Patient reported barriers to enrolling in a patient portal

J Am Med Inform Assoc. 2011 Dec;18 Suppl 1(Suppl 1):i8-12. doi: 10.1136/amiajnl-2011-000473. Epub 2011 Nov 9.

Abstract

Background: Previous studies of patient portals have found low rates of enrollment and significant disparities in enrollment by race and ethnicity. As the reasons for these findings are unclear, we sought to identify patient reported barriers to enrollment in a patient portal.

Methods: We conducted a telephone survey of patients in one urban general internal medicine clinic. Patients were eligible if they did not enroll within 30 days of receiving an electronic order inviting participation. Our primary outcomes were: (a) reasons for not enrolling in the patient portal; (b) reasons for not attempting enrollment; and (c) perceived benefits of the portal.

Results: Participants' (N=159) mean age was 51 years, 48% were black, 72% female, and 70% had a college degree or greater. 63% of respondents not enrolling reported never attempting enrollment despite remembering receiving an order. Most of these 63% did not attempt enrollment because of lack of information or motivation. Smaller proportions reported not attempting enrollment because of negative attitudes toward the portal (30%) or computer related obstacles (8%). Overall, respondents favorably viewed most patient portal features, however black respondents were less likely than white respondents to consider features assisting self-management such as getting test results (69% vs 86%; p<0.05) as important. Adjusting for age, gender, education, and chronic disease did not substantially change results.

Conclusion: Strategies to increase enrollment in patient portals need to ensure patients understand patient portal features and receive follow-up reminders. Interventions to reduce racial disparities in enrollment must address attitudinal barriers and not focus solely on improving access.

MeSH terms

  • Attitude to Computers / ethnology
  • Attitude to Health* / ethnology
  • Chi-Square Distribution
  • Data Collection
  • Electronic Health Records / statistics & numerical data*
  • Female
  • Health Records, Personal*
  • Humans
  • Internal Medicine
  • Interviews as Topic
  • Male
  • Middle Aged
  • Patient Access to Records*