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Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study

BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addic...

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Autores principales: Quanbeck, Andrew, Gustafson, David H, Marsch, Lisa A, Chih, Ming-Yuan, Kornfield, Rachel, McTavish, Fiona, Johnson, Roberta, Brown, Randall T, Mares, Marie-Louise, Shah, Dhavan V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811649/
https://www.ncbi.nlm.nih.gov/pubmed/29382624
http://dx.doi.org/10.2196/jmir.8928
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author Quanbeck, Andrew
Gustafson, David H
Marsch, Lisa A
Chih, Ming-Yuan
Kornfield, Rachel
McTavish, Fiona
Johnson, Roberta
Brown, Randall T
Mares, Marie-Louise
Shah, Dhavan V
author_facet Quanbeck, Andrew
Gustafson, David H
Marsch, Lisa A
Chih, Ming-Yuan
Kornfield, Rachel
McTavish, Fiona
Johnson, Roberta
Brown, Randall T
Mares, Marie-Louise
Shah, Dhavan V
author_sort Quanbeck, Andrew
collection PubMed
description BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: The outcomes according to the RE-AIM framework are as follows: Reach—Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness—Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption—Patients sustained high levels of Seva use—between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation—At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance—Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.
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spelling pubmed-58116492018-02-16 Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study Quanbeck, Andrew Gustafson, David H Marsch, Lisa A Chih, Ming-Yuan Kornfield, Rachel McTavish, Fiona Johnson, Roberta Brown, Randall T Mares, Marie-Louise Shah, Dhavan V J Med Internet Res Original Paper BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: The outcomes according to the RE-AIM framework are as follows: Reach—Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness—Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption—Patients sustained high levels of Seva use—between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation—At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance—Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge. JMIR Publications 2018-01-30 /pmc/articles/PMC5811649/ /pubmed/29382624 http://dx.doi.org/10.2196/jmir.8928 Text en ©Andrew Quanbeck, David H Gustafson, Lisa A Marsch, Ming-Yuan Chih, Rachel Kornfield, Fiona McTavish, Roberta Johnson, Randall T Brown, Marie-Louise Mares, Dhavan V Shah. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.01.2018. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Quanbeck, Andrew
Gustafson, David H
Marsch, Lisa A
Chih, Ming-Yuan
Kornfield, Rachel
McTavish, Fiona
Johnson, Roberta
Brown, Randall T
Mares, Marie-Louise
Shah, Dhavan V
Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study
title Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study
title_full Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study
title_fullStr Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study
title_full_unstemmed Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study
title_short Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study
title_sort implementing a mobile health system to integrate the treatment of addiction into primary care: a hybrid implementation-effectiveness study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811649/
https://www.ncbi.nlm.nih.gov/pubmed/29382624
http://dx.doi.org/10.2196/jmir.8928
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