Evidence map›Paper›PMID 32442266›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Barriers to hospital electronic public health reporting and implications for the COVID-19 pandemic.

A Jay Holmgren, Nate C Apathy, Julia Adler-Milstein

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  10. Collaborating for COVID-19: Hospital Health Information Exchange and Public Health Partnership.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

A Jay HolmgrenHarvard Business School, Harvard University, Boston, Massachusetts, USA.
Nate C ApathyRichard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA.
Julia Adler-MilsteinDepartment of Medicine, University of San Francisco, San Francisco, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We sought to identify barriers to hospital reporting of electronic surveillance data to local, state, and federal public health agencies and the impact on areas projected to be overwhelmed by the COVID-19 pandemic. Using 2018 American Hospital Association data, we identified barriers to surveillance data reporting and combined this with data on the projected impact of the COVID-19 pandemic on hospital capacity at the hospital referral region level. Our results find the most common barrier was public health agencies lacked the capacity to electronically receive data, with 41.2% of all hospitals reporting it. We also identified 31 hospital referral regions in the top quartile of projected bed capacity needed for COVID-19 patients in which over half of hospitals in the area reported that the relevant public health agency was unable to receive electronic data. Public health agencies' inability to receive electronic data is the most prominent hospital-reported barrier to effective syndromic surveillance. This reflects the policy commitment of investing in information technology for hospitals without a concomitant investment in IT infrastructure for state and local public health agencies.

Indexed as

Coronavirus InfectionsElectronic Health RecordsHospitalsPandemicsPneumonia, ViralBetacoronavirusCOVID-19Data CollectionHumansPopulation SurveillancePublic HealthSARS-CoV-2COVID-19electronic health recordspandemicpublic healthsyndromic surveillance

Identifiers

PMID32442266
PMCPMC7313984

What OpenQuestion holds

Textmetadata
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.