Patterns in nursing home medication errors: disproportionality analysis as a novel method to identify quality...

Area of Science:

• Healthcare Quality Improvement
• Patient Safety Research
• Pharmacovigilance

Background:

• Traditional analysis of medication error data may miss subtle associations.
• Quality improvement efforts require effective methods to identify potential safety issues.

Purpose of the Study:

• To explore disproportionality analysis as a novel method for medication error data.
• To identify medication error relationships not obvious through traditional analyses.
• To supplement descriptive data and target quality improvement efforts.

Main Methods:

• Utilized data from the Medication Error Quality Initiative (MEQI) individual event reporting system.
• Applied disproportionality analysis to data from 206 North Carolina nursing homes (2006-2007).
• Explored associations between medication types and causes at state and facility levels.

Main Results:

• Identified 59 drug-cause pairs meeting disproportionality signals statewide.
• Warfarin linked to communication errors; esomeprazole, risperidone, nitrofurantoin to transcription errors.
• Oxycodone and morphine disproportionately associated with name confusion errors.

Conclusions:

• Exploratory analysis tools, like disproportionality analysis, can identify disproportionate medication error rates.
• Candidate associations identified can guide patient safety initiatives.
• Further evaluation is needed to confirm the value of these findings for patient safety work.