# (MEnD-AKI) Multicenter Implementation of an Electronic Decision Support System for Drug-associated AKI

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2022 · $630,467

## Abstract

Abstract
Acute Kidney Injury (AKI) in the US has increased by 38% over the last eight years, with drugs as a major
contributor to AKI in hospitalized patients. Drug-associated AKI (D-AKI) results in severe consequences with
approximately 40% of patients experiencing in-hospital death or dialysis dependence and 70% having
evidence of residual kidney damage following the initial D-AKI event. We have determined that many patients
at high risk for AKI are identified late and often continue to receive nephrotoxic drugs until AKI becomes
severe. Thus, we designed a proposal to address the need for early, appropriate management of nephrotoxins
in high-risk patients by studying the effect of an advanced clinical decision support system (CDSS) for primary
physicians and hospitalists aimed at reducing D-AKI in hospitalized adults. Specifically, we aim to 1) optimize
the clinical performance of D-AKI risk-alerts generated by a clinical decision support system; 2) test whether an
advanced clinical decision support system coupled with a pharmacist-led intervention improves short and long-
term outcomes for patients with D-AKI; and 3) determine physician perception of the pharmacists’
performance, physician acceptance and cost-effectiveness of our intervention.
In 2012 Kidney Disease Improving Global Outcomes (KDIGO) published the first comprehensive AKI clinical
practice guideline. Recommendations include the use of standard criteria for defining and staging AKI and a
series of stage-based management steps to be considered for all patients with AKI or at risk for developing it.
However, clinicians have been slow to adopt these recommendations and some groups (most notably the US
KDOQI expert panel), while endorsing the guideline overall, have called for more research testing the
recommendations. Our proposal directly addresses this concern by testing whether a unique clinical decision
support system identifying high risk patients coupled with an advanced pharmacist service directed to the
primary physician can address D-AKI and drug dosing for other forms of AKI to improve patient care. Thus, our
central goal is to examine the effect of a pharmacist-led intervention on the early detection and management of
AKI, progression of and short-term recovery from AKI, and on various AKI-related outcomes.

## Key facts

- **NIH application ID:** 10414976
- **Project number:** 5R01DK121730-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Azra Bihorac
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $630,467
- **Award type:** 5
- **Project period:** 2021-06-01 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10414976

## Citation

> US National Institutes of Health, RePORTER application 10414976, (MEnD-AKI) Multicenter Implementation of an Electronic Decision Support System for Drug-associated AKI (5R01DK121730-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10414976. Licensed CC0.

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