Cross-sectional evaluation of a clinical decision support tool to identify medication-related problems at discharge from the acute care setting

BackgroundThere are many reported pharmacist-led transitions of care (TOC) programs to address medication-related problems (MRP) at discharge from the acute care setting. Most have identified time and labor resources as significant limitations. This study aims to assess the effectiveness of a medication risk score (MRS)-driven clinical decision support system (CDSS) in identifying actionable MRPs and improving medication safety in the acute care discharge TOC setting.MethodsA cross-sectional analysis was conducted in a cohort of 481 subjects discharged from the acute care setting. The MRS-CDSS was utilized to identify MRPs and provide recommendations for risk reduction. The distribution of MRPs, recommendations, and their associations with MRS severity were analyzed. Additionally, the potential reduction in MRS per subject and its correlation with MRS severity were examined.ResultsThe median MRS reduction per subject was 2 points, while high/severe-risk patients showed a median potential reduction of 7 points. Among the identified MRPs (n = 691), drug interaction, drug use without indication, and adverse drug reaction accounted for 89.7% of all MRPs. The top three recommendations, discontinue medication, change the time of administration, and start alternative therapy, represented 94.1% of all recommendations. Stratified analysis by MRS category revealed a significant increase in adverse drug reaction MRPs and recommendations to discontinue medications with higher MRS severity. The results were consistent with previous outpatient studies, supporting the MRS-CDSS's ability to enhance medication safety.ConclusionThis study demonstrates that the MRS-CDSS effectively identifies actionable MRPs and has the potential to substantially reduce overall pharmacotherapy regimen risk when applied during acute care discharge TOC. The findings support implementable recommendations directed at patient safety and the allocation of health care resources to high-risk patients for maximum benefit.