Development and Validation of Nine Deprescribing Algorithms for Patients on Hemodialysis to Decrease Polypharmacy. (October 2020) - Lefebvre, Melissa J.; Ng, Patrick C. K.; Desjarlais, Arlene; McCann, Dennis; Waldvogel, Blair; Tonelli, Marcello; Garg, Amit X.; Wilson, Jo-Anne; Beaulieu, Monica; Marin, Judith; Orsulak, Cali; Lloyd, Anita; et al.
Background: Polypharmacy is ubiquitous in patients on hemodialysis (HD), and increases risk of adverse events, medication interactions, nonadherence, and mortality. Appropriately applied deprescribing can potentially minimize polypharmacy risks. Existing guidelines are unsuitable for nephrology clinicians as they lack specific instructions on how to deprescribe and which safety parameters to monitor. Objective: To develop and validate deprescribing algorithms for nine medication classes to decrease polypharmacy in patients on HD. Design: Questionnaires and materials sent electronically. Participants: Nephrology practitioners across Canada (nephrologists, nurse practitioners, renal pharmacists). Methods: A literature search was performed to develop the initial algorithms via Lynn's method for development of content-valid clinical tools. Content and face validity of the algorithms was evaluated over three interview rounds using Lynn's method for determining content validity. Canadian nephrology clinicians each evaluated three algorithms (15 clinicians per round, 45 clinicians in total) by rating each algorithm component on a four-point Likert scale for relevance; face validity was rated on a five-point scale. After each round, content validity index of each component was calculated and revisions made based on feedback. If content validity was not achieved after three rounds, additional rounds were completed until content validity was achieved. Results: After three rounds of validation, six algorithms achieved content validity. After an additional round, the remaining three algorithms achieved content validity. The proportion of clinicians rating each face validity statement as "Agree" or "Strongly Agree" ranged from 84% to 95% (average of all five questions, across three rounds). Limitations: Algorithm development was guided by existing deprescribing protocols intended for the general population and the expert opinions of our study team, due to a lack of background literature on HD-specific deprescribing protocols. There is no universally accepted method for the validation of clinical decision-making tools. Conclusions: Nine medication-specific deprescribing algorithms for patients on HD were developed and validated by clinician review. Our algorithms are the first medication-specific, patient-centric deprescribing guidelines developed and validated for patients on HD.