Patients learning to read their doctors' notes: the importance of reminders

J Am Med Inform Assoc. 2016 Sep;23(5):951-5. doi: 10.1093/jamia/ocv167. Epub 2016 Feb 11.

Abstract

Objective: To examine whether patients invited to review their clinicians' notes continue to access them and to assess the impact of reminders on whether patients continued to view notes.

Materials and methods: We followed OpenNotes trial participants for 2 years at Beth Israel Deaconess Medical Center (BIDMC) and Geisinger Health System (GHS). Electronic invitations alerting patients to signed notes stopped at GHS after year 1, creating a natural experiment to assess the impact of reminders. We used generalized linear models to measure whether notes were viewed within 30 days of availability.

Results: We identified 14 360 patients (49 271 visits); mean age 52.2; 57.8% female. In year 1, patients viewed 57.5% of their notes, and their interest in viewing notes persisted over time. In year 2, BIDMC patients viewed notes with similar frequency. In contrast, GHS patients viewed notes far less frequently, a change starting when invitations ceased (RR 0.29 [0.26-0.32]) and persisting to the end of the study (RR 0.20 [0.17-0.23]). A subanalysis of BIDMC patients revealed that black and other/multiracial patients also continued to view notes, although they were overall less likely to view notes compared with whites (RR 0.75 [0.67-0.83] and 0.93 [0.89-0.98], respectively).

Discussion: As millions of patients nationwide increasingly gain access to clinicians' notes, explicit email invitations to review notes may be important for fostering patient engagement and patient-doctor communication.

Conclusion: Note viewing persists when accompanied by email alerts, but may decline substantially in their absence. Non-white patients at BIDMC viewed notes less frequently than whites, although their interest also persisted.

Keywords: electronic health records; medical records; patient activation; patient engagement; reminder systems.

MeSH terms

  • Adult
  • Confounding Factors, Epidemiologic
  • Electronic Health Records / statistics & numerical data*
  • Electronic Mail*
  • Ethnicity
  • Female
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Patient Access to Records
  • Patient Portals / statistics & numerical data*
  • Reminder Systems*