Using Clinical Alerts to Decrease Inappropriate Medication Prescribing
Using Clinical Alerts in a Computerized Provider Order Entry System to Decrease Inappropriate Medication Prescribing Among Hospitalized Elders
Introduction:
The Beers list identifies medications that should be avoided in persons 65 years or older because they are ineffective, pose an unnecessarily high risk, or a safer alternative is available. In a recent study, we found a high rate of prescribing of Beers list medications to hospitalized patients. At Baystate, 41% of medical patients received at least one Beers list drug classified as "high severity," meaning it carried a high risk for an adverse drug reaction, while 5% received 3 or more. Some Beers drugs have been associated with delirium and falls. When compared to Baystate patients who did not receive a high severity medication, those who did had an increased risk of mortality (7.8% vs. 5.2%), longer length of stay (5.5 days vs. 3.9 days) and higher costs ($11,240 vs. 6243).
Specific Aims:
- Quantify the impact of synchronous electronic alerts on physician prescribing of high-severity Beers' list drugs to hospitalized patients over the age of 65 years.
- Compare physician reactions to each drug-specific alert
Project Description:
We will develop a series of clinical alerts in CIS, Baystate's computerized provider order entry system, to reduce the use of potentially inappropriate medications among hospitalized elders. We will randomize providers to electronic alerts or usual care. Whenever a provider randomized to alerts attempts to place an order for a high-risk medication on the Beers list and the intended recipient is over 65 years of age, a synchronous alert (i.e. a "pop-up") will inform the physician about the risks associated with the medication and will propose safer alternatives.
We will collect data on physician ordering and patient outcomes comparing the number of Beers list prescriptions from providers receiving electronic alerts to those not receiving alerts. Our anticipated outcome is a decrease in inappropriate prescribing during the period when the electronic alerts are activated. Other potential outcomes include decrease in length of stay and a decrease in falls.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Massachusetts
-
Springfield, Massachusetts, United States, 01199
- Baystate Medical Center
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Hospitalized patients with Age > 65
Exclusion Criteria:
- None
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
No Intervention: Usual care
|
|
|
Experimental: Pop-up alerts
Providers will receive pop-up alerts in the electronic medical record when prescribing one of the specified medications from the Beers list.
|
Pop-up alert in the electronic medical record whenever the provider enters an order for a specified high risk medication from the Beers list.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
The percentage of elderly patients who receive a specified high-risk medication from the Beer's list.
Time Frame: Earlier of hospital stay or end of study
|
Earlier of hospital stay or end of study
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
The average number of specified high risk medications prescribed per patient.
Time Frame: Earlier of hospital stay or end of study
|
Earlier of hospital stay or end of study
|
|
Restraint use
Time Frame: Earlier of hospital stay or end of study
|
Earlier of hospital stay or end of study
|
|
Falls
Time Frame: Earlier of hospital stay or end of study
|
Earlier of hospital stay or end of study
|
|
Length of stay
Time Frame: Earlier of hospital stay or end of study
|
Earlier of hospital stay or end of study
|
|
Total Cost
Time Frame: Earlier of hospital stay or end of study
|
Earlier of hospital stay or end of study
|
|
Discharge status
Time Frame: 6 months
|
6 months
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Linda J Canty, MD, Baystate Medical Center
Study record dates
Study Major Dates
Study Start
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimate)
First Posted
Study Record Updates
Last Update Posted (Estimate)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
Other Study ID Numbers
- 132454
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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