The development and validation of coded scripts to assess drug related problems due to anticholinergic burden and medication complexity in large study databases

Abstract

The drug burden index (DBI) and medication regimen complexity index (MRCI) are validated tools which identify patients who may experience drug related problems (DRPs) due to anticholinerg and/or sedative burden and medication complexity, respectively. We set out to create two coded scripts in order to identify these patients in large study databases.

We translated the established algorithms for DBI and MRCI into an R script. The scripts were developed in a large trial database of elderly patients with polypharmacy, and subsequently the performance was validated in this database. DBI and MRCI scores for these patients were calculated by our scripts, and the resulting scores were thereafter compared to manual calculations in stratified samples. Validation was expressed as the proportion of identical score pairs. We assessed four scenarios for imputing the daily frequency of as needed medication for the DBI coded script. Additionally, the MRCI coded script was validated by comparing the ranking of six varying test regimens according to the coded script with the ranking according to the original published MRCI tool.

Both DBI and MRCI coded scripts showed a high proportion of identical score pairs (91.5% and 88.1% for two scenarios of the DBI calculation, and 94% for the MRCI coding). The mean difference between all selected score pairs were minimal. Excluding as needed medication from the DBI computations, led to underestimation of the total anticholinergic burden. Our MRCI coded script showed an identical ranking of the six test regimens.

In conclusion, we have achieved two validated coded scripts to calculate the DBI and the MRCI in large study databases, allowing us to identify patients who may experience DRPs due to anticholinerg burden and medication complexity in large study databases. The actual use of as needed medication is usually not recorded. We propose to impute as needed medication with a median value to avoid underestimation of the DBI score.