Evidence map›Paper›PMID 36448474›Full record

ArticleJournal of primary care & community health

Federally Qualified Health Center Penetration Associated With Reduced Community COVID-19 Mortality in Four United States Cities.

Mary M Ford, Angela Allard, Jordan Goldberg, Cynthia Summers

Open access · goldAbstract read
In one paragraph

Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

4 authors at 1 institution in 1 country.

Mary M FordPrimary Care Development Corporation, New York, NY, USA.ORCID 0000-0003-3256-4276
Angela AllardPrimary Care Development Corporation, New York, NY, USA.
Jordan GoldbergPrimary Care Development Corporation, New York, NY, USA.
Cynthia SummersPrimary Care Development Corporation, New York, NY, USA.
Primary Care Development Corporation · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has had significant impacts on health care access and delivery, with disparate effects across social and racial lines. Federally Qualified Health Centers (FQHCs) provide critical primary care services to the nation's most underserved populations, including many communities hardest hit by COVID-19.

methodsWe conducted an ecological analysis that aimed to examine FQHC penetration, COVID-19 mortality, and socio-demographic factors in 4 major United States cities: New York, New York; Chicago, Illinois; Detroit, Michigan; and Seattle, Washington.

resultsWe found the distribution of COVID-19 cases and mortality varied spatially and in magnitude by city. COVID-19 mortality was significantly higher in communities with higher percentages of low-income residents and higher percentages of racial/ethnic minority residents. FQHC penetration was protective against increased COVID-19 mortality, after model adjustment.

conclusionsOur study underpins the critical role of safety-net health care and policymakers must ensure investment in long-term sustainability of FQHCs, through strategic deployment of capital, workforce development, and reimbursement reform.

Indexed as

COVID-19CitiesEthnicityHumansMinority GroupsNew YorkPandemicscommunity health centersCOVID-19 mortalityFQHC penetrationhealth disparities

Identifiers

PMID36448474
PMCPMC9716186
OpenAlexW4310705926

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.