Open AccessCrowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study
Author(s) -
Anish K. Agarwal,
Lauren Southwick,
Rachelle Schneider,
Arthur Pelullo,
Robin Ortiz,
Elissa V. Klinger,
Roy Rosin,
Raina M. Merchant
Publication year - 2022
Publication title -
jmir mental health
Language(s) - English
Resource type - Journals
ISSN - 2368-7959
DOI - 10.2196/31909
Subject(s) - mood , emergency department , phone , thematic analysis , medicine , community health , pandemic , intervention (counseling) , hotline , resource (disambiguation) , health care , nursing , public health , medical emergency , covid-19 , qualitative research , computer science , psychiatry , disease , telecommunications , social science , linguistics , philosophy , computer network , pathology , sociology , infectious disease (medical specialty) , economics , economic growth
Background The COVID-19 pandemic has placed strains on communities. During this public health crisis, health systems have created remote methods of monitoring symptom progression and delivering care virtually. Objective Using an SMS text message-based system, we sought to build and test a remote model to explore community needs, connect individuals to curated resources, and facilitate community health worker intervention when needed during the pandemic. The primary aims of this pilot study were to establish the feasibility (ie, engagement with the text line) and acceptability (ie, participant ratings of resources and service) of delivering automated well-being resources via smartphone technology. Methods Eligible patients (aged 18 years or older, having a cell phone with SMS text messaging capability, and recently visited the emergency department) were identified using the electronic health record. The patients were consented to enroll and begin receiving COVID-19–related information and links to community resources. We collected open-ended and close-ended resource and mood ratings. We calculated the frequencies and conducted a thematic review of the open-ended responses. Results In 7 weeks, 356 participants were enrolled; 13,917 messages were exchanged including 333 resource ratings (mean 4) and 673 well-being scores (mean 6.8). We received and coded 386 open-ended responses, most of which elaborated upon their self-reported mood score (29%). Overall, 77% (n=274) of our participants rated the platform as a service they would highly recommend to a family member or friend. Conclusions This approach is designed to broaden the reach of health systems, tailor to community needs in real time, and connect at-risk individuals with robust community health support.