Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 426

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Changes in Health Services Use Among Commercially Insured US Populations During the COVID-19 Pandemic

Open access
Whaley, Christopher M., Pera, Megan F., Cantor, Jonathan, Chang, Jennie, Velasco, Julia, Hagg, Heather K., Sood, Neeraj, Bravata, Dena M.·2020·JAMA Network Open

Abstract

Importance: The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented strain on patients and health care professionals and institutions, but the association of the pandemic with use of preventive, elective, and nonelective care, as well as potential disparities in use of health care, remain unknown. Objective: To examine changes in health care use during the first 2 months of the COVID-19 pandemic in March and April of 2020 relative to March and April of 2019 and 2018, and to examine whether changes in use differ by patient's zip code-level race/ethnicity or income. Design, Setting, and Participants: This cross-sectional study analyzed health insurance claims for patients from all 50 US states who receive health insurance through their employers. Changes in use of preventive services, nonelective care, elective procedures, prescription drugs, in-person office visits, and telemedicine visits were examined during the first 2 months of the COVID-19 pandemic in 2020 relative to existing trends in 2019 and 2018. Disparities in the association of the pandemic with health care use based on patient's zip code-level race and income were also examined. Results: Data from 5.6, 6.4, and 6.8 million US individuals with employer-sponsored insurance in 2018, 2019, and 2020, respectively, were analyzed. Patient demographics were similar in all 3 years (mean [SD] age, 34.3 [18.6] years in 2018, 34.3 [18.5] years in 2019, and 34.5 [18.5] years in 2020); 50.0% women in 2018, 49.5% women in 2019, and 49.5% women in 2020). In March and April 2020, regression-adjusted use rate per 10 000 persons changed by -28.2 (95% CI, -30.5 to -25.9) and -64.5 (95% CI, -66.8 to -62.2) for colonoscopies; -149.1 (95% CI, -162.0 to -16.2) and -342.1 (95% CI, -355.0 to -329.2) for mammograms; -60.0 (95% CI, -63.3 to -54.7) and -118.1 (95% CI, -112.4 to -113.9) for hemoglobin A1c tests; -300.5 (95% CI, -346.5 to -254.5) and -369.0 (95% CI, -414.7 to -323.4) for child vaccines; -4.6 (95% CI, -5.3 to -3.9) and -10.9 (95% CI, -11.6 to -10.2) for musculoskeletal surgery; -1.1 (95% CI, -1.4 to -0.7) and -3.4 (95% CI, -3.8 to -3.0) for cataract surgery; -13.4 (95% CI, -14.6 to -12.2) and -31.4 (95% CI, -32.6 to -30.2) for magnetic resonance imaging; and -581.1 (95% CI, -612.9 to -549.3) and -1465 (95% CI, -1496 to -1433) for in-person office visits. Use of telemedicine services increased by 227.9 (95% CI, 221.7 to 234.1) per 10 000 persons and 641.6 (95% CI, 635.5 to 647.8) per 10 000 persons. Patients living in zip codes with lower-income or majority racial/ethnic minority populations experienced smaller reductions in in-person visits (≥80% racial/ethnic minority zip code: 200.0 per 10 000 [95% CI, 128.9-270.1]; 79%-21% racial/ethnic minority zip code: 54.2 per 10 000 [95% CI, 33.6-74.9]) but also had lower rates of adoption of telemedicine (≥80% racial/ethnic minority zip code: -71.6 per 10 000 [95% CI, -87.6 to -55.5]; 79%-21% racial/ethnic minority zip code: -15.1 per 10 000 [95% CI, -19.8 to -10.4]). Conclusions and Relevance: In this cross-sectional study of a large US population with employer-sponsored insurance, the first 2 months of the COVID-19 pandemic were associated with dramatic reductions in the use of preventive and elective care. Use of telemedicine increased rapidly but not enough to account for reductions in in-person primary care visits. Race and income disparities at the zip code level exist in use of telemedicine.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamanetworkopen.2020.24984

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 15 references

Cited by

See all 426

Metadata

Authors
Whaley, C. M., Pera, M. F., Cantor, J., Chang, J., Velasco, J., Hagg, H. K., Sood, N., & Bravata, D. M.
Venue
JAMA Network Open
Published
2020-11-05
Volume
3
Issue
11
Pages
e2024984
ISSN
2574-3805 (ISSN-L)
OpenAlex
W3095526646
Cited by
426
References
15
FWCI
22.30
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Changes in Health Services Use Among Commercially Insured US Populations During the COVID-19 Pandemic. https://app.cochat.ai/papers/10.1001/jamanetworkopen.2020.24984
The paper
Whaley, C. M., Pera, M. F., Cantor, J., Chang, J., Velasco, J., Hagg, H. K., Sood, N., & Bravata, D. M. (2020). Changes in Health Services Use Among Commercially Insured US Populations During the COVID-19 Pandemic. JAMA Network Open. https://doi.org/10.1001/jamanetworkopen.2020.24984

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.