Evidence map›Paper›PMID 34458878›Full record

ArticleTechniques and innovations in gastrointestinal endoscopy2021

A Multimodal Interdisciplinary QI Intervention Is Associated with Reduction in After Hours Inpatient Endoscopy Cases.

Sonali Palchaudhuri, Sara Attalla, Shivan J Mehta, Afshin Parsikia, Richard T White, Nuzhat A Ahmad, Gregory G Ginsberg, Mark S Weiss, Colleen Demopoulos, John Keogh and 3 more

Open access · greenAbstract read
In one paragraph

Article in Techniques and innovations in gastrointestinal endoscopy, 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
0.2field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  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

13 authors at 2 institutions in 1 country.

Sonali PalchaudhuriDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Sara AttallaDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Shivan J MehtaDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Afshin ParsikiaDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Richard T WhitePerioperative Services, Hospital of the University of Pennsylvania, University of Pennsylvania, Philadelphia, PA.
Nuzhat A AhmadDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Gregory G GinsbergDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Mark S WeissAnesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA.
Colleen DemopoulosDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
John KeoghPerioperative Services, Hospital of the University of Pennsylvania, University of Pennsylvania, Philadelphia, PA.
David C MetzDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Michael L KochmanDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
Shazia Mehmood SiddiqueDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA.
University of Pennsylvania · USHospital of the University of Pennsylvania · US

Funding

CLINICAL EPIDEMIOLOGY TRAINING IN GASTROENTEROLOGYT32DK007740 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI James D Lewis · 1997 to 2026
$9.2M
Evaluation of variability in care and outcomes for patients with gastrointestinal bleedingK08DK120902 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI SIDDIQUE, SHAZIA MEHMOOD · 2020 to 2024
$851k
NIDDK NIH HHS K08 DK120902NIDDK NIH HHS T32 DK007740
6 · The paper itself

Abstract

BACKGROUND AND

aimsIncreasing demand for inpatient endoscopic services results in performing more non-emergent endoscopic cases after-hours, which poses risks to patient safety and negatively impacts patient and provider satisfaction. This study sought to quantify the existing state using quality improvement (QI) methodology, design targeted interventions, and determine their effectiveness.

methodsWe conducted an existing state evaluation through a process map, time-series study, and caseload analysis from 7/2017-12/2018. Using end-of-workday (EOW) as a proxy for patient/provider dissatisfaction and risk for patient safety events, we performed a prospective evaluation of a staged interdisciplinary multimodal intervention aimed to decrease the proportion of days with EOW after 7PM, decrease the proportion of cases begun after 5PM, and decrease EOW variability. The post-intervention period was 6/2019-2/2020.

resultsBased on existing state analyses, we implemented a series of targeted interventions: (1) provider workflow tips, (2) expedited transport for select patients, (3) pathway to reschedule appropriate cases to outpatient endoscopy, and (4) increased staffing for high caseload days through resource pooling. The proportion of days with EOW after 7PM decreased from 42.4% to 29.3% (caseload-adjusted odds ratio of 0.39, p< 0.001). Despite increased caseload, cases begun after 5PM decreased from 17.5% to 14.2% (OR 0.75, p = 0.009). EOW SD decreased from 2:20 hours to 1:36 hours.

conclusionsThe multimodal intervention reduced days with EOW after 7PM and the proportion of cases begun after 5PM, despite increased caseload. This study shows how applying research methods to implement QI interventions successfully decreases late inpatient endoscopic cases.

Indexed as

delivery scienceendoscopic workflowinpatient endoscopyprocedural efficiency

Identifiers

PMID34458878
PMCPMC8386508
OpenAlexW3163229699

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.