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Research Letter |

Functional Impairment and Internet Use Among Older Adults: Implications for Meaningful Use of Patient Portals FREE

S. Ryan Greysen, MD, MHS, MA1; Carie Chin Garcia, MD2; Rebecca L. Sudore, MD, MPH3,4; Irena Stijacic Cenzer, MA3,4; Kenneth E. Covinsky, MD, MPH3,4
[+] Author Affiliations
1Division of Hospital Medicine, University of California, San Francisco
2Department of Medicine, California Pacific Medical Center, San Francisco
3San Francisco Veterans Affairs Medical Center, San Francisco, California
4Division of Geriatric Medicine, University of California, San Francisco
JAMA Intern Med. 2014;174(7):1188-1190. doi:10.1001/jamainternmed.2014.1864.
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Published online

Medicare is currently dispensing $30 billion in incentives to health care facilities that adopt the use of electronic medical records (EMRs). In 2014, incentives for “meaningful use” of EMRs will require online access by patients, and reimbursement penalties of up to 5% for nonadoption will begin in 2015.1 Broader use of online patient portals to EMRs is intended to improve care coordination; yet the impact of common problems in Medicare-eligible patients, such as chronic illness or functional impairment, on Internet use is unknown.

This study was approved by the institutional review board for the University of California, San Francisco. We used the Health and Retirement Study (http://hrsonline.isr.umich.edu), a nationally representative sample of community-dwelling seniors (limited to Medicare-eligible individuals aged ≥65 years, excluding the 3%-6% of all Medicare patients who live in nursing homes), for cross-sectional analysis of Internet use at 2 time points, 2002 and 2010 (Table). Information regarding informed consent is available at the Health and Retirement Study website. We performed descriptive statistics (χ2 or t test) and multivariable regression analysis (modified Poisson) to characterize features of Internet use at each time point.

Table Graphic Jump LocationTable.  Demographic and Clinical Characteristics of Seniors as Determinants of Internet Use in 2002 and 2010

Overall rates of Internet use doubled from 2002 through 2010 (from 21% to 42%); however, changes in use differed by demographic and health characteristics. Overall, groups with the lowest rates showed the largest relative increases from 2002 through 2010: those with less than a high school education (from 4% to 9%), nonwhite race (from 7% to 21%), functional impairment (from 10% to 23%), poor or fair self-rated health (from 11% to 25%), age 75 years or older (from 12% to 27%), unpartnered status (from 12% to 29%), and any chronic condition (from 19% to 40%) (Table).

In multivariable regression analysis adjusted for demographic characteristics and socioeconomic status, those older than 75 years or with functional impairments were less likely to use the Internet than all other groups in both 2002 and 2010. Comparing these adjusted ratios in the 2002 to 2010 period, there were significant changes in 3 low-use groups: those aged 75 years or older, nonwhites, and those with poor or fair self-rated health. There was no significant change, however, for those with functional impairment (Figure).

Place holder to copy figure label and caption
Figure.
Adjusted Risk Ratios for Internet Use in 2002 and 2010 in Low-Use Groups

Relative risk of 1.0 indicates no difference in change from 2002 to 2010 compared with reference group (from left to right, vs no functional impairment [P = .08], age younger than 75 years [P = .04], white race [P = .01], good or better self-rated health [P = .02], no chronic condition [P = .86]). Risk ratios are adjusted for demographic characteristics (sex, race, marital status) and socioeconomic status (education and net worth). All analyses are weighted for differential probability of selection and the complex sampling design of the Health and Retirement Study.aStatistically significant comparison.

Graphic Jump Location

Internet use has increased in Medicare-eligible patients from 2002 through 2010 but remains low for the frailest seniors. Our results suggest that functional impairment is more predictive of Internet nonuse than chronic illness, poor self-rated health, or age, which has important implications for patient portal use. Whereas prior studies of the “digital divide” in health care have highlighted differences in demographic characteristics and socioeconomic status,2 our study demonstrates the additional impact of functional limitations that are prevalent in the Medicare population. If these trends from the early years of EMR use persist into the current era of rapid implementation, the frailest and most vulnerable patients may be at risk for increasingly disengaged and uncoordinated care as more aspects of health care move online.

Thus, strategies to reduce the digital divide in Medicare patients will also need to address functional limitations. Existing software can read web pages out loud for visually impaired individuals, and voice recognition software may make Internet use easier for those who cannot easily manipulate a mouse or keyboard. Furthermore, emerging mobile technologies such as touchscreens, smartphones, and motion sensors may enable a wide range of body gestures to further expand the ways that people can interact with EMRs via the Internet.3 Although more evidence is needed to validate outcomes for these approaches,4 it is clear that patient portals will require greater agility to adapt to patient needs. Beyond adaptive changes in the technology per se, more training is needed for frail seniors and their caregivers to use portals effectively to engage in care. Indeed, caregivers (often younger and not functionally impaired) are likely important but overlooked targets for expanding portal use and improving care coordination for frail seniors.5 Without such adaptations, frail seniors who might otherwise benefit the most from portals may be the least likely to engage.

Meaningful use of EMRs will soon require patient portal use by Medicare patients, and more seniors are going online now than ever6; however, our findings highlight the need for health care providers to address functional barriers to Internet use and for future research to target digital health interventions to the specific needs of the frailest patients in this aging population.

Corresponding Author: S. Ryan Greysen, MD, MHS, MA, Division of Hospital Medicine, University of California, San Francisco, 533 Parnassus Ave, PO Box 0131, San Francisco, CA 94113 (ryan.greysen@ucsf.edu).

Published Online: May 16, 2014. doi:10.1001/jamainternmed.2014.1864.

Author Contributions: Dr Greysen 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.

Study concept and design: Greysen, Chin Garcia, Sudore, Covinsky.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Greysen, Chin Garcia, Sudore.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Greysen, Cenzer, Covinsky.

Obtained funding: Chin Garcia, Covinsky.

Administrative, technical, or material support: Covinsky.

Study supervision: Chin Garcia, Covinsky.

Conflict of Interest Disclosures: None reported.

Funding/Support: Dr Greysen is supported by the National Institutes of Health National Institute on Aging (NIH-NIA) through the Claude D. Pepper Older Americans Independence Center, a Career Development Award (1K23AG045338-01), and the NIH-NIA Loan Repayment Program. Dr Covinsky is supported by the NIH-NIA through a K-24 Career Mentoring Award and an R01 grant from the National Institute of Nursing Research. Dr Sudore is supported by the US Department of Veterans Affairs, the National Palliative Care Research Center Foundation, and the NIH-NIA (grant 1R01AG045043-01).

Role of the Sponsor: The funders 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.

Previous Presentation: This study was presented at the American Geriatrics Society Annual Meeting; May 16, 2014; Orlando, Florida.

Additional Contributions: John Boscardin, PhD, Divisions of Biostatistics and Epidemiology and Geriatric Medicine, University of California, San Francisco, provided expert statistical advice.

Marcotte  L, Seidman  J, Trudel  K,  et al.  Achieving meaningful use of health information technology: a guide for physicians to the EHR incentive programs. Arch Intern Med. 2012;172(9):731-736.
PubMed   |  Link to Article
Chang  BL, Bakken  S, Brown  SS,  et al.  Bridging the digital divide: reaching vulnerable populations. J Am Med Inform Assoc. 2004;11(6):448-457.
PubMed   |  Link to Article
Steinhubl  SR, Muse  ED, Topol  EJ.  Can mobile health technologies transform health care? JAMA. 2013;310(22):2395-2396.
PubMed   |  Link to Article
Kumar  S, Nilsen  WJ, Abernethy  A,  et al.  Mobile health technology evaluation: the mHealth evidence workshop. Am J Prev Med. 2013;45(2):228-236.
PubMed   |  Link to Article
Sarkar  U, Bates  DW.  Care partners and online patient portals. JAMA. 2014;311(4):357-358.
PubMed   |  Link to Article
Zickuhr  K, Madden  M. Older Adults and Internet Use: for the First Time, Half of Adults Ages 65 and Older Are Online. 2012. http://www.pewinternet.org/2012/06/06/older-adults-and-internet-use/. Accessed May 22, 2013.

Figures

Place holder to copy figure label and caption
Figure.
Adjusted Risk Ratios for Internet Use in 2002 and 2010 in Low-Use Groups

Relative risk of 1.0 indicates no difference in change from 2002 to 2010 compared with reference group (from left to right, vs no functional impairment [P = .08], age younger than 75 years [P = .04], white race [P = .01], good or better self-rated health [P = .02], no chronic condition [P = .86]). Risk ratios are adjusted for demographic characteristics (sex, race, marital status) and socioeconomic status (education and net worth). All analyses are weighted for differential probability of selection and the complex sampling design of the Health and Retirement Study.aStatistically significant comparison.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable.  Demographic and Clinical Characteristics of Seniors as Determinants of Internet Use in 2002 and 2010

References

Marcotte  L, Seidman  J, Trudel  K,  et al.  Achieving meaningful use of health information technology: a guide for physicians to the EHR incentive programs. Arch Intern Med. 2012;172(9):731-736.
PubMed   |  Link to Article
Chang  BL, Bakken  S, Brown  SS,  et al.  Bridging the digital divide: reaching vulnerable populations. J Am Med Inform Assoc. 2004;11(6):448-457.
PubMed   |  Link to Article
Steinhubl  SR, Muse  ED, Topol  EJ.  Can mobile health technologies transform health care? JAMA. 2013;310(22):2395-2396.
PubMed   |  Link to Article
Kumar  S, Nilsen  WJ, Abernethy  A,  et al.  Mobile health technology evaluation: the mHealth evidence workshop. Am J Prev Med. 2013;45(2):228-236.
PubMed   |  Link to Article
Sarkar  U, Bates  DW.  Care partners and online patient portals. JAMA. 2014;311(4):357-358.
PubMed   |  Link to Article
Zickuhr  K, Madden  M. Older Adults and Internet Use: for the First Time, Half of Adults Ages 65 and Older Are Online. 2012. http://www.pewinternet.org/2012/06/06/older-adults-and-internet-use/. Accessed May 22, 2013.

Correspondence

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