# Scalable Clinical Decision Support for Individualized Cancer Risk Management

> **NIH NIH U24** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $745,481

## Abstract

Project Summary / Abstract
We propose to enable a scalable clinical decision support (CDS) platform that helps clinicians and patients
select cancer screening strategies that are best suited to each individual. This kind of CDS is important
because increased evidence supports personalizing cancer screening decisions according to each individual's
unique cancer risks. While a highly desired goal, individualizing screening at a population scale requires the
implementation of patient-specific risk assessments for several types of cancer. This is quite challenging in
today's overwhelmed primary care environment. Our proposed CDS platform addresses this challenge by (i)
automating the risk stratification process at the population level based on EHR data and patient reported data;
(ii) prioritizing patients for case review by genetic counselors; and (iii) automatically communicating risk and
screening recommendations with primary care providers and their patients.
We will integrate the CDS platform with the Epic EHR and test it at the University of Utah Health Care
community clinics and the Huntsman Cancer Institute. We will assess the generalizability of the CDS platform
with a different EHR (Cerner) at a different institution (Intermountain Healthcare). To maximize the
dissemination potential for the proposed cancer risk screening platform, we will extend two well-established
open source CDS platforms: OpenCDS and OpenInfobutton. These platforms are reference implementations
of international EHR standards that are required for EHR certification in the US. We will also obtain software
certification from the Open Source EHR Alliance, share the CDS platform and our experiences with other
awardees in the ITCR Program, present the CDS platform at national and international cancer and informatics
conferences; and engage with relevant stakeholders through a technical expert panel.
Any healthcare organization with a certified EHR will be able to use the proposed CDS platform. Therefore, if
successful, this proposal can have a significant impact on disseminating individualized cancer screening
practices according to the best available evidence.

## Key facts

- **NIH application ID:** 9979779
- **Project number:** 5U24CA204800-04
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** GUILHERME DEL FIOL
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $745,481
- **Award type:** 5
- **Project period:** 2017-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9979779

## Citation

> US National Institutes of Health, RePORTER application 9979779, Scalable Clinical Decision Support for Individualized Cancer Risk Management (5U24CA204800-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9979779. Licensed CC0.

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