Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review
The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States. We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representin...
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| Published in: | Journal of the American Medical Informatics Association : JAMIA Vol. 27; no. 5; p. 834 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
01.05.2020
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| ISSN: | 1527-974X, 1527-974X |
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| Abstract | The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.
We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.
We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.
Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.
Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use. |
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| AbstractList | The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.OBJECTIVEThe study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.MATERIALS AND METHODSWe conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.RESULTSWe included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.DISCUSSIONGiven the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use.CONCLUSIONFew studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use. The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States. We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics. We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use. Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed. Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use. |
| Author | Adler-Milstein, Julia Barr-Walker, Jill Sarkar, Urmimala Thao, Crishyashi Lyles, Courtney Nouri, Sarah S Acharya, Prasad |
| Author_xml | – sequence: 1 givenname: Sarah S surname: Nouri fullname: Nouri, Sarah S organization: Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California, USA – sequence: 2 givenname: Julia surname: Adler-Milstein fullname: Adler-Milstein, Julia organization: Center for Clinical Informatics and Improvement Research, School of Medicine, University of California, San Francisco, San Francisco, California, USA – sequence: 3 givenname: Crishyashi surname: Thao fullname: Thao, Crishyashi organization: Center for Clinical Informatics and Improvement Research, School of Medicine, University of California, San Francisco, San Francisco, California, USA – sequence: 4 givenname: Prasad surname: Acharya fullname: Acharya, Prasad organization: Chronic Disease Control Branch, Center for Healthy Communities, California Department of Public Health, Sacramento, California, USA – sequence: 5 givenname: Jill surname: Barr-Walker fullname: Barr-Walker, Jill organization: Zuckerberg San Francisco General Hospital Library, University of California, San Francisco, San Francisco, California, USA – sequence: 6 givenname: Urmimala surname: Sarkar fullname: Sarkar, Urmimala organization: UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California, USA – sequence: 7 givenname: Courtney surname: Lyles fullname: Lyles, Courtney organization: UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32364238$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com. |
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| Keywords | health equity social determinants of health digital health population health informatics |
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| Title | Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review |
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