A Systematic Review of Patient Acceptance of Consumer Health Information Technology

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In this article a systematic literature review was performed to identify variables promoting consumer health information technology (CHIT) acceptance, or barriers in acceptance of CHIT among patients.[1]

Background

Consumer health informatics is a branch of health informatics that addresses the needs of the consumer by using consumer health information technologies (CHITs). CHITs are defined as computer-based systems that are designed to facilitate information access and exchange, enhance decision making, provide social and emotional support, and help behavior changes that promote health and well-being. While the potential for using CHITs to improve health care has been acknowledged, these technologies are still not always accepted by patients for variety of reasons, including poor device usability, insufficient training on how to use the technology, lack of computer skills, and low self-efficacy. There is a considerable body of research testing the feasibility, acceptability, and effectiveness of various CHITs for primary health care service delivery, in general, or patient self-care at home, in particular.

Methods

“Acceptance” of technology has been defined in four primary ways: (1) satisfaction with the technology, (2) use or adoption of the technology, (3) efficient or effective use of the technology, and (4) intention or willingness to use the technology.Online database literature searches were performed in early Dec 2006, and again in Feb 2009 to obtain relevant research articles to review. The electronic bibliographic databases used for searching were Web of Science, Business Source Elite, CINAHL, Communication and Mass Media Complete, MEDLINE, PsycArticles, and PsycInfo. The search terms employed were patient*, senior*, elder*, old*, disabilit*, accept*, abandon*, intent*, intention to use, reject*, satisf*, use*, utiliz*, computer*, eHealth, e-health, e-mail, health* informat*, Internet, technolog*, web*, telemedicine, and combinations of them. The authors manually searched the following health informatics journals to reduce the likelihood of missing relevant articles: Journal of the American Medical Informatics Association, International Journal of Medical Informatics, Journal of Medical Internet Research, and Telemedicine and e-Health.[1]

Results

The search returned 1,871 articles and their titles and abstracts were read. Based on the selection criteria, 185 articles were retained for more detailed review. Fifty-two articles met the criteria and were included in this review study. 94 different predictors of acceptance were tested in the studies reviewed.[1]

Discussion

Organizational variables were tested, few human-technology interaction or environmental variables were examined, and social variables were studied:

Patient Factors

Technology acceptance studies in the field of information systems have suggested that age, gender, education level, computing experience, and voluntariness of use moderate the effects of performance expectancy, effort expectancy, subjective norm, and computer anxiety on acceptance.

  • studies found that acceptance increased with higher education.
  • Prior experience or exposure to computer/health technology appears to be associated with increased acceptance.
  • Although not a consistent effect, generally, older adults are less likely to accept CHITs. This could possibly be due to less computer familiarity or literacy among older patients.
  • Most of the studies that tested the effect of gender demonstrated that gender had no direct impact on acceptance. However, studies of other types of technologies have found that gender was a significant moderator of computer anxiety and perceived behavioral control.Previous studies demonstrated that women were more likely to report higher computer anxiety than men and perceived behavioral control was more salient for women in the early stages of experiencing technology.
  • Studies showed that physical, visual, and cognitive limitations are associated with decreased acceptance.

Human–Technology Interaction Factors

Davis' Technology Acceptance Model posits perceived usefulness and perceived ease of use as the main predictors of technology acceptance.

  • All studies that tested the influences of usefulness, ease of use, and computer/technology self-efficacy demonstrated that those variables were significant predictors of acceptance.
  • Computer anxiety was tested in 3 of the 52 studies, and all three studies indicated that computer anxiety was negatively associated with acceptance. Feelings of anxiety surrounding computers can be negatively associated with perceived ease of use, and in turn influence acceptance.

Organizational Factors

  • Organizational factors that were found to lead to increased acceptance included being less satisfied with medical care services, being less satisfied with one's health plan, being less reliant on others for transportation, having Internet skill training, being less satisfied with the amount of disease treatment-related information given by physician, having a regular primary care provider, attending one of the two study hospitals, being in an academic medical center (vs. veterans affairs hospital), having difficulty accessing necessary health care, having more trust in one's health care provider, having more trust in the technology vendor, and having a higher external control belief.
  • Nurse training of patients or technical help lines for patients may influence acceptance through perceived ease of use, perceived usefulness, and self-efficacy.
  • Support from their clinic or hospital, are believed to promote more favorable beliefs about the technology among patients, which could then improve acceptance.
  • The CHITs might also change the organization of patient's daily lives or daily routines. If those changes are large, and the large changes are perceived as introducing extra workload with low utility, acceptance could be impacted.

Environmental Factors

Environmental factors refer to the physical aspects of the environment. Lighting, noise, temperature, housekeeping, and air flow might all affect CHIT acceptance.

  • Poor lighting could cause readability problems and physical discomfort when using a computer-based (health) information system.
  • noise and thermal discomfort, which can cause sensory disruption, also hold relevance in CHIT acceptance.

Social Factors

social factors concern the influences of others/groups to which one belongs.

  • Patients might be more or less likely to accept CHIT depending on, for example, the extent to which their physician, home care nurse, children, or grandchildren urge them to use it.

Task Factors

  • Individuals were more likely to demonstrate negative perceptions about a new technology when the technology caused a greater change in the nature of the task.

Conclusion

Evidence does show that CHITs can improve patients' quality of life and well-being, and increase medication adherence. However, technologies cannot help facilitate self-monitoring and self-management or improve patients' health outcomes when patients do not accept the technology. Further, current CHIT users may abandon CHITs when they perceive the technology as disadvantageous or functionally incompatible with their needs, existing values, or past experiences. Therefore, in order for any patient health information technologies to be successfully implemented, the needs of patient end-users (physical, psychological, and social) must be adequately met and addressed.

Comments

Consumer Health information technology can improve preventive care and help patients manage chronic disease conditions. Other than patient acceptance of Consumer HIT, Physician budgets in implementing Personal Health Records or Patient portals and physician reimbusment for preventive care services and secure messaging, may affect efficient use of CHIT.

References

  1. 1.0 1.1 1.2 Or, C. K. L., & Karsh, B.-T. (2009). A Systematic Review of Patient Acceptance of Consumer Health Information Technology. Journal of the American Medical Informatics Association : JAMIA, 16(4), 550–560. http://doi.org/10.1197/jamia.M2888