# Targeted Automated Nephrology e-Consultation for Diabetic Kidney Disease > **NIH NIH K23** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $85,737 ## Abstract ABSTRACT Diabetic kidney disease (DKD) is an enormous and growing public health problem that is associated with significant cardiovascular morbidity/mortality and kidney failure, in addition to posing a significant economic burden for the US health system. Patients with DKD experience significant gaps in the delivery of guideline- recommended treatments for reducing the risk of cardiovascular disease and kidney failure. Previously studied interventions intended to address these gaps have relied on overburdened primary care teams and have shown only modest success. The overall goal of the proposed research is to design and pilot an intervention of proactive nephrology e-consultation which leverages the electronic health record to identify patients with DKD who might benefit from nephrology expertise, but whose kidney disease is not severe enough to require in- person nephrology referral. As part of this intervention, nephrologists would perform targeted, automated consultations (TACos) for eligible patients by reviewing patient charts and providing individualized recommendations focused on delivering guideline-indicated DKD care. For health systems with limited subspecialist capacity for in-person visits, TACos offer a “high-touch” approach to extending subspecialty expertise in collaboration with primary care to reach a broader population. For DKD, TACos have the potential to promote both utilization of established DKD therapies and uptake of novel therapies, such as sodium- glucose cotransporter 2 inhibitors. The specific aims of this project are 1) to conduct semi-structured interviews of primary care clinicians and nephrologists to understand the most helpful elements of a TACo intervention; 2) to use a microsimulation modeling approach to determine the best strategies for targeting TACos for optimizing impact and equity based on existing practice patterns in a local setting; and 3) to evaluate the feasibility and acceptability of a pilot implementation of TACos in one public health care delivery system. To accomplish the goals and to prepare Dr. Chu for an independent research career as an implementation scientist focused on improving chronic kidney disease care, he will be mentored by a team of experts in qualitative research methods, kidney disease epidemiology, simulation modeling, and implementation science. Specifically, this proposal will allow the Dr. Chu to achieve the following training goals: 1) undertake formal didactic and mentored training in implementation science; 2) develop skills to design and conduct qualitative research studies to inform intervention design; 3) learn to apply simulation modeling approaches to predict potential impact of interventions; and 4) gain experience conducting a pilot study that implements and evaluates a care delivery intervention. Completion of these aims will generate the preliminary data and provide a training foundation to support an R-level proposal to study the effectiveness of TACos or other... ## Key facts - **NIH application ID:** 10814226 - **Project number:** 5K23DK131316-02 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO - **Principal Investigator:** Chi Chu - **Activity code:** K23 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $85,737 - **Award type:** 5 - **Project period:** 2023-03-23 → 2024-06-07 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10814226 ## Citation > US National Institutes of Health, RePORTER application 10814226, Targeted Automated Nephrology e-Consultation for Diabetic Kidney Disease (5K23DK131316-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10814226. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*