Use of e-Health Services between 1999 and 2002: A Growing Digital Divide

• Published in: Journal of the American Medical Informatics Association : JAMIA 2005-03, Vol.12 (2), p.164-171
• Main Authors: Hsu, John, Huang, Jie, Kinsman, James, Fireman, Bruce, Miller, Robert, Selby, Joseph, Ortiz, Eduardo
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Aged; California; Child; Child, Preschool; Delivery of Health Care, Integrated; Humans; Infant; Internet - statistics & numerical data; Longitudinal Studies; Middle Aged; Original Investigations; Prepaid Health Plans; Racial Groups; Socioeconomic Factors; Telemedicine - statistics & numerical data
• ISSN: 1067-5027; 1527-974X
• DOI: 10.1197/jamia.M1672

To evaluate the patterns of e-Health use over a four-year period and the characteristics of users. Longitudinal, population-based study (1999–2002) of members of a prepaid integrated delivery system. Available e-Health services included ordering prescription drug refills, scheduling appointments, and asking medical questions. Rates of known access to e-Health services, and of e-Health use each quarter. The number of members with known e-Health access increased from 51,336 (1.6%) in 1999 to 324,522 (9.3%), in 2002. The percentage of households in which at least one person in the household had access increased from 2.7% to 14.1%. Among the subjects with known access, the percentage of subjects that used e-Health at least once increased from 25.7% in 1999 to 36.2% in 2002. In the multivariate analysis, subjects who had a low expected clinical need, were nonwhite, or lived in low socioeconomic status (SES) neighborhoods were less likely to have used e-Health services in 2002. Disparities by race/ethnicity and SES persisted after controlling for access to e-Health and widened over time. Access to and use of e-Health services are growing rapidly. Use of these services appears to be greatest among persons with more medical need. The majority of subjects, however, do not use any e-Health services. More research is needed to determine potential reasons for disparities in e-Health use by race/ethnicity and SES as well as the implications of these disparities on clinical outcomes.