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Patients are being encouraged to go online to obtain health information and interact with their health care systems. However, a 2014 survey found that less than 60% of American adults aged 65 and older use the Internet, with much lower usage among black and Latino seniors compared with non-Hispanic white seniors, and among older versus younger seniors.
Our aims were to (1) identify race/ethnic and age cohort disparities among seniors in use of the health plan’s patient portal, (2) determine whether race/ethnic and age cohort disparities exist in access to digital devices and preferences for using email- and Web-based modalities to interact with the health care system, (3) assess whether observed disparities in preferences and patient portal use are due simply to barriers to access and inability to use the Internet, and (4) learn whether older adults not currently using the health plan’s patient portal or website have a potential interest in doing so in the future and what kind of support might be best suited to help them.
We conducted two studies of seniors aged 65-79 years. First, we used administrative data about patient portal account status and utilization in 2013 for a large cohort of English-speaking non-Hispanic white (n=183,565), black (n=16,898), Latino (n=12,409), Filipino (n=11,896), and Chinese (n=6314) members of the Kaiser Permanente Northern California health plan. Second, we used data from a mailed survey conducted in 2013-2014 with a stratified random sample of this population (final sample: 849 non-Hispanic white, 567 black, 653 Latino, 219 Filipino, and 314 Chinese). These data were used to examine race/ethnic and age disparities in patient portal use and readiness and preferences for using digital communication for health-related purposes.
Adults aged 70-74 and 75-79 were significantly less likely than 65-69 year olds to be registered to use the patient portal, and among those registered, to have used the portal to send messages, view lab test results, or order prescription refills. Across all age groups, non-Hispanic whites and Chinese seniors were significantly more likely than black, Latino, and Filipino seniors to be registered and to have performed these actions. The survey found that black, Latino, and Filipino seniors and those 75 years old and older were significantly less likely to own digital devices (eg, computers, smartphones), use the Internet and email, and be able and willing to use digital technology to perform health care-related tasks, including obtaining health information, than non-Hispanic whites, Chinese, and younger seniors (aged 65-69), respectively. The preference for using non-digital modalities persisted even among Internet users.
Health plans, government agencies, and other organizations that serve diverse groups of seniors should include social determinants such as race/ethnicity and age when monitoring trends in eHealth to ensure that eHealth disparities do not induce greater health status and health care disparities between more privileged and less privileged groups.
The adoption of digital technology has been accelerating rapidly, and the Internet has become an important tool for health care-related communications and transactions. Increasingly, health care organizations and government agencies are using their websites as key modes of informing patients and the public about health, health care, and health care coverage. In addition, email and secure website portals are used for informational, health care delivery, and business transactions [
It is well documented that digital divides exist in the general US population by race/ethnicity, income, educational attainment, and health literacy [
To date, limited information has been available about the extent to which race/ethnic and age-related eHealth digital divides exist within the senior age group, and beyond access issues, are a function of eHealth literacy and preferences for using digital technology for health-related purposes. Additionally, of the relatively few studies that have focused on race/ethnic differences among seniors, most have been restricted to non-Hispanic whites, African-American/blacks, and Hispanic/Latinos, leaving a gap in information regarding use of digital technology for health-related purposes among the growing Asian segment of the senior population.
Seniors are being expected to make the shift from print and telephonic health communications to interacting via websites, email, text messages, and interactive voice response systems along with other adult age groups. As such, an emerging research and policy priority is to identify the extent to which age and race/ethnic differences in seniors’ access to and comfort with using eHealth have the potential to create or exacerbate disparities in access to timely health care–related information, patient education, and lower-cost health care options such as video visits and online ordering and purchasing of prescription medications and medical equipment. Recognizing this potential,
As part of “Stage 3 Meaningful Use” requirements for electronic medical record systems, health plans, hospitals, and medical offices may be asked to identify and act on patient communication preferences for clinical summaries, reminders, and patient educational materials [
In this study, we assessed the extent to which race/ethnic and age-related eHealth digital divides exist among the racially and ethnically diverse seniors of Kaiser Permanente Northern California (KPNC) and what might be driving the divides that are observed. We used a two-pronged approach. We first examined race/ethnic and age-group differences in overall registration to use and patterns of use of four features of the health plan’s secure patient portal in 2013 in a large study population of non-Hispanic white, black, Hispanic/Latino, Filipino, and Chinese adults aged 65-79. Concurrently, we surveyed a sample of this population to obtain information about the types of digital devices (eg, computer, mobile phone, tablet) and digital technologies (Internet, email, text messaging, Skype) they were using, as well as their readiness and preferences for using digital modalities for health-related purposes. The study had four main aims: (1) to identify race/ethnic and age cohort disparities among seniors in use of the health plan’s patient portal, (2) to determine whether race/ethnic and age cohort disparities exist in access to digital devices and preferences for using email- and Web-based modalities to interact with the health care system, (3) to assess whether observed disparities in preferences and patient portal use are due simply to barriers to access and inability to use the Internet, and (4) to learn whether older adults who are not currently using the health plan’s patient portal or website have a potential interest in doing so in the future and, if so, what kind of support might be best suited to help them.
KPNC is a vertically integrated health care delivery system that serves over 2.4 million adult members and their family members who mostly reside or work in the San Francisco Bay Area, Silicon Valley, Sacramento area, or the Central Valley in Northern California. The KPNC adult membership is highly similar to the insured population of Northern California with regard to demographic and health characteristics [
Our primary aim was to determine whether race/ethnic and age-related differences exist in preferences for using the health plan’s patient portal features and health education resources, which are primarily available in English. The health plan also has Spanish language websites, but at the time of this study, these did not have full functionality in Spanish and were not as comprehensive with regard to health information. Because previous research has shown a sharp drop in Internet use after age 75, we restricted the study population to members aged 65-79 who had no indication in health plan records of having a preference for oral or written communication in a language other than English (non–limited English proficient [non-LEP]). Within this age group, we restricted our study to a cohort of adults who had been assigned to one of the health plan’s five largest race/ethnic groups: non-Hispanic white, African-American/black (black), Hispanic/Latino (Latino), Filipino-American (Filipino), or Chinese-American (Chinese) using data from administrative and research sources. In 2013, these five race/ethnic groups accounted for approximately 95% of all non-LEP health plan members aged ≥65. Furthermore, members aged 65-79 in these race/ethnic groups accounted for approximately 75% of all non-LEP members aged ≥65. Because we wanted everyone to have had at least 2 years of opportunity and encouragement to create a kp.org account and to use the website’s secure features, we further restricted the study population to people who in November 2013 had been continuous KPNC members for at least 2.5 years.
The full study population for the patient portal use study included 183,565 non-Hispanic white members, 16,898 black members, 12,409 Latino members, 11,896 Filipino members, and 6314 Chinese members aged 65-79. Of these, 114,752 non-Hispanic white, 13,006 black, 8755 Latino, 9329 Filipino, and 4087 Chinese members were in the health plan’s diabetes, hypertension, and/or coronary artery disease registry. We used the full study sample to calculate percentages of members who were registered to use the kp.org patient portal and from whom at least one secure email had been received by December 31, 2013. We used the subgroup of members who had at least one laboratory test in the 2013 calendar year to calculate percentages who viewed lab test results online at least once in 2013, and the subgroup who had at least one prescription refill in 2013 to calculate percentages who used the online prescription refill ordering feature at least once. We also calculated use of these secure features, plus signing into the secure portal at least once during the calendar year, among the same subgroups of members, first restricting analyses to those who had a kp.org account by the end of 2013 and then restricting to those in a chronic disease registry. It should be noted that these members may not have had a kp.org account or activated a kp.org account at the time they might have wanted to communicate with a doctor, obtain a lab test result, or order a prescription refill. However, in 2013, it was possible for nearly all adult members to create, activate, and immediately start to use a kp.org account within a few minutes.
All analyses for the patient portal study were conducted using SAS version 9.3 [
From the study population, we selected stratified random samples of approximately equal numbers of women and men from three age groups (65-69, 70-74, 75-79) within each race/ethnic group: 1320 non-Hispanic whites, 1320 blacks, 1320 Latinos, 510 Filipinos, and 510 Chinese. The Filipino and Chinese samples were smaller than the others because their data were originally intended to be used for pilot study purposes.
The survey was conducted using a mailed print questionnaire available only in English, with interviewer administration upon request. An online option was not made available due to our prior experience that a very small percentage of seniors choose to participate using an online questionnaire when both modalities are offered. Participants were offered a US $5 gift card as recognition for returning a completed survey. The first survey was mailed in mid-November 2013, and a second mailing was conducted in mid-December 2013 to those who had not responded. People who did not respond to either of the first two survey mailings were sent a third, slightly shorter, questionnaire in early February 2014. Participants were told that the survey was being done to help Kaiser Permanente and other organizations learn about seniors’ use of digital tools (like computers, mobile devices, and the Internet) and how they prefer to give and get information about their health and health care. The survey materials stated that participation was important even if they did not use a computer, the Internet, email, or a mobile phone, or did not use the Kaiser Permanente website and did not want to use it. A copy of the survey questionnaire can be found in
Survey respondents were assigned analytic weighting factors to adjust for sampling design and nonresponse. The weighting factors were created by dividing the number of people in the full study population who were in the age–sex–race/ethnicity–kp.org account status stratum that the respondent was representing by the number of survey respondents in that stratum. Patient portal account status was included as a component of the weighting after we discovered that in several race/ethnicity × age group strata, members who had signed up for a kp.org account by the time of the survey were significantly more likely to have responded than those who had not. Because approximately 6.84% (178/2602) of the sample completed the slightly shorter form of the survey, separate sets of weighting factors were created for those items included in both longer and shorter forms of the survey and for those items that were included only in the longer form. The raw (ie, unweighted) and weighted age-sex composition of the race/ethnic groups and the full sample are available on request.
All analyses were conducted using SAS version 9.3 procedures for complex datasets [
Kaiser Foundation Research Institute’s Institutional Review Board approved both the patient portal and survey studies.
In the full study population and across all racial and ethnic groups, older seniors (ie, adults aged 70-74 and 75-79) were significantly less likely than those aged 65-69 to have registered to use the patient portal, to have signed into the patient portal at least once, and to have used the patient portal to send a secure message, view lab test results online, or order prescription refills at least once by the end of the year (see
The overall survey response rate was 53.45% (2602/4868) after excluding ineligibles (14 not reachable by mail, 65 non-members, 32 deceased, 1 with dementia). Response rates were similar across age groups: 52.01% (841/1617) for ages 65-69, 53.87% (878/1630) for ages 70-74, and 54.47% (883/1621) for ages 75-79, with no significant sex difference within age group. However, response rates differed significantly by race/ethnic group: 65.26% (849/1301) for non-Hispanic whites, 44.44% (567/1276) for blacks, 50.50% (653/1293) for Latinos, 44.42% (219/493) for Filipinos, and 62.18% (314/505) for Chinese, with no significant differences in response by age and sex within each race/ethnic group.
Registration for and use of the patient portal by age group and race/ethnicitya.
Use of the patient portal in 2013 | Age | All | Non-Hispanic white | Black | Latino | Filipino | Chinese | |
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65-79 | 77.1 | 81.1 | 54.1b | 62.5b | 60.5b | 81.4 |
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65-69 | 82.2 | 86.3 | 61.3b | 67.0b | 65.4b | 86.1 |
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70-74 | 78.6c | 82.6c | 55.4b,c | 63.7b,d | 61.1b,c | 83.7 |
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75-79 | 71.5c | 75.5c | 47.3b,c | 57.9b,c | 55.2b,c | 75.6b,c |
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65-79 | 80.5 | 82.2 | 65.9b | 70.8b | 68.9b | 85.5b |
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65-69 | 83.3 | 85.0 | 69.4b | 75.6b | 74.1b | 87.5 |
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70-74 | 81.6c | 83.5c | 66.9b | 71.8b,d | 69.1b,c | 86.2b |
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75-79 | 76.4c | 78.2c | 61.3b,c | 65.7b,c | 63.3b,c | 83.1b,c |
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65-79 | 59.5 | 64.2 | 32.9b | 41.4b | 38.8b | 67.3b |
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65-69 | 65.9 | 70.8 | 39.6b | 47.7b | 45.3b | 72.7 |
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70-74 | 61.7c | 66.6c | 34.3b,c | 42.8b,c | 39.3b,c | 70.1b |
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75-79 | 51.9c | 56.3c | 26.3b,c | 35.1b,c | 32.3b,c | 60.3c,e |
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65-79 | 77.1 | 79.1 | 60.9b | 66.2b | 64.1b | 82.6b |
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65-69 | 80.1 | 82.0 | 64.7b | 71.2b | 69.3b | 84.4 |
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70-74 | 78.5c | 80.6 c | 62.0b | 67.2b,d | 64.3b | 83.8b |
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75-79 | 72.6c | 74.6 c | 55.7b,c | 60.7b,c | 58.5b,c | 79.8b,c |
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65-79 | 46.3 | 50.8 | 23.3b | 30.1b | 26.1b | 49.1 |
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65-69 | 52.3 | 56.9 | 29.4b | 35.2b | 31.9b | 54.2 | |
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70-74 | 48.1c | 52.8c | 24.1b,c | 31.1b,c | 26.5b,c | 52.0 | |
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75-79 | 39.7c | 43.7c | 17.9b,c | 25.4b,c | 20.4b,c | 42.2c | |
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65-79 | 60.1 | 62.6 | 43.1b | 48.2b | 43.1b | 60.3b |
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65-69 | 63.5 | 66.0 | 47.9b | 52.5b | 48.8b | 63.0 |
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70-74 | 61.3b | 63.9b | 43.6b,c | 48.8c | 43.3b,c | 62.1 |
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75-79 | 55.5b | 57.9b | 37.9b,c | 44.0b,c | 36.9b,c | 55.8c |
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65-79 | 62.8 | 68.0 | 33.9b | 42.7b | 40.0b | 69.1 |
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65-69 | 69.2 | 74.5 | 40.5b | 49.6b | 47.8b | 74.6 | |
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70-74 | 64.6c | 69.9c | 35.0b,c | 44.1b,c | 40.3b,c | 71.7 | |
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75-79 | 55.6c | 60.6c | 27.6b,c | 36.0b,c | 32.7b,c | 62.2c | |
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65-79 | 79.6 | 82.1 | 60.6b | 66.5b | 64.1b | 83.6 |
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65-69 | 82.4 | 84.8 | 63.7b | 71.4b | 70.2b | 85.7 | |
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70-74 | 80.6c | 83.0 c | 61.3c | 67.6b,d | 64.3b,c | 84.9 | |
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75-79 | 75.7c | 78.3 c | 56.4b,c | 60.9b,c | 57.3b,c | 80.3c |
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65-79 | 35.0 | 38.6 | 16.5b | 21.2b | 18.5b | 37.0 |
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65-69 | 42.1 | 46.5 | 21.2b | 26.6b | 22.9b | 44.4 |
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70-74 | 36.5c | 40.4c | 17.5b,c | 21.8b,c | 18.1b,c | 38.4 |
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75-79 | 28.1c | 31.0c | 11.9b,c | 16.9b,c | 15.5b,c | 31.1c |
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65-79 | 44.3 | 46.6 | 29.3b | 33.0b | 29.7b | 44.8 |
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65-69 | 49.9 | 52.6 | 32.9b | 38.0b | 33.8b | 50.8 |
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70-74 | 45.4c | 47.8c | 30.5b | 33.3b,d | 28.7b,c | 45.2d |
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75-79 | 38.3c | 40.0c | 24.3b,c | 28.8b,c | 27.1b,c | 40.3c |
aCell percentages represent use among adults in that age, race/ethnic, or age-race/ethnic subgroup. The denominator for cell percentages in the “All” column includes all non-Hispanic white, black, Latino, Filipino, and Chinese members in that age group. See
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
Differences by age cohort and race/ethnic group in use of the health plan’s patient portal in 2013 among patients ages 65-79 who have diabetes, hypertension, and/or coronary artery diseasea.
Use of the patient portal in 2013 | Age | All | Non-Hispanic white | Black | Latino | Filipino | Chinese |
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65-79 | 76.9 | 81.5 | 55.2b | 63.0b | 61.9b | 82.0 |
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65-69 | 82.2 | 86.8 | 63.5b | 68.3b | 67.3b | 87.9 |
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70-74 | 78.5b | 83.3c | 56.2b,c | 64.6b,d | 62.7b,c | 83.7d |
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75-79 | 71.9b | 76.5c | 48.4b,c | 57.9b,c | 56.3b,c | 77.0c |
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65-79 | 63.3 | 69.2 | 36.2b | 44.5b | 42.8b | 71.7e |
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65-69 | 70.3 | 76.7 | 44.1b | 51.4b | 50.5b | 78.6 |
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70-74 | 65.4b | 71.6c | 37.2b,c | 46.4b,c | 43.2b,c | 74.6e,f |
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75-79 | 56.6b | 61.9c | 29.9b,c | 38.2b,c | 35.8b,c | 64.9b |
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65-79 | 49.3 | 54.8 | 25.8b | 32.6b | 28.7b | 52.8e |
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65-69 | 56.0 | 62.2 | 32.5b | 38.2b | 35.5b | 59.6 |
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70-74 | 51.2b | 57.0c | 26.6b,c | 34.1b,g | 29.2b,c | 56.6 |
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75-79 | 43.0b | 47.9c | 20.4b,c | 27.6b,c | 22.4bb,c | 45.1c,g |
aStudy population for this table is members who were in a health plan diabetes, hypertension, or coronary artery disease registry in 2013. Cell percentages represent use among adults in that age, race/ethnic, or age-race/ethnic subgroup. The denominator for cell percentages in the “All” column includes all non-Hispanic white, black, Latino, Filipino, and Chinese members in that age group. See
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fSignificantly differs (
gSignificantly differs (
The full respondent sample, after weighting, was predominantly non-Hispanic white (79.4%) and aged 70-74 (43.7%) (see
Significant differences across age and race/ethnic groups were observed for educational attainment, income, and health status. Compared with 65-69 year olds, those aged 70-74 and 75-79 were significantly less likely to be college graduates and significantly more likely to be low income. Compared with non-Hispanic white seniors, black and Latino seniors were significantly less likely to be college graduates, whereas Filipino and Chinese seniors were significantly more likely to have college degrees. Nearly one-fourth (22.0%) of Latinos did not graduate from high school, compared with around 4% of the other race/ethnic groups. Black, Latino, and Filipino seniors were significantly more likely than non-Hispanic white seniors to be in the low-income group and significantly less likely to be in the higher income group, whereas the income distribution of Chinese seniors did not significantly differ from that of non-Hispanic white. Seniors aged 75-79 were significantly more likely to consider their health to be fair or poor than those in the younger groups, and black, Latino, and Filipino seniors were significantly more likely than non-Hispanic white seniors to consider themselves to have fair or poor health and to have cardiovascular conditions.
Characteristics of survey respondents, after weighting, by age group and race/ethnicitya .
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All, % | By age group, % | By race/ethnicity,% | |||||||
65-79 (N=2602) | 65-69 (n=841) | 70-74 (n=878) | 75-79 (n=883) | Non-Hispanic white (n=849) | Black (n=567) | Latino (n=653) | Filipino (n=219) | Chinese |
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65-69 | 23.5 | n/a | n/a | n/a | 23.4 | 23.6 | 23.6 | 25.6 | 23.1 |
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70-74 | 43.7 | n/a | n/a | n/a | 43.8 | 43.3 | 42.3 | 45.0 | 42.0 |
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75-79 | 32.8 | n/a | n/a | n/a | 32.8 | 33.1 | 34.1 | 29.4 | 34.9 |
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Women | 54.1 | 53.8 | 53.9 | 54.5 | 53.8 | 56.9 | 54.8 | 57.1 | 48.2 |
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Men | 45.9 | 46.2 | 46.1 | 45.5 | 46.2 | 43.1 | 45.2 | 42.9 | 51.8 |
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Non-Hispanic white | 79.4 | 79.0 | 79.6 | 79.5 | n/a | n/a | n/a | n/a | n/a |
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Black | 7.3 | 7.3 | 7.3 | 7.4 | n/a | n/a | n/a | n/a | n/a |
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Hispanic/Latino | 5.4 | 5.4 | 5.2 | 5.6 | n/a | n/a | n/a | n/a | n/a |
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Filipino | 5.2 | 5.6 | 5.3 | 4.6 | n/a | n/a | n/a | n/a | n/a |
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Chinese | 2.7 | 2.7 | 2.6 | 2.9 | n/a | n/a | n/a | n/a | n/a |
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Non-high school graduate | 5.0 | 3.2 | 3.1 | 8.9b | 3.9 | 4.7 | 22.0c | 4.7 | 4.1 |
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High school graduate/GEDd | 21.3 | 14.5 | 19.9 | 28.1 | 21.0 | 25.2 | 31.0 | 14.1 | 14.3 |
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Some college | 23.8 | 33.4 | 36.1 | 30.8 | 34.2 | 45.0 | 27.8 | 22.7 | 24.6 |
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College graduate | 39.9 | 48.9 | 40.9e | 32.2b | 40.9 | 25.0c | 19.2c | 58.4c | 57.0c |
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≤25,000 | 17.7 | 11.9 | 18.7b | 26.7b | 15.8 | 26.1c | 22.3c | 29.3c | 16.8 |
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25,001-35,000 | 12.6 | 10.0 | 13.2 | 16.5 | 11.9 | 16.3 | 17.5 | 17.5 | 8.7 |
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35,001-80,000 | 42.0 | 42.9 | 42.6 | 39.6 | 42.1 | 39.7 | 43.9 | 43.9 | 41.3 |
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>80,000 | 27.7 | 35.2 | 25.5b | 17.2b | 30.2 | 17.8c | 16.3c | 16.3c | 33.3 |
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Very good or excellent | 43.8 | 49.7 | 46.8 | 35.6b | 48.3 | 21.2c | 28.0c | 25.9 c | 38.9g |
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Good | 38.1 | 34.8 | 38.2 | 40.2 | 35.9 | 48.8 | 39.9 | 49.7 | 44.8 |
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Fair or poor | 18.1 | 15.5 | 15.0 | 24.2b | 15.8 | 30.0c | 32.1c | 24.4g | 16.3 |
History of diabetes, hypertension, coronary artery disease, heart failure, or strokeh | 71.7 | 62.1 | 70.3e | 80.6b | 69.0 | 87.4c | 77.8c | 86.5c | 70.5 | |
Takes medication for ≥1 chronic condition | 90.5 | 87.2 | 90.3 | 93.3i | 89.9 | 95.4c | 90.7 | 94.9j | 86.8 |
aCell percentages are based on weighted data for everyone in that age or race/ethnic group. Ns at the top of columns are the unweighted number of respondents in that group.
bSignificantly differs (
cSignificantly differs (
dGED=General Educational Development (credential indicating that an individual has met high school level academic skills).
eSignificantly differs (
fBased on estimates from a 2011 health survey of the same health plan membership. A household income ≤$35,000 qualifies an individual for income-subsidized, low income housing.
gSignificantly differs (
hIn ≥1 of the health plan’s chronic disease registries for these conditions.
iSignificantly differs (
jSignificantly differs (
Although 81% of seniors aged 65-79 had a mobile phone, less than one-third (31.2%) had a smartphone, and less than half (47.2%) were able to send and receive text messages (see
Ability to use the Internet to get health information from websites or to communicate with others significantly differed by race/ethnicity and age (see
Whereas 80% of non-Hispanic white and Chinese seniors were able to send and receive email, only approximately 60% of black, Filipino, and Latino seniors were able to do so, even with help (see
Nearly two-thirds (64.2%) of seniors thought that they could use the patient portal on their own to send a secure message to their doctor or to look up a lab test result, 60.6% thought they could print out information or forms from a website, and 50.9% thought they could get to a website to get information or forms if given a URL verbally or in print (see
Seniors were presented with five health care–related tasks that could be carried out using the patient portal and asked to indicate which of the methods listed they currently used or were willing to use and which method they most preferred to use. They were also asked how they preferred to receive information about health care benefits and health newsletters. Finally, they were asked how they would like to get health information and advice, in addition to getting this information directly from their doctor and other clinicians.
Seniors’ access to digital devices, Internet, and email, by age group and race/ethnicitya.
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All | By age group | By race/ethnicity | ||||||||
65-79 (N=2602) | 65-69 (n=841) | 70-74 (n=878) | 75-79 (n=883) | Non-Hispanic white (n=849) | Black (n=567) | Latino (n=653) | Filipino (n=219) | Chinese |
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81.0 | 88.4 | 84.3 | 71.2b | 82.2 | 82.8 | 72.6c | 70.2c | 77.0 | ||
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Has a smartphone | 31.2 | 43.4 | 33.9d | 18.7b | 32.8 | 30.5 | 22.0c | 19.6c | 26.6e | |
|
Able to receive text messages | 47.2 | 61.5 | 51.4d | 31.4b | 47.4 | 53.6f | 41.0f | 45.1 | 54.9 | |
|
If has a mobile phone | 60.5 | 71.2 | 63.1g | 46.5b | 60.5 | 59.6 | 68.4h | 59.9 | 67.0 | |
|
81.5 | 91.5 | 82.5b | 73.1b | 85.3 | 70.7c | 63.0c | 57.5c | 82.8 | ||
|
Desktop, laptop, or netbook | 79.5 | 90.4 | 80.0b | 71.2b | 83.5 | 69.1c | 61.1c | 53.1c | 79.8 | |
|
Tablet | 25.1 | 34.3 | 27.4g | 15.6b | 27.1 | 16.0c | 12.6c | 20.1f | 28.3 | |
|
Has home Internet | 83.8 | 91.3 | 85.5d | 76.2b | 87.4 | 71.9g | 68.4h | 61.0c | 84.8 | |
|
|||||||||||
|
Able to use on own or with help | 79.4 | 88.9 | 81.5b | 68.7b | 83.9 | 64.4c | 58.2c | 53.3c | 79.2 | |
|
Uses on own | 69.4 | 80.7 | 70.8b | 59.4b | 74.4 | 51.8c | 48.0c | 39.3c | 69.4 | |
|
Uses with help or proxy uses | 10.0 | 8.2 | 10.7 | 10.3 | 9.5 | 12.6 | 10.2 | 14.0 | 9.8 | |
|
If uses the Internet, how frequently goes online | (n=1886) | (n=707) | (n=637) | (n=542) | (n=714) | (n=390) | (n=410) | (n=125) | (n=247) | |
|
Daily | 64.2 | 70.0 | 64.3 | 58.8d | 66.2 | 51.1c | 53.7c | 47.2c | 66.0 | |
|
≤1x/wk | 16.6 | 16.7 | 16.7 | 18.8 | 15.1 | 28.3c | 25.8c | 26.2f | 14.4 | |
|
(n=2594) | (n=839) | (n=876) | (n=879) | (n=848) | (n=565) | (n=650) | (n=217) | (n=314) | ||
|
Able to use by self or with help | 79.3 | 86.1 | 81.2g | 72.1b | 83.4 | 63.2c | 59.6c | 58.5c | 80.8 | |
|
Uses on own | 70.0 | 80.2 | 71.9g | 60.3b | 74.7 | 52.6c | 49.1c | 43.0c | 72.6 | |
|
Uses with help or proxy uses | 9.3 | 5.9 | 9.3 | 11.8d | 8.8 | 10.6 | 10.6 | 15.6h | 8.2 | |
|
Has an email address | 76.2 | 82.4 | 78.4 | 68.6b | 80.5 | 60.0c | 57.9c | 51.3c | 76.3 | |
|
Has own email address | 63.8 | 68.5 | 66.3 | 57.2b | 67.3 | 51.2c | 48.2c | 42.6c | 65.7 | |
|
Shares an email address (may also have own) | 11.3 | 13.5 | 11.4 | 9.5 | 13.0 | 6.2c | 6.9c | 4.9h | 8.2f | |
|
Uses someone else’s email address | 1.8 | 1.4 | 1.7 | 2.2 | 1.4 | 3.1f | 3.6f | 3.7f | 2.4 | |
|
If receives email, how frequently checks for email | (n=1866) | (n=682) | (n=630) | (n=554) | (n=699) | (n=377) | (n=420) | (n=124) | (n=246) | |
|
|
Daily | 67.9 | 70.4 | 68.6 | 64.8 | 70.0 | 49.5c | 59.5c | 56.4h | 70.5 |
|
|
≤1x/wk | 13.8 | 12.4 | 12.2 | 17.4 | 12.3 | 24.6c | 22.9c | 22.2f | 13.7 |
aCell percentages based on weighted data for everyone in that age or race/ethnic group. Ns at top of columns are the unweighted number of respondents in that group except when analyses are restricted to a subset of that group.
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fSignificantly differs (
gSignificantly differs (
hSignificantly differs (
Seniors’ perceptions of their ability to perform health care–related tasks involving digital technologya.
Task | All | By age group | By race/ethnicity | ||||||||
65–79 |
65-69 |
70-74 |
75-79 |
Non-Hispanic white |
Black |
Latino |
Filipino |
Chinese |
|||
|
|||||||||||
|
Could do by self | 64.2 | 76.1 | 66.3b | 52.9c | 68.6 | 47.2d | 44.3d | 40.9d | 63.3 | |
|
Could do by self or with help | 79.7 | 88.2 | 81.7b | 71.1c | 82.9 | 67.2d | 63.6d | 66.1d | 79.6 | |
|
|||||||||||
|
Could do by self | 64.5 | 76.4 | 66.8b | 52.8c | 69.0 | 45.7d | 43.6d | 40.2d | 68.2 | |
|
Could do by self or with help | 78.4 | 87.3 | 80.5b | 69.2c | 81.9 | 63.8d | 60.6d | 61.2d | 82.6 | |
|
|||||||||||
|
Could do by self | 65.4 | 76.0 | 68.9b | 53.2c | 69.4 | 51.2d | 45.3d | 45.0d | 67.2 | |
|
Could do by self or with help | 76.4 | 86.1 | 78.9b | 66.3c | 79.8 | 63.3d | 59.3d | 58.4d | 79.7 | |
|
|||||||||||
|
Could do by self | 35.2 | 51.4 | 38.1c | 20.0c | 37.6 | 28.1d | 23.0d | 21.6d | 34.3 | |
|
Could do by self or with help | 45.9 | 63.5 | 49.3c | 28.7c | 47.7 | 40.6e | 34.6d | 36.1f | 47.4 | |
|
|||||||||||
|
Could do by self | 52.1 | 62.5 | 55.0g | 41.0c | 54.6 | 49.4 | 37.8d | 34.5d | 50.3 | |
|
Could do by self or with help | 59.3 | 70.9 | 61.3b | 48.5c | 61.0 | 57.3 | 46.2d | 50.9e | 59.5 | |
|
|||||||||||
|
Could do by self | 50.9 | 66.9 | 52.1c | 38.0c | 55.2 | 37.9d | 30.4d | 24.3d | 51.3 | |
|
Could do by self or with help | 60.2 | 75.3 | 61.8c | 47.4c | 63.3 | 49.6d | 42.6d | 42.9d | 65.2 | |
|
|||||||||||
|
Could do by self | 60.6 | 72.0 | 63.2b | 48.8c | 65.3 | 46.2d | 39.2d | 30.8d | 60.7 | |
|
Could do by self or with help | 70.4 | 81.7 | 72.3c | 59.9c | 74.0 | 58.1d | 50.8d | 50.8d | 74.3 |
aCell percentages are based on weighted data for everyone in the age or race/ethnic group.
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fSignificantly differs (
gSignificantly differs (
Overall, over half (58.2%) of seniors said they send secure messages to their doctors in non-urgent situations, approximately the same percentage as communicates by phone (see
Methods used and preferred for performing tasks that could be done through the patient portala .
|
All | By age group | By race/ethnicity | ||||||||
65-79 | 65-69 | 70-74 | 75-79 | Non-Hispanic white | Black | Latino | Filipino | Chinese | |||
|
(N=2534) | (n=822) | (n=858) | (n=854) | (n=826) | (n=555) | (n=628) | (n=215) | (n=310) | ||
|
|
||||||||||
|
|
Uses this method | 58.2 | 70.0 | 58.7b | 48.8b | 63.6 | 33.8c | 36.6c | 32.2c | 55.6d |
|
|
Most prefers this method | 51.8 | 63.9 | 53.8e | 40.5b | 57.7 | 25.2c | 29.0c | 25.0c | 46.7f |
|
|
||||||||||
|
|
Uses this method | 8.2 | 8.5 | 9.8 | 6.0 | 8.1 | 7.0 | 7.3 | 10.1 | 14.5f |
|
|
Most prefers this method | 4.8 | 3.5 | 6.4 | 3.5 | 4.9 | 3.3 | 4.4 | 3.3 | 7.5 |
|
|
||||||||||
|
|
Uses this method | 53.7 | 48.0 | 50.0 | 62.6b | 48.8 | 76.9c | 71.3c | 75.9c | 58.0d |
|
|
Most prefers this method | 43.5 | 32.9 | 39.9g | 56.0b | 37.5 | 71.6c | 67.0c | 72.7c | 45.8d |
|
(N=2594) | (n=838) | (n=874) | (n=882) | (n=847) | (n=566) | (n=649) | (n=219) | (n=313) | ||
|
|
||||||||||
|
|
Uses this method | 54.4 | 64.9 | 55.4e | 45.5b | 58.8 | 31.1c | 36.3 | 33.5c | 63.6 |
|
|
Most prefers this method | 38.9 | 47.3 | 41.2 | 30.1c | 42.9 | 21.4c | 21.4c | 15.6c | 45.7 |
|
|
||||||||||
|
|
Uses this method | 32.9 | 35.7 | 35.1 | 27.8g | 34.2 | 25.0c | 26.1f | 32.7 | 28.2 |
|
|
Most prefers this method | 19.1 | 19.6 | 20.4 | 17.2 | 20.4 | 11.1c | 15.1d | 19.6 | 10.7c |
|
|
||||||||||
|
|
Uses this method | 66.6 | 74.4 | 69.3 | 57.5b | 70.8 | 43.6c | 48.4c | 51.6c | 71.4 |
|
|
Most prefers this method | 57.9 | 66.8 | 61.2 | 47.3c | 63.1 | 32.3c | 36.3c | 35.2c | 56.5 |
|
|
||||||||||
|
|
Uses this method | 51.8 | 48.6 | 50.3 | 56.0g | 47.9 | 71.2c | 66.3c | 68.3c | 53.6 |
|
|
Most prefers this method | 35.6 | 28.7 | 33.1 | 44.0c | 30.5 | 57.6c | 54.0c | 63.2c | 40.4f |
|
|
||||||||||
|
|
Uses this method | 18.4 | 16.7 | 17.1 | 21.4 | 17.7 | 27.9c | 22.1 | 15.1 | 13.5 |
|
|
Most prefers this method | 7.3 | 5.1 | 6.5 | 9.9g | 7.1 | 10.5 | 11.0g | 3.9 | 3.8 |
|
(N=2258) | (n=715) | (n=764) | (n=779) | (n=731) | (n=521) | (n=561) | (n=187) | (n=258) | ||
|
|
||||||||||
|
|
Uses this method | 35.7 | 45.0 | 39.1 | 24.8b | 39.7 | 20.0c | 22.1c | 12.8c | 36.1 |
|
|
Most prefers this method | 33.5 | 42.3 | 37.4 | 21.7b | 37.2 | 16.3c | 19.8c | 12.2c | 34.3 |
|
|
||||||||||
|
|
Uses this method | 63.3 | 58.5 | 59.5 | 71.6b | 61.4 | 70.8f | 72.3c | 72.7f | 59.0 |
|
|
Most prefers this method | 57.2 | 51.2 | 53.3 | 66.9b | 55.9 | 61.8 | 64.5f | 67.5d | 52.8 |
|
|
||||||||||
|
|
Uses this method | 20.6 | 18.9 | 19.8 | 23.0 | 17.3 | 37.0c | 31.3c | 32.6c | 26.0f |
|
|
Most prefers this method | 9.5 | 6.5 | 9.7 | 11.4g | 7.1 | 22.4c | 16.1c | 20.9c | 12.9d |
|
(N=2586) | (n=835) | (n=871) | (n=880) | (n=843) | (n=565) | (n=646) | (n=218) | (n=314) | ||
|
|
||||||||||
|
|
Uses this method | 24.3 | 29.2 | 24.4 | 20.6e | 26.6 | 16.0c | 16.7c | 9.5c | 20.6 |
|
|
Most prefers this method | 9.4 | 11.5 | 9.0 | 8.5 | 10.4 | 6.4d | 6.0d | 2.5d | 8.9 |
|
|
||||||||||
|
|
Uses this method | 44.8 | 54.1 | 48.9 | 32.8b | 48.9 | 28.4c | 26.2c | 24.7c | 44.7 |
|
|
Most prefers this method | 29.2 | 33.6 | 35.1 | 18.3b | 33.0 | 12.3c | 13.3c | 9.3c | 25.4d |
|
|
||||||||||
|
|
Uses this method | 39.2 | 41.8 | 41.3 | 34.5 | 39.7 | 45.0 | 40.3 | 25.6c | 34.0 |
|
|
Most prefers this method | 13.4 | 14.8 | 14.3 | 11.3 | 13.2 | 18.2c | 18.7d | 6.5d | 11.7 |
|
|
||||||||||
|
|
Uses this method | 67.8 | 61.9 | 65.4 | 75.1g | 65.1 | 78.6d | 75.2c | 85.1c | 68.6 |
|
|
Most prefers this method | 47.8 | 39.5 | 41.1 | 62.4b | 43.2 | 63.5c | 62.8c | 80.5c | 54.9f |
|
|
||||||||||
|
|
Uses this method | 5.2 | 6.4 | 6.7 | 2.4e | 5.3 | 5.7 | 4.1 | 5.3 | 3.6 |
|
|
Most prefers this method | 0.8 | 0.6 | 1.5 | 0.1 | 0.8 | 1.2 | 0.3 | 1.2 | 0.5 |
|
(N=2570) | (n=832) | (n=862) | (n=876) | (n=839) | (n=560) | (n=643) | (n=216) | (n=312) | ||
|
|
||||||||||
|
|
Uses this method | 49.1 | 59.1 | 52.0g | 38.2b | 54.5 | 28.3c | 27.4c | 21.1c | 41.6c |
|
|
Most prefers this method | 35.1 | 42.3 | 39.3 | 24.2b | 39.3 | 19.1c | 18.6c | 12.8c | 27.8c |
|
|
||||||||||
|
|
Uses this method | 7.4 | 11.5 | 7.9 | 3.6b | 7.8 | 6.7 | 5.1d | 3.9d | 6.3 |
|
|
Most prefers this method | 1.3 | 1.8 | 2.0 | <0.1 | 1.5 | <0.1 | 0.8 | 0.3 | 0.9 |
|
|
||||||||||
|
|
Uses this method | 12.5 | 11.5 | 13.3 | 12.1 | 12.6 | 17.1d | 10.3 | 7.8 | 10.0 |
|
|
Most prefers this method | 2.0 | 2.5 | 1.6 | 2.2 | 1.9 | 3.5 | 2.4 | 2.2 | 1.3 |
|
|
||||||||||
|
|
Uses this method | 77.2 | 70.4 | 76.1 | 83.5b | 75.3 | 85.0c | 83.1c | 87.4c | 79.3 |
|
|
Most prefers this method | 56.6 | 50.1 | 52.4 | 67.0b | 52.2 | 71.4c | 71.1c | 82.4c | 66.6c |
|
|
||||||||||
|
|
Uses this method | 18.5 | 13.2 | 18.8g | 21.7e | 18.3 | 24.0d | 21.4 | 12.4 | 12.9 |
|
|
Most prefers this method | 5.5 | 3.9 | 5.3 | 7.0 | 5.4 | 6.6 | 8.7d | 3.2 | 3.4 |
aMost preferred method restricted to people who indicated only one method or a most preferred method if >1 method was indicated. Cell percentages are based on weighted data for everyone in the age or race/ethnic group. Ns at top of columns are the unweighted number of respondents in that group.
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fSignificantly differs (
gSignificantly differs (
hRestricted to seniors who take medications for a chronic condition and do not rely totally on others to order their prescription refills.
i“By phone using the phone keypad to enter answers to questions read by a nice taped voice.”
Half of seniors were willing to get information about health care benefits (50.9%) or health newsletters (54.5%) by email (see
Of those who indicated use of any method for these health care tasks and communications, approximately 90% of seniors indicated a preferred method for communicating with doctors, ordering prescription refills, and completing health questionnaires. Around 80% had a preferred method for obtaining lab test results or receiving reminders. All indicated a health communications preference. Although seniors aged 65-69 and 70-74 were significantly more likely to prefer secure messaging with their doctor than leaving a phone message, the reverse was true for 75-79 year olds. Similarly, non-Hispanic white seniors were significantly more likely to prefer secure messaging over use of the phone, but black, Latino, and Filipino seniors were significantly more likely to prefer phone calls over secure messaging, with Chinese seniors equally split between these two options. A similar demographic pattern was observed for viewing lab test results online versus receiving them in a mailed letter. Seniors aged 65-69 were significantly more likely to order prescription refills online than by phone, but the opposite was true for the two older groups and for all race/ethnic groups. All age and race/ethnic groups significantly preferred getting reminders by regular email rather than in a secure message that required them to sign into the patient portal. With respect to completion of health questionnaires, seniors in the two older age groups and in all race/ethnic groups significantly preferred to use a print versus an online questionnaire accessed by the patient portal. Combining online and facility-based touchscreen tablet data entry (both of which enable real-time direct flow of member data into the electronic medical record) resulted in very little increase in the percentages that preferred digital questionnaires. Across all age and race/ethnic groups, seniors preferred getting health care benefit information and newsletters by regular mail than by email. Seniors in the oldest age group were significantly (
Methods seniors are willing to use and would prefer for receiving newsletters and benefits informationa.
|
All | By age group | By race/ethnicity | ||||||||
65-79 | 65-69 | 70-74 | 75-79 | Non-Hispanic white | Black | Latino | Filipino | Chinese | |||
|
(N=2581) | (n=838) | (n=865) | (n=878) | (n=839) | (n=564) | (n=647) | (n=219) | (n=312) | ||
|
|
||||||||||
|
|
Willing to use this method | 38.6 | 41.9 | 42.5 | 31.1b | 41.4 | 27.8c | 27.7c | 22.9c | 37.5 |
|
|
Most prefers this method | 17.8 | 17.6 | 22.1 | 12.2d | 19.8 | 8.6c | 10.7c | 8.5c | 14.5 |
|
|
||||||||||
|
|
Willing to use this method | 23.3 | 31.9 | 25.9 | 13.7b | 25.6 | 15.9c | 12.2c | 12.5c | 18.1e |
|
|
Most prefers this method | 8.9 | 10.6 | 10.5 | 5.6f | 10.0 | 5.7e | 3.5c | 2.9c | 6.7 |
|
|
||||||||||
|
|
Willing to use this method | 22.8 | 34.6 | 22.7b | 14.6b | 25.1 | 13.8c | 13.1c | 13.3c | 18.1g |
|
|
Most prefers this method | 7.7 | 12.9 | 6.9 | 5.1 | 8.8 | 2.9c | 4.1g | 1.2c | 5.7 |
|
|
||||||||||
|
|
Willing to use this method | 50.9 | 59.5 | 55.0 | 39.3b | 54.8 | 36.0c | 34.0c | 30.7c | 47.9h |
|
|
Most prefers this method | 34.3 | 41.1 | 39.5 | 22.8b | 38.6 | 17.3c | 18.4c | 12.7c | 26.9g |
|
|
||||||||||
|
|
Willing to use this method | 76.6 | 74.0 | 73.3 | 82.7f | 74.4 | 87.1c | 84.0c | 87.2c | 76.9 |
|
|
Most prefers this method | 60.7 | 52.6 | 56.4 | 72.1b | 57.3 | 73.3c | 75.3c | 78.8c | 64.1e |
|
|
||||||||||
|
|
Willing to use this method | 9.4 | 9.6 | 8.8 | 9.9 | 9.1 | 13.8g | 13.0g | 4.4g | 6.4 |
|
|
Most prefers this method | 0.6 | 0.9 | 0.3 | 0.7 | 0.4 | 1.8g | 2.5e | 0.4 | <0.1 |
|
(N=2377) | (n=769) | (n=790) | (n=818) | (n=815) | (n=480) | (n=594) | (n=187) | (n=301) | ||
|
|
||||||||||
|
|
Willing to use this method | 39.2 | 44.0 | 44.5 | 28.5b | 42.8 | 25.9c | 24.0c | 21.2c | 33.4g |
|
|
Most prefers this method | 21.6 | 22.6 | 25.5 | 16.0d | 23.9 | 11.4c | 13.3c | 11.7c | 17.3g |
|
|
||||||||||
|
|
Willing to use this method | 23.8 | 31.8 | 25.3d | 16.0b | 26.4 | 16.0c | 12.4c | 11.2c | 15.5c |
|
|
Most prefers this method | 10.4 | 11.9 | 12.1 | 7.0d | 11.8 | 6.7e | 5.0c | 1.4c | 7.1g |
|
|
||||||||||
|
|
Willing to use this method | 24.0 | 32.2 | 25.2d | 16.4b | 26.3 | 14.9c | 13.7c | 14.2c | 21.9 |
|
|
Most prefers this method | 9.5 | 13.9 | 10.4 | 5.3b | 10.5 | 5.5e | 5.1g | 4.8g | 10.5 |
|
|
||||||||||
|
|
Willing to use this method | 54.5 | 62.5 | 59.3 | 42.2b | 59.3 | 37.2c | 34.4c | 30.0c | 48.2e |
|
|
Most prefers this method | 38.4 | 44.0 | 44.2 | 26.6b | 42.7 | 21.2c | 22.1c | 16.5c | 32.0e |
|
|
||||||||||
|
|
Willing to use this method | 65.9 | 62.0 | 60.5 | 75.8b | 62.7 | 80.3c | 77.8c | 80.8c | 68.1 |
|
|
Most prefers this method | 58.7 | 51.9 | 52.3 | 71.7b | 54.1 | 76.4c | 76.6c | 82.2c | 65.1e |
aMost preferred method restricted to people who indicated only one method or a most preferred method if >1 method was indicated. Cell percentages are based on weighted data for everyone in the age or race/ethnic group. Ns at top of columns are the unweighted number of respondents in that group.
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fSignificantly differs (
gSignificantly differs (
hDiffers (
iRestricted to people who completed the longer form of the questionnaire.
Willingness to go online to perform health-related tasks was significantly higher among those who could use the Internet on their own or with some help than in the overall senior population, with the same patterns of significant age group and race/ethnic differences as seen for other measures (see
Percentages of 65-79 year olds who would be willing to have a video visit if their doctor did not think it was necessary for them to be seen in person. (A video visit enables a patient and doctor to see each other while they are talking by using a smartphone, tablet, or webcam-enabled computer).
Willingness to perform health care–related tasks onlinea.
|
All | By age group | By race/ethnicity | |||||||
65-79 | 65-69 | 70-74 | 75-79 | Non-Hispanic white | Black | Latino | Filipino | Chinese | ||
|
||||||||||
|
All | 58.2 | 70.0 | 58.7b | 48.8b | 63.6 | 33.8c | 36.6c | 32.2c | 55.6d |
|
Those who can use the Internet | 71.8 | 77.9 | 70.3b | 68.5b | 74.6 | 51.0c | 58.8c | 58.1c | 68.9 |
|
||||||||||
|
All | 54.4 | 64.9 | 55.4e | 45.5b | 58.8 | 31.1c | 36.3c | 33.5c | 63.6 |
|
Those who can use the Internet | 67.1 | 72.9 | 66.3b | 63.2 | 69.0 | 47.4c | 57.9c | 60.0c | 75.3 |
|
||||||||||
|
All | 35.7 | 45.0 | 39.1 | 24.8b | 39.7 | 20.0c | 22.1c | 12.8c | 36.1 |
|
Those who can use the Internet | 44.4 | 50.2 | 47.8 | 34.2b | 46.8 | 29.9c | 36.3c | 22.8c | 43.4 |
|
||||||||||
|
All | 49.1 | 59.1 | 52.0g | 38.2b | 54.5 | 28.3c | 27.4c | 21.1c | 41.6c |
|
Those who can use the Internet | 61.5 | 66.6 | 63.5 | 53.7b | 64.7 | 43.7c | 45.3c | 39.4c | 51.5c |
|
||||||||||
|
All | 7.4 | 11.5 | 7.9 | 3.6b | 7.8 | 6.7 | 5.1d | 3.9d | 6.3 |
|
Those who can use the Internet | 9.1 | 13.0 | 9.4 | 5.1b | 9.3 | 9.5 | 7.8 | 5.6 | 7.9 |
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All | 35.4 | 42.4 | 38.4 | 26.4b | 39.1 | 22.4c | 20.5c | 15.9c | 28.3g |
|
Those who can use the Internet | 44.3 | 47.7 | 46.5 | 37.6b | 46.4 | 34.0c | 33.6c | 29.8c | 34.9c |
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All | 24.5 | 27.4 | 27.9 | 18.0e | 26.7 | 17.5c | 15.2c | 11.6c | 24.3 |
|
Those who can use the Internet | 30.5 | 30.7 | 33.4 | 25.7 | 31.4 | 26.8 | 24.9c | 20.2c | 30.3 |
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All | 33.8 | 44.6 | 36.6e | 22.0b | 36.5 | 24.8g | 20.6g | 19.3g | 31.6 |
|
Those who can use the Internet | 41.7 | 49.5 | 44.8 | 29.5b | 42.8 | 37.7 | 32.8g | 34.3d | 36.0 |
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All | 50.9 | 59.5 | 55.0 | 39.3b | 54.8 | 36.0c | 34.0c | 30.7c | 47.9 |
|
Those who can use the Internet | 63.5 | 68.1 | 67.8 | 53.5b | 65.1 | 56.3c | 55.5c | 52.9c | 58.1 |
aAbility to use the Internet was assigned based on a “Yes” answer to the question “Can you use the Internet to get information from websites or to communicate with others?” Most senior Internet users were able go online on their own, but some indicated needing help or someone to go online for them. Ability to use email was assigned using the same type of question and responses. Cell percentages are based on weighted data for everyone in that age or race/ethnic group. Because percentages are based on responses to different questions, unweighted cell Ns vary. Most cell Ns can be ascertained from earlier tables, and they are also provided in
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fRestricted to seniors who take medications for a chronic condition and do not rely totally on others to order their prescription refills.
gSignificantly differs (
About 40.53% (93,667/231,080) of the seniors in the full study population did not use (or have a proxy use on their behalf) any of four patient portal features (secure message to a doctor, viewing lab test results online, ordering a prescription refill, or making a primary care or vision care appointment) in 2013. Of these non-portal users, 80.20% (75,120/93,667) were 70-79 years old (38.89%, 36,426/93,667, aged 75-79), and over half (56.49%, 52,911/93,667) had not registered for a patient portal account.
To learn more about nonusers of the patient portal, we linked survey respondents with their 2013 patient portal utilization data. We found that among those who had not used any of the four portal features in 2013, 56.6% did not use the Internet even with help, 12.8% used it but needed help or someone else to use it for them, and 30.6% were able to use it on their own. Latino and Filipino nonusers of portal features were significantly more likely than non-Hispanic white nonusers (70.1%, 73.5% vs 52.5%, respectively,
Seniors with a high school education or less were significantly less likely to have used any of the four patient portal features than those with at least some college or with a 4-year college degree (46.0% vs 71.6% and 81.6%, respectively,
Of the 26% (288/843, unweighted) of non-portal users who expressed interest in learning how to use patient portal features, 50.4% were currently unable to use the Internet by themselves, and 25.3% did not have easy access to a digital device to go online.
Use of patient portal features in 2013 is significantly lower among seniors with ≤ high school education and in fair-poor health, and lower among Black, Latino, and Filipino seniors in these vulnerable groups.
Seniors were asked whether, in their opinion, the health plan’s shift toward using its website has made it easier or harder for them to perform five health care–related tasks (getting information about health plan benefits and costs, communicating with their doctor, getting lab test results, getting information about health conditions and treatments, and getting health education) and overall managing their health care. Results are shown in
Seniors’ opinions on the effect of technology on ease of health care communication and educationa .
Health care–related tasks | All | By age group | By race/ethnicity | ||||||
65-79 | 65-74 | 75-79 | Non-Hispanic white | Black | Latino | Filipino | Chinese | ||
|
|||||||||
|
Easier | 46.8 | 50.2 | 38.9b | 46.1 | 48.0 | 47.2 | 53.7 | 50.5 |
|
Harder | 16.8 | 13.8 | 23.7c | 15.0 | 20.9d | 23.4e | 29.8f | 21.1f |
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|||||||||
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Easier | 73.3 | 76.5 | 65.9g | 76.1 | 58.2f | 63.2f | 61.4f | 69.3 |
|
Harder | 11.8 | 9.6 | 17.0g | 10.1 | 16.7d | 18.7f | 24.4f | 14.6 |
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|||||||||
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Easier | 74.8 | 77.5 | 68.6b | 77.2 | 60.0f | 65.6f | 64.9d | 74.8 |
|
Harder | 11.1 | 9.1 | 15.7b | 9.5 | 16.6e | 17.1f | 21.0f | 14.2 |
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|||||||||
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Easier | 59.5 | 62.6 | 52.4b | 60.3 | 53.3h | 57.3 | 56.4 | 62.0 |
|
Harder | 12.9 | 10.6 | 18.2g | 11.0 | 18.0d | 18.4d | 26.8f | 18.3h |
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|||||||||
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Easier | 57.6 | 61.5 | 48.2g | 58.3 | 52.5 | 54.3 | 56.6 | 57.8 |
|
Harder | 12.4 | 10.1 | 17.8b | 10.5 | 16.8d | 20.0f | 25.6f | 17.1h |
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|||||||||
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Easier | 61.7 | 66.2 | 50.8g | 63.2 | 53.5d | 56.5i | 54.4h | 61.7 |
|
Harder | 12.1 | 10.0 | 17.3b | 10.5 | 15.5c | 19.0f | 23.9f | 15.4 |
aSeniors were asked whether the health plan’s shift toward using its website and patient portal has made it easier or harder for them to obtain information and communicate with their doctors. Analyses were restricted to people who expressed an opinion (including that there had been no change) about their ability to perform this task. Cell percentages are based on weighted data for everyone in the age or race/ethnic group. Because people did not indicate opinions about all tasks, unweighted cell Ns vary; they are provided in
bSignificantly differs (
cSignificantly differs (
dSignificantly differs (
eSignificantly differs (
fSignificantly differs (
gSignificantly differs (
hSignificantly differs (
iSignificantly differs (
Our study found that in 2013, nearly 80% of adults aged 65-79 in a large integrated health care delivery system in Northern California were able to use the Internet and email, had easy access to computers, mobile phones, and home Internet, and were using the health plan’s patient portal. The percentages of Internet users in our three senior age groups were not much higher than those found in the 2012 Pew Internet Project national survey of seniors [
Specifically, among seniors who had been health plan members for over 2 years, we documented age and race/ethnic disparities among KPNC members aged 65-79 in registration for and actual use of the health plan’s patient portal secure features during the 2013 calendar year, even though all members were being actively encouraged at multiple touch points (eg, clinicians, receptionists, and electronic and mail media communications) to sign up for and use the patient portal. Using survey data linked to patient portal registration and utilization, we showed that race/ethnic disparities in use of the patient portal were present even among seniors who have the ability to use the Internet. We also showed that seniors with a high school education or less and those who were in fair or poor health were less likely to have used the patient portal than better educated and healthier seniors, respectively, and that within the more vulnerable groups, blacks, Latinos, and Filipinos were less likely to be portal users than non-Hispanic white and Chinese seniors. Previous studies have found similar race/ethnic and age-related disparities in the use of health plan patient portal features by seniors [
Our research found significant differences between ethnic Filipino and Chinese seniors in their use of the health plan patient portal and their ability to use and preferences for using the Internet for health-related purposes, with ethnic Chinese seniors in most cases looking similar to non-Hispanic white, and ethnic Filipinos looking more similar to blacks and Latinos. These two ethnic groups are usually combined along with other Asian ethnicities into a broad “Asian” race/ethnic group. Our results suggest that doing so may be misleading for purposes of planning roll-outs of services and dissemination of health information, resulting in inequities across multiple Asian subgroups.
More importantly, we demonstrated that descriptive statistics about Internet access and preferences for digital engagement that are based on seniors as a group and not broken out by age cohorts and race/ethnicity within age cohorts can provide a deceptively optimistic picture of seniors’ readiness to engage with patient portals and Web-based information than is the reality for certain segments of the senior population, specifically those who are older, non-white, less educated, and lower income. Evaluation of portal use among the population segments with lower ability/desire to use Internet-based communication will require that researchers pay attention to population sampling and post-stratification weighting of respondent data in the absence of data on the full population, such as we employed for our comparisons of account registration and utilization of patient portal features. In conducting our research, we also found that black, Latino, and Filipino seniors, especially those who had not signed up to use the health plan’s patient portal, were significantly less likely to respond to our survey than non-Hispanic white and Chinese seniors, who were significantly more likely to be digitally connected and using the patient portal. This suggests that studies concerned with profiling eHealth engagement in multi-ethnic senior populations or specifically studying racial or ethnic differences need to employ stratified random samples that oversample these race/ethnic groups, not only because individually they tend to make up a smaller percentage of the total senior population, but also because seniors in these race/ethnic groups are much less likely to respond to a research survey. This also extends to evaluating Internet and eHealth use and preferences in populations that include other vulnerable subgroups, such as people with low income and low educational attainment.
Ability to use the Internet and having an email address are basic requirements for registering for a patient portal account that enables a member to access secure portal features, complete online health plan questionnaires that feed responses directly into the electronic medical record, and have secure email interactions with health care providers and other health plan staff. As more information and health care–related transactions become available through patient portals and health plan websites, and assumptions are made by health plan medical staff and workflow planners that most adult members will migrate to Web-based interactions, seniors who cannot or do not want to use their health plan’s patient portal and website may find it harder to interact and access information and services. In our survey, less than half of seniors who had not used any of the four major patient portal features during the year prior to the survey were able to use the Internet or email even with someone’s help and one fourth did not have access to a device that could be used to go online. In addition to disparities in Internet and email access, we found that the majority of black, Latino, and Filipino seniors and close to half of 75-79 year olds did not think they would be able to perform many of the most common health care–related tasks that could be done using the patient portal and health plan website. Further, we found that these race/ethnic and age group differences in perceived ability to use and preference for using the patient portal and website for these tasks persisted even among those seniors who were Internet users. This suggests that successful efforts to reduce race/ethnic- and age-related disparities among seniors in use of patient portals and other eHealth modalities and thus reduce the risk of exacerbating disparities in health and health care access will require more than increasing access to the Internet through community-based WiFi or increasing efforts to promote patient portal registration and use.
Although some seniors who were not using patient portal features or the health plan website say they would be willing to do so if required by the health plan, they also indicated that they needed to have a person (not a Web-based video or guide) provide instruction and support for using these Web-based tools. A 2013 survey from the Pew Research Center found that 66% of non-Internet-using seniors would require help from another person to go online [
Advances in Web design, digital technologies, and greater availability of free Internet access outside the home are increasingly making it easier for older adults with poor eyesight, physical disabilities, and little computer and Internet experience to go online for health. Also, websites continue to improve based on user feedback. However, if seniors are not aware of these advances or do not receive the training and support they need, they may not attempt to use these tools, especially if they had negative experiences in the past. Watkins and Xie recommend tailoring eHealth literacy interventions to take into account known learning styles of different senior demographic subgroups as well as the starting level of experience in using the Internet rather than using a one-size-fits-all approach [
Some seniors in our survey who do not use the Internet expressed concern that they will miss important information that is readily available only on the website or via emails and that they will lose the ability to handle their health care-related tasks without having a relative or informal caregiver act as their intermediary. Some also indicated a fear that as Web-based health care interactions become more the norm, they are going to lose the in-person and phone-based interactions with their doctors and other staff that they feel are important to nurturing their relationships with their health care providers. This is consistent with “digital immigrants” having different expectations and preferences for how they want to interact with their health care providers and the health care system that may not align with what is not only acceptable to but desired by the “digital native” majorities of adult health plan members and health care providers. Our survey results suggest that the eHealth digital divide is already causing significant percentages of black, Latino, Filipino, and older seniors to feel that a shift toward website-based health communications on the part of their health plan has made it harder for them to access information and communicate with their doctors. This is especially concerning because as our study and other research [
Health care organizations and government programs will need to take into account differences in technology access and communication/transaction preferences when designing and implementing health and health care-related communication strategies for culturally and economically diverse adult populations with a wide age range. Although the Internet and other digital technologies offer convenience and access to a greater amount of health-related information, self-care resources, and services than people have had in the past and will play a major role in Health 2.0 [
Health care organizations should expect that some segments of the senior population will prefer not to become “digital immigrants” and want to continue to communicate about health-related matters and engage in other types of health care-related transactions in person, by phone, and using hardcopy print rather than electronic materials. Morrow and Chin suggest that in this regard, it is very important for health care providers to send a clear message to senior patients and their family members that patient portals, secure email, Web-based patient education resources, apps, and other eHealth modalities are meant to supplement, not supplant the modes of personal patient-provider relationship that many seniors value [
Screenshot of a Doctor Home Page developed by The Permanente Medical Group to make it easier for health plan members to use the health plan's website and patient portal.
Our study had several strengths. First, the patient portal component of this study was done using an extremely large and diverse cohort of Medicare-age health plan members. The health plan itself represents an integrated health care delivery system with a highly developed website and patient portal. This enabled us to compare age-group and race/ethnic differences in patient portal use in a population where all members had received extensive encouragement to sign up for the patient portal over at least 2.5 years and had access to the same health care system and patient portal.
Second, by linking patients’ electronic medical record data with use of patient portal features, we were able to restrict comparisons of use of the patient portal for online viewing of laboratory test results and online ordering of prescription refills to seniors who would have had cause to perform these tasks—something that has not been done in previous studies with this or other health plan populations.
Third, because of the size and diversity of the cohort, we were able to document significant age-group disparities and race/ethnic disparities within age groups in this Medicare-age population using directly observed percentages, not just odds ratios from logistic regression models. We were similarly able to document that these disparities persisted even among those who were registered to use the patient portal and among those with chronic health conditions who might be expected to have greater need for engaging with the health care system.
Fourth, our survey sample enabled us to compare access to and ability to use digital devices and the Internet, as well as experience with and preferences for performing health care–related tasks using digital technology across age cohorts and race/ethnic groups in a way that has not been done for a population of adults aged 65 and older. We were also able to link our survey data to patient portal registration and utilization data. This resulted in our discovery of a differential survey response rate by patient portal account creation status (our proxy for Internet access in the portal study component), which we subsequently incorporated into the survey weighting factor. This also made it possible for us to examine social determinants of use of a patient portal using real utilization data and self-reported social determinant variables such as education and Internet access.
Fifth, we were able to differentiate between patients’ use of or willingness to use digital technology for health care–related tasks and their preferences for using these technologies in general.
One limitation of the patient portal component of this study is that we did not have information for the full study population about overall Internet access practices and other factors such as education and income to determine whether disparities were due to these types of social determinants or to patient preferences. As a proxy for the propensity to use the Internet, we compared use of patient portal features among seniors who had created a patient portal account in 2013; this is similar to what has been used by other studies [
Although we were able to examine whether differences in use of secure features during the observation year persisted among those who had signed up to use the patient portal by the end of the year, we were not able to determine whether the need to obtain laboratory test results or refill prescriptions occurred before or after members created their patient portal account. We assumed that all members would have had the opportunity to use the portal to perform these tasks had they desired because everyone in this study population had, by design, been a member for at least 18 months before the study period and could have immediately activated their patient portal account when they created it.
The response rate to the survey was lower than we desired, especially among black, Latino, and Filipino seniors, which limited our ability to study race/ethnic differences within age groups. The small numbers in these groups may also limit generalizability. The numbers of Filipino and Chinese seniors included in the survey were also smaller than we would have liked because these ethnic groups had originally been selected only for pilot study purposes. Had the analysis of patient portal use in the full study sample been completed prior to the survey, we likely would have included comparable numbers of Filipinos and Chinese in the sample to increase the precision of our statistics and to have more statistical power to test for differences in access and preference between these two Asian ethnic groups.
We did not include a question about personal or family income in the survey because a large percentage of seniors had left the income question blank in previous health plan surveys or been disconcerted about being asked. We did ask whether cost was a factor in not having Internet at home and used self-reported education as a measure of socioeconomic status. We also used income data from a 2011 KPNC Member Health Survey to characterize income differences among the age and race/ethnic groups in this health plan, but we were not able to shed light on the joint effect of education and income on access to and preference for using eHealth technology.
Finally, no validated measures of health literacy were included in our survey, so we were unable to study the extent to which health literacy mediates differences in seniors’ access to and preferences for using health information technology as part of their health care.
Our study documents digital disparities by age, race/ethnicity, and educational attainment within the senior age group with regard to access to digital devices, ability to use the Internet and email, and preferences for going online or using traditional telephones to interact with health care providers and the health care system in the United States. Our results suggest that the same subgroups of vulnerable seniors that have previously been shown to have difficulties with health care access may also be hampered by the eHealth digital divide from obtaining timely health information and advice, using digital monitoring devices as part of chronic disease self-management, and taking advantage of cost-saving Internet-based care options such as online purchase of prescription medications and medical equipment and having video visits with doctors and patient educators. Because well-known disparities in health status and health care access and use are being extended into the eHealth arena, we do not expect digital technologies to reduce socioeconomic gradients automatically.
In order to ensure that eHealth disparities do not increase health status and health care access disparities between more privileged and less privileged groups, eHealth initiatives should embed tracking systems and measures of disparities in their access and use. Health care delivery systems, government agencies, and other organizations that serve multiculturally, multilinguistically, multigenerationally, and socioeconomically diverse populations should analyze these data to identify access and use gaps for eHealth resources by seniors separately from the broader population. Most importantly, access to and use of eHealth resources should be monitored not only for the full senior population or the segment already known to be going online, but also by social determinants such as race/ethnicity, older age, low educational attainment, and low income. Government health agencies and quality assurance organizations focused on senior health and health care should hold health care providers and systems accountable for demonstrating that all patients are satisfied with the ease of communicating with their health care providers and the health care systems, their ability to get health and health care–related information and advice, and their ability to access reduced-cost services and products, regardless of whether they are able to go online.
Further research is needed to explore the extent to which age group and race/ethnic eHealth disparities affect patient-provider communication, use of patient education and disease management resources, and ultimately, health outcomes in different settings. Research is also needed to develop and evaluate the impact of improvements in the design of websites, patient portals, online patient education resources, self-monitoring tools, and eHealth devices that access Internet-based health resources aimed at reducing the physical, cognitive, psychomotor, emotional, and financial barriers that currently inhibit many seniors from using online resources for health-related purposes. Finally, more research is needed to develop and test interventions targeting seniors that aim to increase use of patient portals, eHealth devices, and other eHealth resources, including eHealth literacy programs, multimodal methods of providing website-specific training and support, and making home Internet more accessible to those on limited incomes.
Cell denominators for
Survey questionnaire.
Cell denominators for
Kaiser Permanente Northern California
non–limited English proficient
This study was funded by Kaiser Permanente Northern California Region’s Community Benefit Program. We wish to acknowledge the contributions of the following people to this study: (1) Suzanne Gillespie at the Kaiser Permanente Center for Health Research for her valuable input as we were developing the survey content; (2) Hao Xiang in Kaiser Permanente National’s Digital Analytics and Insights group for preparing the kp.org utilization dataset used for the portal study; (3) Kaiser Permanente Division of Research survey team members Teresa Y Lin, Pete Bogdanos, Alice Ansfield, and Gary Salyer who assisted with survey data collection and data processing; (4) Diana Ruff, medical editor, for her help polishing our manuscript. Special thanks to all the Kaiser Permanente Northern California health plan members who took time to participate in the survey
NPG conceived and designed the study, developed the survey questionnaire, directed the survey used for the study, performed all analyses reported in the manuscript, and wrote the manuscript. MCH collaborated on the study design and questionnaire development, interpretation of the analyses, and the writing of the manuscript. Both authors read and approved the final manuscript.
None declared.