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Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities
INTRODUCTION: Mobile health (mHealth) has the potential to change how patients make healthcare decisions. We sought to determine the readiness to use mHealth technology in underserved communities. METHODS: We conducted a cross-sectional survey of patients presenting with low-acuity complaints to an...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Department of Emergency Medicine, University of California, Irvine School of Medicine
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754190/ https://www.ncbi.nlm.nih.gov/pubmed/31539337 http://dx.doi.org/10.5811/westjem.2019.6.41911 |
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author | van Veen, Tara Binz, Sophia Muminovic, Meri Chaudhry, Kaleem Rose, Katie Calo, Sean Rammal, Jo-Ann France, John Miller, Joseph B. |
author_facet | van Veen, Tara Binz, Sophia Muminovic, Meri Chaudhry, Kaleem Rose, Katie Calo, Sean Rammal, Jo-Ann France, John Miller, Joseph B. |
author_sort | van Veen, Tara |
collection | PubMed |
description | INTRODUCTION: Mobile health (mHealth) has the potential to change how patients make healthcare decisions. We sought to determine the readiness to use mHealth technology in underserved communities. METHODS: We conducted a cross-sectional survey of patients presenting with low-acuity complaints to an urban emergency department (ED) with an underserved population. Patients over the age of two who presented with low-acuity complaints were included. We conducted structured interview with each patient or parent (for minors) about willingness to use mHealth tools for guidance. Analysis included descriptive statistics and univariate analysis based on age and gender. RESULTS: Of 560 patients included in the survey, 80% were adults, 64% female, and 90% Black. The mean age was 28 ± 9 years for adults and 9 ± 5 years for children. One-third of patients reported no primary care physician, and 55% reported no access to a nurse or clinician for medical advice. Adults were less likely to have access to phone consultation than parents of children (odds ratio [OR] 0.49, 95% confidence interval [CI], 0.32 – 0.74), as were males compared to females (OR 0.52, 95% CI, 0.37–0.74). Most patients (96%) reported cellular internet access. Two-thirds of patients reported using online references. When asked how they would behave if an mHealth tool advised them that their current health problem was low risk, 69% of patients responded that they would seek care in an outpatient clinic instead of the ED (30%), stay home and not seek urgent medical care (28%), or use telehealth (11%). CONCLUSION: In this urban community we found a large capacity and willingness to use mHealth technology in medical triage. |
format | Online Article Text |
id | pubmed-6754190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Department of Emergency Medicine, University of California, Irvine School of Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-67541902019-09-25 Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities van Veen, Tara Binz, Sophia Muminovic, Meri Chaudhry, Kaleem Rose, Katie Calo, Sean Rammal, Jo-Ann France, John Miller, Joseph B. West J Emerg Med Population Health INTRODUCTION: Mobile health (mHealth) has the potential to change how patients make healthcare decisions. We sought to determine the readiness to use mHealth technology in underserved communities. METHODS: We conducted a cross-sectional survey of patients presenting with low-acuity complaints to an urban emergency department (ED) with an underserved population. Patients over the age of two who presented with low-acuity complaints were included. We conducted structured interview with each patient or parent (for minors) about willingness to use mHealth tools for guidance. Analysis included descriptive statistics and univariate analysis based on age and gender. RESULTS: Of 560 patients included in the survey, 80% were adults, 64% female, and 90% Black. The mean age was 28 ± 9 years for adults and 9 ± 5 years for children. One-third of patients reported no primary care physician, and 55% reported no access to a nurse or clinician for medical advice. Adults were less likely to have access to phone consultation than parents of children (odds ratio [OR] 0.49, 95% confidence interval [CI], 0.32 – 0.74), as were males compared to females (OR 0.52, 95% CI, 0.37–0.74). Most patients (96%) reported cellular internet access. Two-thirds of patients reported using online references. When asked how they would behave if an mHealth tool advised them that their current health problem was low risk, 69% of patients responded that they would seek care in an outpatient clinic instead of the ED (30%), stay home and not seek urgent medical care (28%), or use telehealth (11%). CONCLUSION: In this urban community we found a large capacity and willingness to use mHealth technology in medical triage. Department of Emergency Medicine, University of California, Irvine School of Medicine 2019-09 2019-08-06 /pmc/articles/PMC6754190/ /pubmed/31539337 http://dx.doi.org/10.5811/westjem.2019.6.41911 Text en Copyright: © 2019 Veen et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Population Health van Veen, Tara Binz, Sophia Muminovic, Meri Chaudhry, Kaleem Rose, Katie Calo, Sean Rammal, Jo-Ann France, John Miller, Joseph B. Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities |
title | Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities |
title_full | Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities |
title_fullStr | Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities |
title_full_unstemmed | Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities |
title_short | Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities |
title_sort | potential of mobile health technology to reduce health disparities in underserved communities |
topic | Population Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754190/ https://www.ncbi.nlm.nih.gov/pubmed/31539337 http://dx.doi.org/10.5811/westjem.2019.6.41911 |
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