Evidence map›Paper›PMID 34137827›Full record

ArticleJAMA network open2021

Secondary Use of COVID-19 Symptom Incidence Among Hospital Employees as an Example of Syndromic Surveillance of Hospital Admissions Within 7 Days.

Steven Horng, Ashley O'Donoghue, Tenzin Dechen, Matthew Rabesa, Ayad Shammout, Lawrence Markson, Venkat Jegadeesan, Manu Tandon, Jennifer P Stevens

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

9 authors at 2 institutions in 1 country.

Steven HorngCenter for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Ashley O'DonoghueCenter for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Tenzin DechenCenter for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Matthew RabesaEmployee Health, Beth Israel Lahey Health, Boston, Massachusetts.
Ayad ShammoutInformation Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Lawrence MarksonInformation Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Venkat JegadeesanInformation Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Manu TandonInformation Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Jennifer P StevensCenter for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Beth Israel Deaconess Medical Center · USLahey Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Alternative methods for hospital occupancy forecasting, essential information in hospital crisis planning, are necessary in a novel pandemic when traditional data sources such as disease testing are limited. Objective: To determine whether mandatory daily employee symptom attestation data can be used as syndromic surveillance to estimate COVID-19 hospitalizations in the communities where employees live. Design, Setting, and Participants: This cohort study was conducted from April 2, 2020, to November 4, 2020, at a large academic hospital network of 10 hospitals accounting for a total of 2384 beds and 136 000 discharges in New England. The participants included 6841 employees who worked on-site at hospital 1 and lived in the 10 hospitals' service areas. Exposure: Daily employee self-reported symptoms were collected using an automated text messaging system from a single hospital. Main Outcomes and Measures: Mean absolute error (MAE) and weighted mean absolute percentage error (MAPE) of 7-day forecasts of daily COVID-19 hospital census at each hospital. Results: Among 6841 employees living within the 10 hospitals' service areas, 5120 (74.8%) were female individuals and 3884 (56.8%) were White individuals; the mean (SD) age was 40.8 (13.6) years, and the mean (SD) time of service was 8.8 (10.4) years. The study model had a MAE of 6.9 patients with COVID-19 and a weighted MAPE of 1.5% for hospitalizations for the entire hospital network. The individual hospitals had an MAE that ranged from 0.9 to 4.5 patients (weighted MAPE ranged from 2.1% to 16.1%). For context, the mean network all-cause occupancy was 1286 during this period, so an error of 6.9 is only 0.5% of the network mean occupancy. Operationally, this level of error was negligible to the incident command center. At hospital 1, a doubling of the number of employees reporting symptoms (which corresponded to 4 additional employees reporting symptoms at the mean for hospital 1) was associated with a 5% increase in COVID-19 hospitalizations at hospital 1 in 7 days (regression coefficient, 0.05; 95% CI, 0.02-0.07; P < .001). Conclusions and Relevance: This cohort study found that a real-time employee health attestation tool used at a single hospital could be used to estimate subsequent hospitalizations in 7 days at hospitals throughout a larger hospital network in New England.

Indexed as

Sentinel SurveillanceAdultCohort StudiesCOVID-19FemaleForecastingHospitalizationHospitalsHumansIncidenceMaleMiddle AgedNew EnglandPersonnel, HospitalSARS-CoV-2Symptom Assessment

Identifiers

PMID34137827
PMCPMC11984965
OpenAlexW3171352973

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.