The y-axis scale shown in blue indicates range from 0% to 20%. Tablet and social network sites questions were asked only in 2013 through 2014. Error bars indicate 95% CIs of the weighted percentages. P values for trends: cell phone (.17), computer (.11), internet and online for any other reason (<.001), email and texting (<.001), internet banking (<.001), tablet (<.001), social network sites (.006), internet shopping (.003), obtain health condition information (.002), fill prescriptions (<.001), contact a clinician (<.001), and handle insurance matters (.065). Cumulative attrition between 2011 and 2014 was due to death (n = 1430) and loss to follow-up (n = 1824).
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Levine DM, Lipsitz SR, Linder JA. Trends in Seniors’ Use of Digital Health Technology in the United States, 2011-2014. JAMA. 2016;316(5):538–540. doi:10.1001/jama.2016.9124
Copyright 2016 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
The sickest, most expensive, and fastest growing segment of the US population are seniors 65 years and older.1 Digital health technology has been advocated as a solution to improve health care quality, cost, and safety. However, little is known about digital health use among seniors.
The Partners HealthCare Human Research Committee exempted this study from review. The National Health and Aging Trends Study (NHATS) is an annual in-home, computer-assisted, longitudinal, nationally representative survey of community-dwelling Medicare beneficiaries 65 years and older drawn from the Medicare enrollment database through a complex sampling design.2 Each year, NHATS asks the same respondents about everyday (nonhealth) technology use and 4 digital health modalities: use of the internet to fill prescriptions, contact a clinician, address insurance matters, and research health conditions.
For this study, we included participants in 2011 (response rate, 71%) who were followed yearly until 2014. We examined everyday and digital health use and variables associated with digital health use using logistic regression, adjusting for all characteristics in the Table, the complex survey design, repeated measures, nonresponse, and missing data.
We analyzed trends over time with the trend test. We considered 2-sided P values less than .05 to be significant. We performed all analyses with SAS (SAS Institute), version 9.4.
In 2011, the mean age of the 7609 participants was 75 years (SD, 7.4); 57% were women (Table). Although 76% of seniors used cell phones and 64% computers, fewer used internet (43%) and email and texting (40%). Less than 20% used internet banking, internet shopping, social network sites (2013 data), and tablets (2013 data). Fewer seniors used digital health technology: 16% obtained health information, 8% filled prescriptions, 7% contacted clinicians, and 5% handled insurance online.
In 2011, variables associated with less use of any digital health were older age; black, Latino, and other race/ethnicity; divorce; and poor health (Table). Variables associated with greater use included college education, higher annual income, taking medications, and more comorbidities.
By 2014, 1430 participants had died and 1824 were lost to follow-up, leaving 4355 seniors (57%). Although cell phone and computer use were stable, small statistically significant increases were noted in other everyday technologies (Figure). Use of 3 of 4 digital health technologies increased. The proportion of seniors who used any digital health increased from 21% in 2011 to 25% in 2014 (difference, 4% [95% CI, 3% to 5%]; P < .01). In 2011, 1.1% used all 4 modalities compared with 1.8% in 2014 (difference, 0.7% [95% CI, 0.1% to 1.3%]; P = .02). From 2011 to 2014, 14% (95% CI, 13% to 15%) of seniors increased the number of modalities used; 10% (95% CI, 9% to 11%) decreased their use.
Seniors used digital health at low rates with only modest increases from 2011 through 2014. To our knowledge, this is the first nationally representative study to examine trends in seniors’ digital health use, although a study in Northern California found higher patient portal use than the clinician contact rate in this study.3
Seniors’ use of everyday technology was below that of the general population (approximately 90% use the internet and own cell phones; 60% search for health information),4 but similar to other studies of older adults, except for the finding of racial and socioeconomic differences.4,5 Relying on everyday technology or generic internet use rates to estimate digital health use may be misleading. For example, although 63% used a computer and 43% used the internet, only 10% filled prescriptions online.
Limitations include that NHATS is a closed cohort with inception in 2011; more recent cohorts may be different. Many survey participants were lost to follow-up or died, although there were not large changes in sample characteristics. Data were only available over 4 years.
Digital health is not reaching most seniors and is associated with socioeconomic disparities, raising concern about its ability to improve quality, cost, and safety of their health care. Future innovations should focus on usability, adherence, and scalability to improve the reach and effectiveness of digital health for seniors.
Correction: This article was corrected for an error in the Figure on September 2, 2016.
Corresponding Author: David M. Levine, MD, MA, Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Harvard Medical School, 1620 Tremont St, Third Floor, Boston, MA 02120 (firstname.lastname@example.org).
Author Contributions: Dr Levine had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: All authors.
Administrative, technical, or material support: Levine, Linder.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Funding/Support: This work received funding support from an Institutional National Research Service Award (Dr Levine; T32HP10251) from the National Institutes of Health, the Ryoichi Sasakawa Fellowship Fund, and by the Brigham and Women’s Hospital Division of General Internal Medicine and Primary Care.
Role of the Funder/Sponsor: All funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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