Abstract

IntroductionCreatinine‐based equations used to estimate renal function are inaccurate in certain clinical contexts; however, there are limited resources to guide pharmacists in these situations.ObjectivesTo assess current renal function estimation and subsequent drug dosing practices among American College of Clinical Pharmacy (ACCP) members via an electronic survey.MethodsA 21‐item survey was emailed to the listservs of four ACCP Practice‐Research Networks: Adult Medicine, Nephrology, Critical Care, and Infectious Diseases. The survey included pharmacist demographics, practice site information, and case‐based clinical application scenarios requiring the respondent to choose a renal function estimate for overweight, underweight, and elderly patients (≥65 years). Four patient cases captured respondents' enoxaparin dosing decisions in patients with an estimated creatinine clearance of around 30 mL/min. Estimates of renal function were provided based on Cockcroft‐Gault (C‐G), Modification of Diet in Renal Disease, and Chronic Kidney Disease Epidemiology equations.ResultsThere were 299 survey responses. The majority of respondents were pharmacists (98%) who practiced in the hospital setting (96%) as clinical specialists (69%). The C‐G equation was chosen to estimate renal function most commonly (85%). Total and adjusted body weights were used in C‐G estimates most commonly in patients who were underweight (80%) and overweight (75%), respectively. Given an elderly patient with low serum creatinine (Scr), 34% of respondents used actual Scr, 30% rounded Scr to 0.8, and 29% rounded Scr to 1.0 for use in C‐G. Enoxaparin renal dose adjustment differed based on clinical indication. Respondents chose more frequent (every 12 hour) dosing in patients with pulmonary embolism vs atrial fibrillation. Of the 79% of respondents whose practice site utilizes pharmacist‐driven renal dose adjustment policies, 94% indicated they deviated from the policy.ConclusionLarge variation exists among clinical pharmacists in the application of renal function estimating equations which may impact dosing strategies and patient care.

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