Development and validation of deprescribing algorithms for kidney failure using consensus development methodology

Patients with kidney failure (KF) are at high risk of inappropriate polypharmacy; however, this can be mitigated through deprescribing. While several evidence-based deprescribing guidelines exist for various patient populations, their applicability and utility in KF settings remain limited.

This study aimed to adapt existing evidence on deprescribing in KF to develop practical deprescribing algorithms that support clinicians in implementing deprescribing interventions in KF care.

Available evidence about deprescribing in KF was reviewed, and local prescribing trends among KF patients were explored. Second, a panel of five experts in pharmacotherapy, medication safety, and clinical research was convened and conducted consensus development workshops to appraise the evidence and develop comprehensive deprescribing algorithms for patients with KF. The adapted algorithms were reviewed by nephrology consultants (n = 3) and clinical pharmacists (n = 2) for clinical validation. The validated algorithms were also applied in a pilot deprescribing study to assess their feasibility and utility in this setting.

One general and 18 drug class-specific evidence-based deprescribing algorithms in KF care were developed. These provide a structured, stepwise approach to assessing medication appropriateness and guiding deprescribing decisions. Expert validation resulted in refinements of the algorithms. In the pilot testing among hemodialysis (HD) and low clearance clinics, the generic deprescribing algorithm was applied in all cases. The drug-class-specific algorithms were used in 41 deprescribing plans (55.4%) in the HD and in 5 (45.5%) in the low-clearance clinic settings.

We developed and validated a set of evidence-based deprescribing algorithms tailored to patients with KF, offering a practical and structured approach to support clinicians in deprescribing potentially inappropriate medications.