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:

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 Overview

• Status: Completed
• Conditions: Elderly
• Intervention / Treatment: Behavioral: Pop-up alert

• Study Type: Interventional
• Enrollment (Actual): 719
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Massachusetts
    • Springfield, Massachusetts, United States, 01199
      • Baystate Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years and older (Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

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

2

Arms and Interventions

Participant Group / Arm	Intervention / 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.	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
The percentage of elderly patients who receive a specified high-risk medication from the Beer's list.	Earlier of hospital stay or end of study

Secondary Outcome Measures

Outcome Measure	Time Frame
The average number of specified high risk medications prescribed per patient.	Earlier of hospital stay or end of study
Restraint use	Earlier of hospital stay or end of study
Falls	Earlier of hospital stay or end of study
Length of stay	Earlier of hospital stay or end of study
Total Cost	Earlier of hospital stay or end of study
Discharge status	6 months

Collaborators and Investigators

• Sponsor: Baystate Medical Center
• Investigators: Principal Investigator: Linda J Canty, MD, Baystate Medical Center

Study record dates

Study Major Dates

• Study Start: April 1, 2013
• Primary Completion (Actual): June 1, 2013
• Study Completion (Actual): June 1, 2013

Study Registration Dates

• First Submitted: December 15, 2009
• First Submitted That Met QC Criteria: December 16, 2009
• First Posted (Estimate): December 17, 2009

Study Record Updates

• Last Update Posted (Estimate): March 10, 2015
• Last Update Submitted That Met QC Criteria: March 7, 2015
• Last Verified: March 1, 2015

More Information

Terms related to this study

• Keywords: Patient safety; Electronic prescribing; Inappropriate medications; Elderly patients in the hospital
• Other Study ID Numbers: 132454