Evidence map›Paper›PMID 38562568›Full record

ArticleAcademic pathology

Intra- and post-pandemic impact of the COVID-19 outbreak on Stanford Health Care.

Thanaphong Phongpreecha, Eloise Berson, Lei Xue, Sayane Shome, Geetha Saarunya, Jennifer Fralick, Bernardita Guridi Ruiz-Tagle, Andrew Foody, Alexander L Chin, Michael Lim and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Academic pathology. 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
–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

1 citing paper in PubMed.

  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

18 authors.

Thanaphong PhongpreechaDepartment of Pathology, Stanford University, USA.
Eloise BersonDepartment of Pathology, Stanford University, USA.
Lei XueDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University, USA.
Sayane ShomeDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University, USA.
Geetha SaarunyaDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University, USA.
Jennifer FralickStanford Health Care, USA.
Bernardita Guridi Ruiz-TagleStanford Health Care, USA.
Andrew FoodyStanford Health Care, USA.
Alexander L ChinStanford Health Care, USA.
Michael LimDepartment of Neurosurgery, Stanford University, USA.
Rudolph ArthoferStanford Health Care, USA.
Christopher AlbiniStanford Health Care, USA.
Kathleen MontineDepartment of Pathology, Stanford University, USA.
Ann K FolkinsDepartment of Pathology, Stanford University, USA.
Christina S KongDepartment of Pathology, Stanford University, USA.
Nima AghaeepourDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University, USA.
Thomas MontineDepartment of Pathology, Stanford University, USA.
Alison KerrStanford Health Care, USA.

Funding

Machine Learning for Integrative Modeling of the Immune System in Clinical SettingsR35GM138353 · NIGMS · STANFORD UNIVERSITY · PI AGHAEEPOUR, NIMA · 2020 to 2024
$2.2M
6 · The paper itself

Abstract

Stanford Health Care, which provides about 7% of overall healthcare to approximately 9 million people in the San Francisco Bay Area, has undergone significant changes due to the opening of a second hospital in late 2019 and, more importantly, the COVID-19 pandemic. We examine the impact of these events on anatomic pathology (AP) cases, aiming to enhance operational efficiency in response to evolving healthcare demands. We extracted historical census, admission, lab tests, operation, and AP data since 2015. An approximately 45% increase in the volume of laboratory tests (P < 0.0001) and a 17% increase in AP cases (P < 0.0001) occurred post-pandemic. These increases were associated with progressively increasing (P < 0.0001) hospital census. Census increase stemmed from higher admission through the emergency department (ED), and longer lengths of stay mostly for transfer patients, likely due to the greater capability of the new ED and changes in regional and local practice patterns post-pandemic. Higher census led to overcapacity, which has an inverted U relationship that peaked at 103% capacity for AP cases and 114% capacity for laboratory tests. Overcapacity led to a lower capability to perform clinical activities, particularly those related to surgical procedures. We conclude by suggesting parameters for optimal operations in the post-pandemic era.

Indexed as

Anatomic pathologyHospital admissionHospital censusOvercapacitySurgery capability

Identifiers

PMID38562568
PMCPMC10982550

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.