Shah NR et al. 2006 "Improving acceptance of computerized prescribing alerts in ambulatory care."

Shah NR, Seger AC, Seger DL, et al. Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc 2006;13(1):5-11.
"Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. Our objective was to improve clinician acceptance of drug alerts by designing a selective set of drug alerts for the ambulatory care setting and minimizing workflow disruptions by designating only critical to high-severity alerts to be interruptive to clinician workflow. The alerts were presented to clinicians using computerized prescribing within an electronic medical record in 31 Boston-area practices. There were 18,115 drug alerts generated during our six-month study period. Of these, 12,933 (71%) were noninterruptive and 5,182 (29%) interruptive. Of the 5,182 interruptive alerts, 67% were accepted. Reasons for overrides varied for each drug alert category and provided potentially useful information for future alert improvement. These data suggest that it is possible to design computerized prescribing decision support with high rates of alert recommendation acceptance by clinicians."
To determine the impact on clinician override rates of interrupting clinician workflow only for high-severity drug alerts in a primary care setting.
Type Clinic
Primary care
Other Information
The study was conducted in "31 adult primary care practices affiliated with Brigham and Women's Hospital (BWH) and Massachusetts General Hospital (MGH), two Boston teaching hospitals in the Partners HealthCare System. The sites included nine academic hospital-based clinics, 17 offsite clinics, and five community health centers."
Type of Health IT
Decision support system
Type of Health IT Functions
The authors "designed computerized alerts for the selected drug contraindications and all alerts were implemented at all 31 adult primary care sites in this study. The [computerized decision support system] CDSS uses data from the [EHR] about each patient's active medication list at time of medication ordering, problem list, laboratory results, and demographics to identify potential contraindications... When a clinician begins an order for a contraindicated medication, the alert appears as an on-screen warning identifying the contraindication... With Level 1 alerts, clinicians could not proceed with the prescription without either eliminating the contraindication or in the case of drug-pregnancy alerts, indicating that the patient was not pregnant or of child-bearing age... With Level 2 alerts, clinicians could proceed if they provided any override reason... Level 3 alerts were displayed for clinician viewing on the top of the computer screen in red letters," but did not require any response or override.
Context or other IT in place
Electronic medical records and a clinical decision support system were already in place.
Workflow-Related Findings
"Of the 3,875 interruptive duplicate drug class alerts, 2,965 (77%) were accepted..., predominantly via the order modifying action of discontinuing the preexisting medication."
"Of the 1,078 interruptive drug-drug interaction alerts, 13 Level 1 alerts were generated, all of which required the clinician to either cancel the order or discontinue the previous medication.... The remaining 1,065 drug-drug contraindication alerts were Level 2 alerts, of which 438 (41%) were accepted..., representing 250 order cancels and 188 order modifications."
"Among the 92 interruptive drug-lab alerts, 37 (40%) were accepted."
"Among the 19 interruptive drug-disease alerts, 10 (53%) were accepted, including nine where the clinician canceled the order and one where the clinician modified the order by choosing 'discontinue preexisting diagnosis.'"
"Among 118 interruptive drug-pregnancy alerts, 16 (14%) were Level 1...The order was canceled in two cases. For the remaining 14, the clinician indicated either the 'patient is not pregnant' or 'patient is not of child-bearing potential.' Among 102 Level 2 alerts, 10 (10%) were accepted."
"In our study, we examined in detail why clinicians continued with an alerted prescription and what actions they took as a consequence of the alert. In many instances, although the clinician continued ordering an alerted medication, he or she also eliminated the potential contraindication (facilitated by the CDSS) by discontinuing the preexisting medication or removing an inaccurate diagnosis. Other times, although the contraindication persisted, the alert achieved its intended effect by altering clinician behavior (i.e., ordering extra monitoring)."
"The problem of incomplete information was especially prominent with the Level 2 drug-pregnancy alerts in which virtually all the override reasons stated the patient was not pregnant. It is often difficult for the computer to verify a patient's pregnancy status based on laboratory values alone, since usually there is not a repeat test performed after a miscarriage or delivery."
"Among the 5,182 interruptive drug alerts presented, the order was canceled in 993 (19%) and modified in 2,482 (48%), resulting in a 67% accept rate."
"Of the 1,707 overridden alerts, 245 had no override reason because the clinician chose "Other" from the coded responses, but then left the free-text box blank."
"We found high user acceptance of ambulatory computerized prescribing alerts when using a selective knowledge base and minimizing workflow interruptions. By implementing tiered alerts, we limited alert burden by assigning 71% of triggered alerts to a noninterruptive display mode. Clinicians accepted the more selective interruptive alerts two-thirds of the time...We believe the high clinician acceptance of our alerts was achieved by presenting the clinicians with fewer but more meaningful alerts."
"Accept rates varied considerably among different alert categories. The highest accept rate was observed in the duplicate drug class category (77%), followed by drug-disease alerts (53%). The lowest accept rate of 10% was seen among the drug-pregnancy alerts."
Study Design
Only postintervention (no control group)
Study Participants
Study participants were "prescribing medical staff [which] included 701 clinicians, composed of 224 attending physicians, 249 resident physicians, 35 nurse practitioners, and 193 ancillary staff including nurses and medical assistants."