An Automated Strategy to Calculate Medication Regimen Complexity

Yuzhi Lu, Ariel R. Green, Rosalphie Quiles, Casey Overby Taylor

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding medication regimen complexity is important to understand what patients may benefit from pharmacist interventions. Medication Regimen Complexity Index (MRCI), a 65-item tool to quantify the complexity by incorporating the count, dosage form, frequency, and additional administration instructions of prescription medicines, provides a more nuanced way of assessing complexity. The goal of this study was to construct and validate a computational strategy to automate the calculation of MRCI. The performance of our strategy was evaluated by comparing our calculated MRCI values with gold-standard values, using correlation coefficients and population distributions. The results revealed satisfactory performance to calculate the sub-score of MRCI that includes dosage form and frequency (76 to 80% match with gold standard), and fair performance for sub-score related to additional direction (52% match with gold standard). Our automated strategy shows potential to help reduce the effort for manually calculating MRCI and highlights areas for future development efforts.

Original languageEnglish (US)
Pages (from-to)1077-1086
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2023
StatePublished - 2023
Externally publishedYes

ASJC Scopus subject areas

  • General Medicine

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