Patient Profiling and Provider Feedback to Reduce Adverse Drug Events
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About
Adverse drug events (ADE) present a unique focus for error reduction. Computerized provider order entry, with embedded clinical decision support, has great promise in reducing medication errors but preventable adverse drug events may still occur despite such systems.
Full description
Background:
Adverse drug events (ADE) present a unique focus for error reduction. Computerized provider order entry, with embedded clinical decision support, has great promise in reducing medication errors but preventable adverse drug events may still occur despite such systems.
Objectives:
The purpose of the study was to evaluate whether adding medication profiling (by using a retrospective drug utilization review program) to computerized provider order entry with embedded order checks (drug alerts) reduces the incidence of adverse drug events.
Methods:
Medication profiles mainly focused on possible drug-drug and drug-disease interactions, with some drug duplications. To do the medication profiles we licensed a proprietary computerized retrospective drug utilization review system. We randomly assigned over 900 patients to Usual Care or Provider Feedback. For patients in the latter group, selected providers were contacted by letter with pertinent information; electronic mail was used for follow-up contact. Clinical and other relevant data was retrospectively abstracted from the medical records for up to one year from the last medication profile for all patients. This was done by a pharmacist reviewer, using a study-derived instrument, and blinded to patient assignment. ADE incidence is the primary outcome of interest, with other outcomes such as ADE severity and preventability also assessed. We also developed and implemented provider surveys in pre- and post-profiling periods.
Status:
Pre and post survey results published. Adjunct study on clinical actions as a result of drug alerts published. Main study (profiling): manuscript in proces.
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Inclusion and exclusion criteria
Inclusion Criteria:
- patient must be alive
- patient must be currently active in GLA system
- medication for which alert was generated must be currently active
- patient provider must not be Peter Glassman
Exclusion Criteria:
Trial design
1,200 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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