Implementation of targeted deprescribing of potentially inappropriate medications in patients on hemodialysis.

PURPOSE: Patients on hemodialysis have a high risk of medication-related problems. Studies using deprescribing algorithms to reduce the number of inappropriate medications in this population have been published, but none have used a patient-partnership approach. Our study evaluated the impact of a similar intervention with a patient-partnership approach.

METHODS

The objective was to describe the implementation of a pharmacist-led intervention with a patient-partnership approach using deprescribing algorithms and its impact on the reduction of inappropriate medications in patients on hemodialysis. Eight algorithms were developed by pharmacists and nephrologists to assess the appropriateness of medications. Pharmacists identified patients taking targeted medications. Following patient enrollment, pharmacists assessed medications with patients and applied the algorithms. With patient consent, deprescription was suggested to nephrologists if applicable. Specific data on each targeted medication were collected at 4 and 16 weeks. Descriptive statistics were used to examine the effects of the deprescribing intervention.

RESULTS

Of 270 patients, 256 were taking at least one targeted medication. Of the 122 patients taking at least one targeted medication who were approached to participate, 66 were included in the study. At enrollment, these patients were taking 252 targeted medications, of which 59 (23.4%) were determined to be inappropriate. Deprescription was initiated for 35 of these 59 medications (59.3%). At 4 weeks, 33 of the 59 medications (55.9%) were still deprescribed, while, at 16 weeks, 27 of the 59 medications (45.8%) were still deprescribed. Proton pump inhibitors and benzodiazepines or Z-drugs were the most common inappropriate medications, and allopurinol was the most deprescribed medication.

CONCLUSION

A pharmacist-led intervention with a patient-partnership approach and using deprescribing algorithms reduced the number of inappropriate medications in patients on hemodialysis.