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RATIONALE & OBJECTIVE: Digital health system tools to support shared decision making and preparation for kidney replacement treatments for patients with chronic kidney disease (CKD) are needed. STUDY DESIGN: Descriptive study of the implementation of digital infrastructure to support a patient-centered health system intervention. SETTING & PARTICIPANTS: 4 CKD clinics within a large integrated health system. EXPOSURE: We developed an integrated suite of digital engagement tools to support patients' shared decision making and preparation for kidney failure treatments. Tools included an automated CKD patient registry and risk prediction algorithm within the electronic health record (EHR) to identify and prioritize patients in need of nurse case management to facilitate shared decision making and preparation for kidney replacement treatments, an electronic patient-facing values clarification tool, a tracking application to document patients' preparation for treatments, and an EHR work flow to broadcast patients' treatment preferences to all health care providers. OUTCOMES: Uptake and acceptability. ANALYTIC APPROACH: Mixed methods. RESULTS: From July 1, 2017, through June 30, 2018, the CKD registry identified 1,032 patients in 4 nephrology clinics, of whom 243 (24%) were identified as high risk for progressing to kidney failure within 2 years. Kidney Transitions Specialists enrolled 117 (48%) high-risk patients by the end of year 1. The values tool was completed by 30/33 (91%) patients who attended kidney modality education. Nurse case managers used the tracking application for 100% of patients to document 287 planning steps for kidney replacement therapy. Most (87%) high-risk patients had their preferred kidney replacement modality documented and displayed in the EHR. Nurse case managers reported that the tools facilitated their identification of patients needing support and their navigation activities. LIMITATIONS: Single institution, short duration. CONCLUSIONS: Digital health system tools facilitated rapid identification of patients needing shared and informed decision making and their preparation for kidney replacement treatments. FUNDING: This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) Project Program Award (IHS-1409-20967). TRIAL REGISTRATION: ClinicalTrials.gov NCT02722382.
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PURPOSE: Precise estimation of creatinine clearance in obese individuals relies on the appropriate assessment of lean body weight (LBW). Anthropometric methods of predicting LBW have not been validated in morbidly obese populations. PATIENTS AND METHODS: Using an existing dataset of anthropometric data for a female cohort with morbid obesity who had undergone measured FFW with dual energy absorptiometry, we evaluated the performance of five previously reported estimating equations for the prediction of LBW. Linear regression was used to derive a new LBW prediction formula and was then compared with the other formulae. RESULTS: Seventy females (mean [standard deviation] age, weight, and body mass index 43.0 [11.0] years, 128.1 [13.8] kg, and 48.3 [4.8] kg/m(2), respectively) were identified. LBW as estimated by the method of Garrow and Webster correlated well (r = 0.87) with measured mass while demonstrating the highest accuracy, best precision, and smallest bias (93%, 2.1 kg, and 2.9 kg, respectively; P < 0.0001 for all comparisons). The derived formula further improved bias, precision, and accuracy. CONCLUSION: Among females with morbid obesity, most previously reported estimating equations for LBW predicted FFW poorly. These findings have important clinical implications for the assessment of kidney function and for safe and effective drug dosing.