Automating the medication regimen complexity index

  • McDonald M
  • Peng T
  • Sridharan S
 et al. 
  • 76


    Mendeley users who have this article in their library.
  • 26


    Citations of this article.


OBJECTIVE: To adapt and automate the medication regimen complexity index (MRCI) within the structure of a commercial medication database in the post-acute home care setting. MATERIALS AND METHODS: In phase 1, medication data from 89 645 electronic health records were abstracted to line up with the components of the MRCI: dosage form, dosing frequency, and additional administrative directions. A committee reviewed output to assign index weights and determine necessary adaptations. In phase 2 we examined the face validity of the modified MRCI through analysis of automatic tabulations and descriptive statistics. RESULTS: The mean number of medications per patient record was 7.6 (SD 3.8); mean MRCI score was 16.1 (SD 9.0). The number of medications and MRCI were highly associated, but there was a wide range of MRCI scores for each number of medications. Most patients (55%) were taking only oral medications in tablet/capsule form, although 16% had regimens with three or more medications with different routes/forms. The biggest contributor to the MRCI score was dosing frequency (mean 11.9). Over 36% of patients needed to remember two or more special instructions (eg, take on alternate days, dissolve). DISCUSSION: Medication complexity can be tabulated through an automated process with some adaptation for local organizational systems. The MRCI provides a more nuanced way of measuring and assessing complexity than a simple medication count. CONCLUSIONS: An automated MRCI may help to identify patients who are at higher risk of adverse events, and could potentially be used in research and clinical decision support to improve medication management and patient outcomes.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Margaret V. McDonald

  • Timothy R. Peng

  • Sridevi Sridharan

  • Janice B. Foust

  • Polina Kogan

  • Liliana E. Pezzin

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free