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Scalable Clinical Decision Support for Individualized Cancer Risk Management

个性化癌症风险管理的可扩展临床决策支持

基本信息

批准号：
10215413
负责人：
GUILHERME DEL FIOL
金额：
$ 74.92万
依托单位：
UNIVERSITY OF UTAH
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2022-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10215413
关键词：
Address Adoption Algorithms Architecture Breast Cancer Detection Breast Cancer Risk Factor Certification Colorectal Cancer Computer software Coupled Data Data Reporting Detection Documentation Ecosystem Electronic Health Record Environment Family Goals Guidelines Healthcare Healthcare Systems Incentives Individual Informatics Information Retrieval Infrastructure Institutes Institution International Intervention Logic Malignant Neoplasms Modality National Comprehensive Cancer Network Natural Language Processing pipeline Patient Care Patients Population Primary Health Care Process Provider PubMed Recording of previous events Research Risk Risk Assessment Risk Management Scanning Screening for cancer System Technology Testing Universities Utah base cancer risk cancer type care providers clinical decision support colorectal cancer risk community clinic design experience genetic counselor health care service organization healthcare community high risk improved incentive program malignant breast neoplasm online course online resource open source patient population personalized screening primary care setting programs risk stratification screening screening guidelines support tools symposium web services

项目摘要

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.

项目摘要/摘要