Automating the medication regimen complexity index. J Am Med Inform Assoc 2013 May 01;20(3):499-505
Date
12/27/2012Pubmed ID
23268486Pubmed Central ID
PMC3628060DOI
10.1136/amiajnl-2012-001272Scopus ID
2-s2.0-84879929473 (requires institutional sign-in at Scopus site) 65 CitationsAbstract
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.
Author List
McDonald MV, Peng TR, Sridharan S, Foust JB, Kogan P, Pezzin LE, Feldman PHAuthor
Liliana Pezzin PhD, JD Professor in the Institute for Health and Equity department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Drug Administration ScheduleElectronic Health Records
Home Care Services
Humans
Medication Adherence
Polypharmacy
Self Administration
