Cargando…
289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis
OBJECTIVES/GOALS: This study examined patterns in helpline call data as the COVID-19 pandemic evolved including the impact of stay-at-home orders, relaxing of restrictive orders, and stages of vaccine uptake, as well as differences in call volume by Chicago neighborhood health indicators. METHODS/ST...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209032/ http://dx.doi.org/10.1017/cts.2022.159 |
_version_ | 1784729846905044992 |
---|---|
author | Cua, Grace Segovia, David Poole, Jim Gore, Devyani McGowan-Tomke, Jennifer James, Alexa Frank, Ben Atkins, Marc |
author_facet | Cua, Grace Segovia, David Poole, Jim Gore, Devyani McGowan-Tomke, Jennifer James, Alexa Frank, Ben Atkins, Marc |
author_sort | Cua, Grace |
collection | PubMed |
description | OBJECTIVES/GOALS: This study examined patterns in helpline call data as the COVID-19 pandemic evolved including the impact of stay-at-home orders, relaxing of restrictive orders, and stages of vaccine uptake, as well as differences in call volume by Chicago neighborhood health indicators. METHODS/STUDY POPULATION: From November 1, 2018 to June 30, 2021, 56 NAMI-Chicago workers accepted 26,173 helpline calls from 9,374 individuals from 438 zip codes across northeastern Illinois with the majority of calls from high poverty Chicago communities. Descriptive and time series analyses examined patterns in call volume related to the onset of the COVID-19 pandemic, Illinois Stay-at-Home Order, and Illinois reopening and vaccine uptake plan relative to comparable times the prior year. Health indicators from the Chicago Health Atlas (https://chicagohealthatlas.org/) were examined to determine patterns related to NAMI call volume and various health indicators at the zip code level. RESULTS/ANTICIPATED RESULTS: Time series analysis indicated the greatest number of calls occurred in 2020; specifically, there was a 212% increase in call volume and 331% increase in repeat callers (three or more calls per caller) during the first and second phase (March 20th to May 28th) of Illinois Stay-at-Home Order from 2019 to 2020. Analysis of the callers primary need indicated NAMI provided resources and referrals to people with unmet basic needs such as housing, food, and access to healthcare during the height of COVID-19 Pandemic in 2020. A series of ANOVAs indicated that individuals from Chicago zip codes with high levels of uninsured rates, poverty rates, households using SNAP benefits, and economic diversity called NAMI significantly more than those with low levels of these health indicators. DISCUSSION/SIGNIFICANCE: Helplines are a much-needed model to assess needs and implement services during public health crises, particularly in communities experiencing economic hardship and stress. Implications for behavioral health service needs both during and following the pandemic will be discussed. |
format | Online Article Text |
id | pubmed-9209032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92090322022-07-01 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis Cua, Grace Segovia, David Poole, Jim Gore, Devyani McGowan-Tomke, Jennifer James, Alexa Frank, Ben Atkins, Marc J Clin Transl Sci Valued Approaches OBJECTIVES/GOALS: This study examined patterns in helpline call data as the COVID-19 pandemic evolved including the impact of stay-at-home orders, relaxing of restrictive orders, and stages of vaccine uptake, as well as differences in call volume by Chicago neighborhood health indicators. METHODS/STUDY POPULATION: From November 1, 2018 to June 30, 2021, 56 NAMI-Chicago workers accepted 26,173 helpline calls from 9,374 individuals from 438 zip codes across northeastern Illinois with the majority of calls from high poverty Chicago communities. Descriptive and time series analyses examined patterns in call volume related to the onset of the COVID-19 pandemic, Illinois Stay-at-Home Order, and Illinois reopening and vaccine uptake plan relative to comparable times the prior year. Health indicators from the Chicago Health Atlas (https://chicagohealthatlas.org/) were examined to determine patterns related to NAMI call volume and various health indicators at the zip code level. RESULTS/ANTICIPATED RESULTS: Time series analysis indicated the greatest number of calls occurred in 2020; specifically, there was a 212% increase in call volume and 331% increase in repeat callers (three or more calls per caller) during the first and second phase (March 20th to May 28th) of Illinois Stay-at-Home Order from 2019 to 2020. Analysis of the callers primary need indicated NAMI provided resources and referrals to people with unmet basic needs such as housing, food, and access to healthcare during the height of COVID-19 Pandemic in 2020. A series of ANOVAs indicated that individuals from Chicago zip codes with high levels of uninsured rates, poverty rates, households using SNAP benefits, and economic diversity called NAMI significantly more than those with low levels of these health indicators. DISCUSSION/SIGNIFICANCE: Helplines are a much-needed model to assess needs and implement services during public health crises, particularly in communities experiencing economic hardship and stress. Implications for behavioral health service needs both during and following the pandemic will be discussed. Cambridge University Press 2022-04-19 /pmc/articles/PMC9209032/ http://dx.doi.org/10.1017/cts.2022.159 Text en © The Association for Clinical and Translational Science 2022 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. |
spellingShingle | Valued Approaches Cua, Grace Segovia, David Poole, Jim Gore, Devyani McGowan-Tomke, Jennifer James, Alexa Frank, Ben Atkins, Marc 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis |
title | 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis |
title_full | 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis |
title_fullStr | 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis |
title_full_unstemmed | 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis |
title_short | 289 Helpline Services Before, During, and After the COVID-19 Pandemic: A Time Series Analysis |
title_sort | 289 helpline services before, during, and after the covid-19 pandemic: a time series analysis |
topic | Valued Approaches |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209032/ http://dx.doi.org/10.1017/cts.2022.159 |
work_keys_str_mv | AT cuagrace 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT segoviadavid 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT poolejim 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT goredevyani 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT mcgowantomkejennifer 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT jamesalexa 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT frankben 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis AT atkinsmarc 289helplineservicesbeforeduringandafterthecovid19pandemicatimeseriesanalysis |