JMIR Publications

ABSTRACT

Background:

As the number of secure electronic messages increases between patients and clinicians, there is a need to explore and understand how patients and clinicians are using those messages, and what they are saying in them.

Objective:

To explore the patient and clinical staff characteristics associated with content exchanged in secure messages.

Methods:

We coded 18,309 messages that were part of threads initiated by 1031 patients with hypertension and/or diabetes from a large urban health system. We conducted four sets of analyses to identify associations between (1) patient characteristics and the types of messages they sent; (2) clinical staff characteristics and the types of messages they sent; (3) staff characteristics and the types of messages patients sent to them; and (4) patient characteristics and the types of messages they received from clinic staff. We used logistic regression to estimate the strength of the associations.

Results:

We found that younger patients had reduced odds for sharing clinical updates (OR=.77; 95% CI: .65 to .91) and requesting prescription refills (OR=.77; 95% CI: .65 to .90), but greater odds for sending a variety of scheduling requests (P-value <.05). Females had reduced odds for self-reporting biometrics (OR=.78; 95% CI: .62 to 0.98) but greater odds for responding to a clinician (OR=1.20; 95% CI: 1.02 to 1.42) and seeking medical guidance (OR=1.19, 95% CI: 1.01 to 1.40). Compared to White patients, Black patients had 2.68 greater odds to request preventive care (95% CI: 1.30 to 5.51) but less likely to request a new or changed prescription (OR=.72; 95% CI: .53 to .98) or laboratory or other diagnostic procedures (OR=.66; 95% CI: .46 to .95). Clinic staff had lower odds of sharing medical guidance with younger (OR=.83; 95% CI:.69 to 1.00) and uninsured patients (OR=.21; 95% CI: .06 to .73), but had two times greater odds of sharing medical guidance with patients with public payers (95% CI: 1.26 to 3.25) compared to patients with private payers. Clinic staff had reduced odds for confirming to female patients that their requests were fulfilled (OR=.82; 95% CI: 0.69 to .98).

Conclusions:

This is the first research to associate patient and clinic staff characteristics with specific types of message content. It is important to recognize that similar to in-person communication, differences exist in communication patterns based on those characteristics. The differences we found in content use based on patient characteristics could lead to the exacerbation of health disparities when content is associated with those health outcomes. Clinic staff and administrators should evaluate how secure messaging is used to ensure that disparities in care are not perpetuated via this communication modality.