title: Leading a horse to water: using automated reminders to increase use of online decision support.
abstract: Online knowledge resources are generally underused despite their potentially beneficial effect on patient care. We are interested in ways to increase use of context-specific links, called infobuttons, from clinical information systems to such resources. We used log files to examine the impact of classroom instruction on infobutton use to pinpoint a particular context where infobuttons appeared to be underused by particular users. We sent users e-mail suggestions about infobuttons and reviewed log files to examine the impact of the messages. Log files showed that usage by medical students and housestaff following classroom instruction was initially high but then tapered off. In particular, we found that infobuttons were infrequently used in an outpatient, but not inpatient, medication application. We sent 552 suggestion e-mails to 371 users after log files showed that they used other resources in that context. Fifty-two of these users used infobuttons within 31 days of receiving the e-mail, which represents 25.9% of recipients who used any resource during the same period. Users responded best when the e-mail was sent within 5 days of using the resource. Traditional instruction had a limited sustained effect on improving the use of infobuttons. An automated method for sending targeted suggestions complemented the traditional approach.
authors.affiliation: National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
authors.forename: James J
authors.initials: JJ
authors.lastname: Cimino
authors.forename: Dmitriy V
authors.initials: DV
authors.lastname: Borovtsov
mesh_terms: D020000:Decision Support Systems, Clinical / Q000706:statistics & numerical data*; D034742:Electronic Mail / Q000706:statistics & numerical data*; D009518:New York; D009862:Online Systems / Q000706:statistics & numerical data; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D017010:Reminder Systems / Q000706:statistics & numerical data*