Evidence map›Paper›PMID 36862699›Full record

ArticlePloS one2023

HCV universal EHR prompt successfully increases screening, highlights potential disparities.

Benjamin Hack, Kavya Sanghavi, Sravya Gundapaneni, Stephen Fernandez, Justin Hughes, Sean Huang, Peter Basch, Allan Fong, Dawn Fishbein

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

9 authors.

Benjamin HackGeorgetown University School of Medicine, Washington, D.C., United States of America.ORCID 0000-0003-2192-6120
Kavya SanghaviMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.
Sravya GundapaneniMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.
Stephen FernandezMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.ORCID 0000-0002-5112-1844
Justin HughesMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.
Sean HuangMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.
Peter BaschMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.
Allan FongMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.
Dawn FishbeinMedStar Health Research Institute, Viral Hepatitis Research, Washington, D.C., United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

objectivesScreening for hepatitis C virus is the first critical decision point for preventing morbidity and mortality from HCV cirrhosis and hepatocellular carcinoma and will ultimately contribute to global elimination of a curable disease. This study aims to portray the changes over time in HCV screening rates and the screened population characteristics following the 2020 implementation of an electronic health record (EHR) alert for universal screening in the outpatient setting in a large healthcare system in the US mid-Atlantic region.

methodsData was abstracted from the EHR on all outpatients from 1/1/2017 through 10/31/2021, including individual demographics and their HCV antibody (Ab) screening dates. For a limited period centered on the implementation of the HCV alert, mixed effects multivariable regression analyses were performed to compare the timeline and characteristics of those screened and un-screened. The final models included socio-demographic covariates of interest, time period (pre/post) and an interaction term between time period and sex. We also examined a model with time as a monthly variable to look at the potential impact of COVID-19 on screening for HCV.

resultsAbsolute number of screens and screening rate increased by 103% and 62%, respectively, after adopting the universal EHR alert. Patients with Medicaid were more likely to be screened than private insurance (ORadj 1.10, 95% CI: 1.05, 1.15), while those with Medicare were less likely (ORadj 0.62, 95% CI: 0.62, 0.65); and Black (ORadj 1.59, 95% CI: 1.53, 1.64) race more than White.

conclusionsImplementation of universal EHR alerts could prove to be a critical next step in HCV elimination. Those with Medicare and Medicaid insurance were not screened proportionately to the national prevalence of HCV in these populations. Our findings support increased screening and re-testing efforts for those at high risk of HCV.

Indexed as

COVID-19Hepatitis CLiver NeoplasmsAgedElectronic Health RecordsHepacivirusHumansMedicareUnited States

Identifiers

PMID36862699
PMCPMC9980726

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Registered trials

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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.