Using Clinical Alerts to Decrease Inappropriate Medication Prescribing

2014-08-27 03:17:11 | BioPortfolio



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.

Study Design

Allocation: Randomized, Control: Placebo Control, Intervention Model: Parallel Assignment, Masking: Single Blind (Outcomes Assessor), Primary Purpose: Prevention




Pop-up alert


Baystate Medical Center
United States




Baystate Medical Center

Results (where available)

View Results


Published on BioPortfolio: 2014-08-27T03:17:11-0400

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