Objectives:

We reviewed the evidence on the barriers and drivers to the use of interactive consumer health information technology (IT) by specific populations, namely the elderly, those with chronic conditions or disabilities, and the underserved.

Data Sources:

We searched MEDLINE®, CINHAHL®, PsycINFO®, the Cochrane Controlled Trials Register and Database of Systematic Reviews, ERIC, and the American Association of Retired Persons (AARP) AgeLine® databases. We focused on literature 1990 to present.

Methods:

We included studies of all designs that described the direct use of interactive consumer health IT by at least one of the populations of interest. We then assessed the quality and abstracted and summarized data from these studies with regard to the level of use, the usefulness and usability, the barriers and drivers of use, and the effectiveness of the interactive consumer health IT applications.

Results:

We identified and reviewed 563 full-text articles and included 129 articles for abstraction. Few of the studies were specifically designed to compare the elderly, chronically ill, or underserved with the general population. We did find that several types of interactive consumer health IT were usable and effective in multiple settings and with all of our populations of interest. Of the studies that reported the impact of interactive consumer health IT on health outcomes, a consistent finding of our review was that these systems tended to have a positive effect when they provided a complete feedback loop that included (a) monitoring of current patient status, (b) interpretation of this data in light of established, often individualized, treatment goals, (c) adjustment of the management plan as needed, (d) communication back to the patient with tailored recommendations or advice, and (e) repetition of this cycle at appropriate intervals. Systems that provided only one or a subset of these functions were less consistently effective.

The barriers and drivers to use were most often reported as secondary outcomes. Many studies were hampered by usability problems and unreliable technology, primarily due to the research being performed on early stage system prototypes. However, the most common factor influencing the successful use of the interactive technology by these specific populations was that the consumers' perceived a benefit from using the system. Convenience was an important factor. It was critical that data entry not be cumbersome and that the intervention fit into the user's daily routine. Usage was more successful if the intervention could be delivered on technology consumers used every day for other purposes. Finally, rapid and frequent interactions from a clinician improved use and user satisfaction.

Conclusions:

The systems described in the studies we examined depended on the active engagement of consumers and patients and the involvement of health professionals, supported by the specific technology interventions. Questions remain as to (a) the optimal frequency of use of the system by the patient, which is likely to be condition-specific; (b) the optimal frequency of use or degree of involvement by health professionals; and (c) whether the success depends on repeated modification of the patient's treatment regimen or simply ongoing assistance with applying a static treatment plan. However, it is clear that the consumer's perception of benefit, convenience, and integration into daily activities will serve to facilitate the successful use of the interactive technologies for the elderly, chronically ill, and underserved.