Evidence map›Paper›PMID 39606400›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Disparities in Anti-emetic Prophylaxis Care Processes are Predicted by Patient Neighborhood: A Retrospective Cohort and Geospatial Analysis.

Jiuying Han, Neng Wan, Cameron K Jacobson, Nathan L Pace, Cade K Kartchner, Alexander S Hohl, Robert B Schonberger, Douglas A Colquhoun, Richard P Dutton, Michael H Andreae and 1 more

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In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Jiuying Han
Cameron K Jacobson
Cade K Kartchner
Robert B SchonbergerORCID 0000-0002-5180-5189
Douglas A ColquhounORCID 0000-0003-1304-9164
Richard P Dutton
Michael H AndreaeORCID 0000-0002-9052-0936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Social Determinants of Health (SDoH) continue to drive persistent disparities in perioperative care. Our team has previously demonstrated racial and socioeconomic disparities in perioperative processes, notably in the administration of antiemetic prophylaxis, in several large perioperative registries. Given how neighborhoods are socially segregated in the US, we examined geospatial clustering of perioperative antiemetic disparities. Methods: We conducted a retrospective cohort study of anesthetic records from the University of Utah Hospital with 19,477 patients meeting inclusion criteria. We geocoded patient home addresses and combined them with the Census Block Group(CBG) level neighborhood disadvantage (ND), a composite index of from the National Neighborhood Data Archive (NaNDA). We stratified our patients by antiemetic risk score and calculated the number of anti-emetic interventions. We utilized Poisson Spatial Scan Statistics, implemented in SaTScan, to detect geographic clusters of under-treatment. Results: We identified one significant cluster (p < .001) of undertreated perioperative antiemetic prophylaxis cases. The relative risk (RR) of the whole cluster is 1.44, implying that patients within the cluster are 1.44 times more likely to receive fewer antiemetics after controlling for antiemetic risk. Patients from more disadvantaged neighborhoods were more likely to receive below median antiemetic prophylaxis after controlling for risk. Conclusions: To our knowledge, this is the first geospatial cluster analysis of perioperative process disparities; we leveraged innovative geostatistical methods and identified a spatially defined, geographic cluster of patients whose home address census-tract level neighborhood deprivation index predicted disparities in risk adjusted antiemetic prophylaxis.

Identifiers

PMID39606400
PMCPMC11601721

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