Evidence map›Paper›PMID 35570965›Full record

ArticleFrontiers in public health2022

Examining Social Determinants of Health During a Pandemic: Clinical Application of Z Codes Before and During COVID-19.

Xueying Yang, Brooks Yelton, Shujie Chen, Jiajia Zhang, Bankole A Olatosi, Shan Qiao, Xiaoming Li, Daniela B Friedman

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
5.8field-weighted citation impact, top 4% 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

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Observational
  2. Article
  3. Stressful life events in electronic health records: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024
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  12. A marker-based neural network system for extracting social determinants of health.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
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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

8 authors at 1 institution in 1 country.

Xueying YangCenter for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Brooks YeltonDepartment of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Shujie ChenCenter for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Jiajia ZhangCenter for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Bankole A OlatosiCenter for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Shan QiaoCenter for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Xiaoming LiCenter for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Daniela B FriedmanDepartment of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
University of South Carolina · US

Funding

Multilevel Determinants of Racial and Ethnic Disparities in Maternal Morbidity and Mortality in the Context of COVID-19 PandemicR01AI127203 · NIAID · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI LI, XIAOMING, OLATOSI, BANKOLE · 2017 to 2021
$5.2M
NIAID NIH HHS R01 AI127203
6 · The paper itself

Abstract

Recognition of the impact of social determinants of health (SDoH) on healthcare outcomes, healthcare service utilization, and population health has prompted a global shift in focus to patient social needs and lived experiences in assessment and treatment. The International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) provides a list of non-billable "Z codes" specific to SDoH for use in electronic health records. Using population-level analysis, this study aims to examine clinical application of Z codes in South Carolina before and during the COVID-19 pandemic. The study population consists of South Carolina residents who had a healthcare visit and had their COVID-19 test result reported to the state's Department of Health and Environmental Control before January 14, 2021. Of the 1,190,531 individuals in the overall sample, Z codes were used only for 14,665 (1.23%) of the patients, including 2,536 (0.97%) COVID-positive patients and 12,129 (1.30%) COVID-negative patients. Compared with hospitals that did not use Z codes, those that did were significantly more likely to have higher bed capacity (

Indexed as

COVID-19PandemicsHumansInternational Classification of DiseasesSocial Determinants of HealthVulnerable PopulationscoronavirusCOVID-19healthy people 2030population healthsocial determinants of healthZ codes

Identifiers

PMID35570965
PMCPMC9098923
OpenAlexW4225159016

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.