Timely Nudge About Lab Results to Increase myGeisinger Uptake

Overview

The purpose of the current study is to test whether sending email communications in a timely manner - when patients have laboratory results available to view on the myGeisinger patient portal - increases enrollment in the portal.

Online patient portals are convenient tools that improve patient access to healthcare services while often reducing burden to both patients and providers. However, many patients have not enrolled in such portals, including Geisinger's patient portal, known as myGeisinger. The purpose of the current study is to test whether sending myGeisinger enrollment information in a timely manner - when the benefits of enrolling are most readily available - increases enrollment. Specifically, messages will be timely in terms of lab test results having just been made available online, with the added benefit that patients can view their results prior to receiving them via mail. Unenrolled patients who recently had a laboratory procedure ordered and whose results are now ready for sharing will be informed via email that their lab results are available. At the same time, these patients will be reminded that these results can be viewed online through myGeisinger. The primary outcome measure of interest, myGeisinger enrollment rates, will be compared between the emailed population and a control group that similarly has lab results available but will not be contacted. In addition, two different versions of the email communication will be tested. One will highlight that the patient will have to go through a sign-up process before viewing test results (in the service of transparency). The other will provide a presumed direct link to view those results, via a button that potentially serves as a pre-commitment step to undergo the registration process ("foot in the door" effect). Secondary analyses will assess differences in enrollment rates as well as unsubscribe rates between the email versions. Exploratory analyses will further examine differences in the rates at which patients opened and clicked on enrollment links within the two emails. Statistical analyses will employ generalized linear models with a binary distribution and log-link function.

Conditions

Interventions

Eligibility

Locations (1)

Outcomes