Using Clinical Alerts to Decrease Inappropriate Medication Prescribing

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT01034761
Recruitment Status : Completed
First Posted : December 17, 2009
Last Update Posted : March 10, 2015
Information provided by (Responsible Party):
Linda Canty, MD, Baystate Medical Center

Brief Summary:


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:

  1. 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.
  2. 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.

Condition or disease Intervention/treatment Phase
Elderly Behavioral: Pop-up alert Not Applicable

Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 719 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single (Outcomes Assessor)
Primary Purpose: Prevention
Official Title: Using Clinical Alerts in a Computerized Provider Order Entry System to Decrease Inappropriate Medication Prescribing Among Hospitalized Elders
Study Start Date : April 2013
Actual Primary Completion Date : June 2013
Actual Study Completion Date : June 2013

Arm Intervention/treatment
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.
Behavioral: Pop-up alert
Pop-up alert in the electronic medical record whenever the provider enters an order for a specified high risk medication from the Beers list.

No Intervention: Usual care

Primary Outcome Measures :
  1. 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 ]

Secondary Outcome Measures :
  1. The average number of specified high risk medications prescribed per patient. [ Time Frame: Earlier of hospital stay or end of study ]
  2. Restraint use [ Time Frame: Earlier of hospital stay or end of study ]
  3. Falls [ Time Frame: Earlier of hospital stay or end of study ]
  4. Length of stay [ Time Frame: Earlier of hospital stay or end of study ]
  5. Total Cost [ Time Frame: Earlier of hospital stay or end of study ]
  6. Discharge status [ Time Frame: 6 months ]

Information from the National Library of Medicine

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Ages Eligible for Study:   65 Years and older   (Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No

Inclusion Criteria:

  • Hospitalized patients with Age > 65

Exclusion Criteria:

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT01034761

United States, Massachusetts
Baystate Medical Center
Springfield, Massachusetts, United States, 01199
Sponsors and Collaborators
Baystate Medical Center
Principal Investigator: Linda J Canty, MD Baystate Medical Center

Responsible Party: Linda Canty, MD, Assistant Clinical Professor of Medine, Baystate Medical Center Identifier: NCT01034761     History of Changes
Other Study ID Numbers: 132454
First Posted: December 17, 2009    Key Record Dates
Last Update Posted: March 10, 2015
Last Verified: March 2015

Keywords provided by Linda Canty, MD, Baystate Medical Center:
Electronic prescribing
Inappropriate medications
Patient safety
Elderly patients in the hospital