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JAMA Netw Open ; 4(6): e2113782, 2021 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-34137827

RESUMO

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.


Assuntos
COVID-19/epidemiologia , Previsões/métodos , Hospitalização/tendências , Recursos Humanos em Hospital/estatística & dados numéricos , Vigilância de Evento Sentinela , Adulto , COVID-19/diagnóstico , Estudos de Coortes , Feminino , Hospitais , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , New England/epidemiologia , SARS-CoV-2 , Avaliação de Sintomas/estatística & dados numéricos
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