Using Clinical Alerts to Decrease Inappropriate Medication Prescribing
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|ClinicalTrials.gov Identifier: NCT01034761|
Recruitment Status : Completed
First Posted : December 17, 2009
Last Update Posted : March 10, 2015
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).
- 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
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|
|Intervention Model:||Parallel Assignment|
|Masking:||Single (Outcomes Assessor)|
|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|
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|
- 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 ]
- The average number of specified high risk medications prescribed per patient. [ Time Frame: Earlier of hospital stay or end of study ]
- Restraint use [ Time Frame: Earlier of hospital stay or end of study ]
- Falls [ Time Frame: Earlier of hospital stay or end of study ]
- Length of stay [ Time Frame: Earlier of hospital stay or end of study ]
- Total Cost [ Time Frame: Earlier of hospital stay or end of study ]
- Discharge status [ Time Frame: 6 months ]
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 ClinicalTrials.gov identifier (NCT number): NCT01034761
|United States, Massachusetts|
|Baystate Medical Center|
|Springfield, Massachusetts, United States, 01199|
|Principal Investigator:||Linda J Canty, MD||Baystate Medical Center|