Reducing the prescribing of heavily marketed medications: a randomized controlled trial.
BACKGROUND
Prescription drug costs are a major component of health care expenditures, yet resources to support evidence-based prescribing are not widely available.


OBJECTIVE
To evaluate the effectiveness of computerized prescribing alerts, with or without physician-led group educational sessions, to reduce the prescribing of heavily marketed hypnotic medications.


METHODS
Cluster-randomized controlled trial.


METHODS
We randomly allocated 14 internal medicine practice sites to receive usual care, computerized prescribing alerts alone, or alerts plus group educational sessions.


METHODS
Proportion of heavily marketed hypnotics prescribed before and after the implementation of computerized alerts and educational sessions.


RESULTS
The activation of computerized alerts held the prescribing of heavily marketed hypnotic medications at pre-intervention levels in both the alert-only group (adjusted risk ratio [RR] 0.97; 95% CI 0.82-1.14) and the alert-plus-education group (RR 0.98; 95% CI 0.83-1.17) while the usual-care group experienced an increase in prescribing (RR 1.31; 95% CI 1.08-1.60). Compared to the usual-care group, the relative risk of prescribing heavily marketed medications was less in both the alert-group (Ratio of risk ratios [RRR] 0.74; 95% CI 0.57-0.96) and the alert-plus-education group (RRR 0.74; 95% CI 0.58-0.97). The prescribing of heavily marketed medications was similar in the alert-group and alert-plus-education group (RRR 1.02; 95% CI 0.80-1.29). Most clinicians reported that the alerts provided useful prescribing information (88%) and did not interfere with daily workflow (70%).


CONCLUSIONS
Computerized decision support is an effective tool to reduce the prescribing of heavily marketed hypnotic medications in ambulatory care settings.


BACKGROUND
clinicaltrials.gov Identifier: NCT00788346.
Fortuna
Robert J
RJ
Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA, USA. rfortuna@post.harvard.edu
Zhang
Fang
F
Ross-Degnan
Dennis
D
Campion
Francis X
FX
Finkelstein
Jonathan A
JA
Kotch
Jamie B
JB
Feldstein
Adrianne C
AC
Smith
David H
DH
Simon
Steven R
SR
D020000:Decision Support Systems, Clinical / Q000592:standards; D004345:Drug Industry / Q000379:methods / Q000592:standards; D011307:Drug Prescriptions / Q000592:standards*; D055695:Electronic Prescribing / Q000592:standards*; D005260:Female; D006801:Humans; D006993:Hypnotics and Sedatives / Q000627:therapeutic use; D007388:Internal Medicine / Q000379:methods / Q000592:standards; D008297:Male; D040541:Marketing / Q000379:methods / Q000592:standards*; D016347:Medical Records Systems, Computerized / Q000592:standards*; D008875:Middle Aged; D010820:Physicians / Q000592:standards; D055553:Prescription Drugs / Q000627:therapeutic use*; D011364:Professional Practice / Q000592:standards
D006993:Hypnotics and Sedatives; D055553:Prescription Drugs