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Secondary Use of COVID-19 Symptom Incidence Among Hospital Employees as an Example of Syndromic Surveillance of Hospital Admissions Within 7 Days.
Horng, Steven; O'Donoghue, Ashley; Dechen, Tenzin; Rabesa, Matthew; Shammout, Ayad; Markson, Lawrence; Jegadeesan, Venkat; Tandon, Manu; Stevens, Jennifer P.
  • Horng S; Center for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • O'Donoghue A; Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • Dechen T; Center for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • Rabesa M; Center for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • Shammout A; Employee Health, Beth Israel Lahey Health, Boston, Massachusetts.
  • Markson L; Information Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • Jegadeesan V; Information Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • Tandon M; Information Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • Stevens JP; Information Systems, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
JAMA Netw Open ; 4(6): e2113782, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-1274643
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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Personnel, Hospital / Sentinel Surveillance / Forecasting / COVID-19 / Hospitalization Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Limits: Adult / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: JAMA Netw Open Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Personnel, Hospital / Sentinel Surveillance / Forecasting / COVID-19 / Hospitalization Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Limits: Adult / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: JAMA Netw Open Year: 2021 Document Type: Article