neuroradiology (SCPW, GSC); Department of Neurology (JSC, YHP), Singapore General Hospital; and Center for Quantitative Medicine (SES), Duke-NUS Medical School, Singapore.ORCID https://orcid.org/0000-0002-1305-2753

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Endovascular therapy (EVT) for stroke has emerged as an important therapy for selected stroke patients, and shorter times to clot removal improve functional outcomes. EVT requires the close coordination of multiple departments and poses unique challenges to care coordination in large hospitals. We present the results of our quality improvement project that aimed to improve our door-to-groin puncture (DTP) times for patients who undergo EVT after direct presentation to our emergency department. Methods: We conducted time-motion studies to understand the full process of an EVT activation and conducted Gemba walks in multiple hospitals. We also reviewed the literature and interviewed stakeholders to create interventions that were implemented over 4 Plan-Do-Study-Act (PDSA) cycles. We retrospectively collected data starting from baseline and during every PDSA cycle. During each cycle, we studied the impact of the interventions, adjusted the interventions, and generated further interventions. A variety of interventions were introduced targeting all aspects of the EVT process. This included parallel processing to reduce waiting time, standardization of protocols and training of staff, behavioral prompts in the form of a stroke clock, and push systems to empower staff to facilitate the forward movement of the patient. A novel role-based communication app to facilitate group communications was also used. Results: Eighty-eight patients spanning across 22 months were analyzed. After the final PDSA cycle, the median DTP time was reduced by 36.5% compared with baseline (130 minutes (interquartile range [IQR] 111-140) to 82.5 minutes (IQR 74.8-100)). There were improvements in all phases of the EVT process with the largest time savings occurring in EVT decision to patient arrival at the angiosuite. Interventions that were most impactful are described. Discussion: EVT is a complex process involving multiple processes and local factors. Analysis of the process from all angles and intervening on multiple small aspects can add up to significant improvements in DTP times.

Identifiers

PMID38939047
PMCPMC11201277

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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.