Enhancing the Detection and Management of Adverse Drug Events in Nursing Homes

• ClinicalTrials.gov Identifier: NCT01531088
• Recruitment Status: Completed
• First Posted: February 10, 2012
• Last Update Posted: January 5, 2016
• Sponsor: University of Pittsburgh
• Collaborator: RAND
• Information provided by (Responsible Party): University of Pittsburgh

Study Description

Brief Summary:

Adverse drug events (ADEs) are the most clinically significant and costly medication-related problems in nursing homes (NH) and are associated with an estimated 93,000 deaths a year and as much as $4 billion of excess healthcare expenditures. Current ADE detection and management strategies that rely on pharmacist retrospective chart reviews (i.e., usual care) are inadequate. Active medication monitoring systems are recommended by many safety organizations as an alternative to detect and manage ADEs. These systems have been shown to be less expensive, faster, and identify ADEs not normally detected by clinicians in the hospital setting. The investigators developed and pilot-tested an active medication monitoring system for use in a single NH, where it was shown to detect ADEs with a high degree of accuracy and at a rate of nearly 2.5 times that of usual care. The long-term objective of our proposed research is to improve patient safety with respect to medications in NHs. The short-term objectives or specific aims of our proposed research are to determine if NH patients managed by physicians who receive active medication monitoring alerts have more ADEs detected, have a faster ADE management response time, and can result in more cost-savings from a societal perspective compared to usual care.

Condition or disease	Intervention/treatment	Phase
Adverse Drug Events	Behavioral: Active medication monitoring	Not Applicable

Detailed Description:

To accomplish the aims outlined in our brief summary above, the investigators will conduct a cluster randomized controlled trial among up to 86 NH physicians working in one of 4 UPMC Health System nursing homes (NHs) in Southwestern Pennsylvania for a period of 12 months. Our hypotheses are that NH patients managed by physicians who receive active medication monitoring alerts will have more ADEs detected, will have a faster ADE management response time, and will result in cost-savings from a societal perspective compared to usual care. This application by an early stage investigator is responsive to PA-09-070 AHRQ Health Services Research Projects and several of its research portfolio priority areas (health information technology, patient safety, and value) by addressing how medication management systems can be used to improve the quality and safety of medication management, as well as improve healthcare decision making. This study represents the first large, well-controlled, comprehensive examination of an active medication monitoring system in the NH.

Study Design

• Study Type: Interventional (Clinical Trial)
• Actual Enrollment: 36 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Masking: Single (Outcomes Assessor)
• Primary Purpose: Health Services Research
• Official Title: Enhancing the Detection and Management of Adverse Drug Events in the Nursing Home
• Study Start Date: January 2012
• Actual Primary Completion Date: April 2014
• Actual Study Completion Date: April 2015

Arms and Interventions

Arm	Intervention/treatment
No Intervention: Usual care; Recommendations made by consultant pharmacists as part of their federally-mandated medication regimen review process
Experimental: Active medication monitoring; Active medication monitoring system providing consultant pharmacists with alerts representing potential adverse drug events	Behavioral: Active medication monitoring; Active medication monitoring system providing consultant pharmacists with alerts representing potential adverse drug events.

Outcome Measures

Primary Outcome Measures :

1. Adverse drug event detection [ Time Frame: 12 months ]
   Number of adverse events detected

Secondary Outcome Measures :

1. Adverse drug event response time [ Time Frame: 12 months ]
   Response time to adverse drug event detection

Eligibility Criteria

• Ages Eligible for Study: Child, Adult, Older Adult
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

Criteria

Inclusion Criteria:

All physicians participating in the study must be a credentialed attending physician at at least one of four UPMC Nursing Homes: UPMC Canterbury Place, UPMC Cranberry Place, UPMC Heritage Place, and/or UPMC Seneca Place.

Exclusion Criteria:

Physicians not credentialed as an attending physician at at least one of four UPMC Nursing Homes: UPMC Canterbury Place, UPMC Cranberry Place, UPMC Heritage Place, and/or UPMC Seneca Place.

Contacts and Locations

Locations

United States, Pennsylvania

University of Pittsburgh

Pittsburgh, Pennsylvania, United States, 15206-3701

Sponsors and Collaborators

University of Pittsburgh

RAND

Investigators

• Principal Investigator: Steven M. Handler, MD, PhD, CMD; University of Pittsburgh

More Information

Publications of Results:

Handler SM, Cheung PW, Culley CM, Perera S, Kane-Gill SL, Kellum JA, Marcum ZA. Determining the incidence of drug-associated acute kidney injury in nursing home residents. J Am Med Dir Assoc. 2014 Oct;15(10):719-24. doi: 10.1016/j.jamda.2014.03.014. Epub 2014 May 10.

Other Publications:

Handler SM, Kane-Gill SL, Kellum JA. Optimal and early detection of acute kidney injury requires effective clinical decision support systems. Nephrol Dial Transplant. 2014 Oct;29(10):1802-3. doi: 10.1093/ndt/gfu211. Epub 2014 Jun 9. No abstract available.

• Responsible Party: University of Pittsburgh
• ClinicalTrials.gov Identifier: NCT01531088
• Other Study ID Numbers: 0015923; AHRQ1R01HS018721 ( Other Grant/Funding Number: AHRQ )
• First Posted: February 10, 2012
• Last Update Posted: January 5, 2016
• Last Verified: January 2016

Keywords provided by University of Pittsburgh:

Nursing Home

Additional relevant MeSH terms:

Drug-Related Side Effects and Adverse Reactions; Chemically-Induced Disorders