In this study of use of e-Health services over time in a well-defined population within an integrated system of care, our findings suggest that both access to and use of e-Health services are growing rapidly over time. Most persons, however, do not use e-Health services, even among those with known access. Not surprisingly, persons who are more likely to need health care tended to use the new electronic services more frequently compared with persons less likely to need health care. The findings also suggest that there is a significant and growing digital divide with respect to e-Health services across racial/ethnic and SES groups. These disparities persist even within an insured, integrated delivery system without any additional charges for e-Health services and despite general increases in the percentage of the population with access. To our surprise, these disparities were present in the population with established access to e-Health services.
It is important to note that e-Health services fundamentally are health care services delivered through new channels. Not everyone needs medical services, even among those who register for access, nor does everyone who needs services require them frequently. A recent study by Baker et al.12
found that most persons (78%) who reported prior use of the Internet for health information only used the Internet for health-related purposes sporadically. The low level of e-Health use suggests that much work is needed before these new services achieve their promise for improving quality and efficiency for the majority of Americans.13,14
Alternatively, the findings are reassuring given concerns that lower transaction costs associated with e-Health also could have led to a deluge of inappropriate patient use.
The apparent growing digital divide by race/ethnicity and by SES is concerning. Although the absolute numbers of nonwhite and low SES e-Health users is increasing over time, the numbers of white and high SES users was higher at baseline and is growing at a faster rate. In other words, this relative disparity not only persists as more persons start using e-Health services but actually widens over time. The findings reflect the growing body of literature suggesting a digital divide.12,15,16,17,18,19
In contrast to our findings, in a cross-sectional telephone interview study of Internet use for health information, Brodie et al.20
found that the divide in use by SES and by race/ethnicity disappeared once they adjusted for differences in Internet access. The discrepancy in findings could be a function of the differences in the types of service, definitions of use, or methods of data collection.
Further research is needed to confirm this growing divide as well as to assess the impact of this disparity in e-Health use on clinical outcomes. In addition, determining the root causes of these differences in use will be critical for informing policy decisions. In this study, we were able to investigate basic access to the online services as a potential cause. In future efforts, individual-level information on education, computer literacy, and income may help disentangle the effects of race/ethnicity and SES on e-Health use. Other potential explanations for disparities in use include differences in the quality or speed of the Internet connection (e.g., access at home vs. work, speed of the connection); the perceived value of the e-Health services, care delivery or other cultural preferences, or the level of trust and privacy concerns; or lags in the current location on similar adoption curves.
Our findings differ from other studies in several other important respects. First, we focused on use of actual e-Health services within an integrated system of care rather than on more nonspecific definitions such as use of the Internet for any health-related purpose or for seeking health information.12,15,21,22
In addition, we examined the proportion of use in the entire population rather than in a self-selected sample of subjects. Thus, it is not surprising that our estimates of use are lower than those of other published reports.12,13,16,23
As future studies examine the potential impacts of e-Health on quality, safety, and efficiency, focusing on e-Health services that are integrated with other forms of health care may be valuable. We also used a range of more stringent definitions of access, e.g., known access to services, which provide reasonable upper and lower boundaries of access. In addition, our study also examined use among households, which may provide an additional insight into “real-world” use, especially as more families engage in proxy use for children or elderly members. Finally, this study collected electronic data on actual e-Health service use rather than relying on self-reported data, which removes concerns about information bias that are common in other evaluations of patient behavior.
Some limitations of our study are that it did not capture individual measures of education, health beliefs, knowledge, trust in the health system, preferences for care, or awareness of the services. The use of neighborhood SES represents a reasonable proxy for individual SES; similarly, the known e-Health access represents a proxy of awareness. Other areas for further study include the usability of the e-Health services, the perceived need for specific services, and the value of e-Health services compared with alternatives (relative utility). Nevertheless, the findings persisted among patients with chronic diseases and high levels of expected need for clinical services; also, if present, the potential limitations would tend to bias toward a null result. The completeness and quality of the race/ethnicity data also could influence the study. The findings, however, were robust even after classifying all the subjects with missing data as white. In addition, the distribution of nonmissing race/ethnicity data resembles the distribution on survey and interview data from previous research studies. If there were a bias toward underreporting nonwhite race/ethnicity, this would tend to bias the results toward the null.
Other limitations include the relatively small number of e-Health services available in this IDS, and, conversely, the number of alternatives to e-Health services available in the IDS, such as through telephone call centers. Based on the patterns of use after the introduction of the drug refill service and real-time appointment scheduling, the addition of new e-Health services with high relative utility could drive increases in use considerably. These data also do not address subject preferences for the availability of the e-Health services or the perceived or real value of the services to patients who are using them. Finally, whether the disparities in e-Health use result in differences in access or clinical outcomes deserves additional study.
In short, access to and use of e-Health services are growing rapidly over time. Despite this growth, the number of users is only a small percentage of potential users, and even fewer are using services on a regular basis. There also appear to be increasing and significant disparities in e-Health use between persons of white and nonwhite race/ethnicity and between persons of low and high SES. These disparities were present even among persons with known access to these services. Given the potential of e-Health services to improve the quality and efficiency of health care delivery, more research is needed to understand why rates of use are low, particularly among some SES and racial/ethnic groups. In addition, as e-Health services improve and mature, information is needed on whether these disparities in use persist and on the impact of these trends on patient health, safety, and resource use.