Evidence map›Paper›PMID 38775290›Full record

ArticleAmerican journal of epidemiology2024

The role and limitations of electronic medical records versus patient interviews for determining symptoms of, underlying comorbidities of, and medication use by patients with COVID-19.

Raymond A Soto, Grace M Vahey, Kristen E Marshall, Emily McDonald, Rachel Herlihy, Helen M Chun, Marie E Killerby, Breanna Kawasaki, Claire M Midgley, Nisha B Alden and 3 more

Abstract readComparative Study
In one paragraph

Article in American journal of epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Chronic pain, fatigue, and emotional distress in femaleFrontiers in molecular neuroscience · 2026
    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

13 authors.

Raymond A SotoEpidemic Intelligence Service, Epidemiology and Laboratory Workforce Branch, Centers for Disease Control and Prevention, Atlanta, GA 30345, United States.ORCID 0000-0002-8483-6459
Grace M VaheyEpidemic Intelligence Service, Epidemiology and Laboratory Workforce Branch, Centers for Disease Control and Prevention, Atlanta, GA 30345, United States.ORCID 0000-0002-6766-1933
Kristen E MarshallEpidemic Intelligence Service, Epidemiology and Laboratory Workforce Branch, Centers for Disease Control and Prevention, Atlanta, GA 30345, United States.ORCID 0000-0003-4484-7011
Emily McDonaldEpidemic Intelligence Service, Epidemiology and Laboratory Workforce Branch, Centers for Disease Control and Prevention, Atlanta, GA 30345, United States.
Rachel HerlihyDivision of Disease Control and Public Health Response, Colorado Department of Public Health and Environment, Denver, CO 80426, United States.ORCID 0000-0003-4535-2299
Helen M ChunCOVID-19 Emergency Response, Division of Emergency Operations, Centers for Disease Control and Prevention, Atlanta, GA 30329, and Fort Collins, CO 80521, United States.ORCID 0000-0002-1050-7361
Marie E KillerbyCOVID-19 Emergency Response, Division of Emergency Operations, Centers for Disease Control and Prevention, Atlanta, GA 30329, and Fort Collins, CO 80521, United States.ORCID 0000-0003-1992-7079
Breanna KawasakiDivision of Disease Control and Public Health Response, Colorado Department of Public Health and Environment, Denver, CO 80426, United States.
Claire M MidgleyCOVID-19 Emergency Response, Division of Emergency Operations, Centers for Disease Control and Prevention, Atlanta, GA 30329, and Fort Collins, CO 80521, United States.ORCID 0000-0001-5196-4713
Nisha B AldenDivision of Disease Control and Public Health Response, Colorado Department of Public Health and Environment, Denver, CO 80426, United States.ORCID 0000-0002-8128-7714
Jacqueline E TateCOVID-19 Emergency Response, Division of Emergency Operations, Centers for Disease Control and Prevention, Atlanta, GA 30329, and Fort Collins, CO 80521, United States.ORCID 0000-0002-8114-6196
J Erin StaplesCOVID-19 Emergency Response, Division of Emergency Operations, Centers for Disease Control and Prevention, Atlanta, GA 30329, and Fort Collins, CO 80521, United States.ORCID 0000-0002-1446-4071
Colorado Investigation TeamDivision of Disease Control and Public Health Response, Colorado Department of Public Health and Environment, Denver, CO 80426, United States.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

Electronic medical records (EMRs) are important for rapidly compiling information to determine disease characteristics (eg, symptoms) and risk factors (eg, underlying comorbidities, medications) for disease-related outcomes. To assess EMR data accuracy, agreement between EMR abstractions and patient interviews was evaluated. Symptoms, medical history, and medication use among patients with COVID-19 collected from EMRs and patient interviews were compared using overall agreement (ie, same answer in EMR and interview), reported agreement (yes answer in both EMR and interview among those who reported yes in either), and κ statistics. Overall, patients reported more symptoms in interviews than in EMR abstractions. Overall agreement was high (≥50% for 20 of 23 symptoms), but only subjective fever and dyspnea had reported agreement of ≥50%. The κ statistics for symptoms were generally low. Reported medical conditions had greater agreement with all condition categories (n = 10 of 10) having ≥50% overall agreement and half (n = 5 of 10) having ≥50% reported agreement. More nonprescription medications were reported in interviews than in EMR abstractions, leading to low reported agreement (28%). Discordance was observed for symptoms, medical history, and medication use between EMR abstractions and patient interviews. Investigations using EMRs to describe clinical characteristics and identify risk factors should consider the potential for incomplete data, particularly for symptoms and medications.

Indexed as

ComorbidityCOVID-19Electronic Health RecordsInterviews as TopicAdultAgedData AccuracyFemaleHumansMaleMiddle AgedSARS-CoV-2COVID-19data accuracyelectronic health recordsepidemiologic methodsmedical recordsSARS-CoV-2telephone interviews

Identifiers

PMID38775290
PMCPMC12983407

What OpenQuestion holds

Textmetadata
LicenceTDM
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.