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Grant Details

Grant Number: 5R01CA183962-05 Interpret this number
Primary Investigator: Hernandez-Boussard, Tina
Organization: Stanford University
Project Title: Utilizing Electronic Health Records to Measure and Improve Prostate Cancer Care
Fiscal Year: 2019
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Abstract

 DESCRIPTION (provided by applicant): Prostate cancer is the most common malignancy in men. Newly diagnosed men face complex treatment choices, each with different risks of acquired patient-centered outcomes (e.g. urinary and erectile dysfunction). Currently, patients and clinicians cannot easily compare the trade-offs among patient-centered outcomes across different treatments because the empirical evidence regarding these trade-offs does not exist, because patient centered outcomes are not routinely recorded in assessable formats. However, electronic healthcare records (EHR) free text is a rich, untapped source of patient centered outcomes. We propose to assemble a robust data-mining workflow to efficiently and accurately capture treatment and outcome quality metrics from structured data and free-text in EHRs. We will put this evidence in the hands of both clinicians and patients through a web-based risk assessment tool. Our proposal has three innovative aspects. First, we will develop an EHR prostate cancer database that will allow for clinical care data to be analyzed alongside diagnostic details. Second, we will create novel ontological representations of quality metrics that will be public and reliably calculable across EHR-systems. Third, we will assemble a robust data- mining workflow that expands on existing methods by focusing on ontology-based dictionaries to annotate free text. Combining this set of innovative components will uniquely allow us to use existing EHRs to efficiently study the trade-offs among patient-centered outcomes across different treatments. In Aim 1 we will create the building blocks needed to identify quality metric data in EHRs. We will develop an EHR-database, map quality metrics to medical vocabularies and ontologies, and create electronic quality metric phenotypes. In Aim 2, we will expand our data-mining workflow with quality metric vocabulary and use it to gather data relevant to quality metrics. In Aim 3 we will develop a web-based tool that integrates the empirical evidence assessed in our first two aims with patient and clinical characteristics to estimate patients' personalized risks of patient centered outcomes across treatments. Our web tool will display such personalized risk predictions, to help clinicians and patients choose a treatment option that offers the best predicted quality of life given the importance they assign to each patient-centered outcome. This proposal will address a critical gap in evidence for prostate cancer treatment and research by providing clinicians and patients with empirical evidence needed to compare the trade-offs among patient centered outcomes across different treatments. Our work is consistent with our nation's focus on EHR `meaningful use' and the comprehensive assessment of healthcare delivery, and with NCI's focus on improving the quality of cancer care delivery.

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Publications

Machine Learning Approaches for Extracting Stage from Pathology Reports in Prostate Cancer.
Authors: Lenain R. , Seneviratne M.G. , Bozkurt S. , Blayney D.W. , Brooks J.D. , Hernandez-Boussard T. .
Source: Studies in health technology and informatics, 2019-08-21; 264, p. 1522-1523.
PMID: 31438212
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Extracting Patient-Centered Outcomes from Clinical Notes in Electronic Health Records: Assessment of Urinary Incontinence After Radical Prostatectomy.
Authors: Gori D. , Banerjee I. , Chung B.I. , Ferrari M. , Rucci P. , Blayney D.W. , Brooks J.D. , Hernandez-Boussard T. .
Source: EGEMS (Washington, DC), 2019-08-20; 7(1), p. 43.
EPub date: 2019-08-20.
PMID: 31497615
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Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study.
Authors: Bozkurt S. , Kan K.M. , Ferrari M.K. , Rubin D.L. , Blayney D.W. , Hernandez-Boussard T. , Brooks J.D. .
Source: BMJ open, 2019-07-18; 9(7), p. e027182.
EPub date: 2019-07-18.
PMID: 31324681
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PSA Testing Use and Prostate Cancer Diagnostic Stage After the 2012 U.S. Preventive Services Task Force Guideline Changes.
Authors: Magnani C.J. , Li K. , Seto T. , McDonald K.M. , Blayney D.W. , Brooks J.D. , Hernandez-Boussard T. .
Source: Journal of the National Comprehensive Cancer Network : JNCCN, 2019-07-01; 17(7), p. 795-803.
PMID: 31319390
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Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models.
Authors: Banda J.M. , Seneviratne M. , Hernandez-Boussard T. , Shah N.H. .
Source: Annual review of biomedical data science, 2018 Jul; 1, p. 53-68.
EPub date: 2018-05-23.
PMID: 31218278
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Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment.
Authors: Banerjee I. , Li K. , Seneviratne M. , Ferrari M. , Seto T. , Brooks J.D. , Rubin D.L. , Hernandez-Boussard T. .
Source: JAMIA open, 2019 04; 2(1), p. 150-159.
EPub date: 2019-01-04.
PMID: 31032481
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Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients.
Authors: Coquet J. , Bozkurt S. , Kan K.M. , Ferrari M.K. , Blayney D.W. , Brooks J.D. , Hernandez-Boussard T. .
Source: Journal of biomedical informatics, 2019 Jun; 94, p. 103184.
EPub date: 2019-04-20.
PMID: 31014980
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Distribution of global health measures from routinely collected PROMIS surveys in patients with breast cancer or prostate cancer.
Authors: Seneviratne M.G. , Bozkurt S. , Patel M.I. , Seto T. , Brooks J.D. , Blayney D.W. , Kurian A.W. , Hernandez-Boussard T. .
Source: Cancer, 2019-03-15; 125(6), p. 943-951.
EPub date: 2018-12-04.
PMID: 30512191
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Utilization of Prostate Cancer Quality Metrics for Research and Quality Improvement: A Structured Review.
Authors: Gori D. , Dulal R. , Blayney D.W. , Brooks J.D. , Fantini M.P. , McDonald K.M. , Hernandez-Boussard T. .
Source: Joint Commission journal on quality and patient safety, 2019 Mar; 45(3), p. 217-226.
EPub date: 2018-09-18.
PMID: 30236510
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Merging heterogeneous clinical data to enable knowledge discovery.
Authors: Seneviratne M.G. , Kahn M.G. , Hernandez-Boussard T. .
Source: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2019; 24, p. 439-443.
PMID: 30864344
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Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer.
Authors: Seneviratne M.G. , Seto T. , Blayney D.W. , Brooks J.D. , Hernandez-Boussard T. .
Source: EGEMS (Washington, DC), 2018-06-01; 6(1), p. 13.
EPub date: 2018-06-01.
PMID: 30094285
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Secondary use of electronic medical records for clinical research: Challenges and Opportunities.
Authors: Yim W.W. , Wheeler A.J. , Curtin C. , Wagner T.H. , Hernandez-Boussard T. .
Source: Convergent science physical oncology, 2018 Mar; 4(1), .
EPub date: 2018-02-12.
PMID: 29732166
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Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.
Authors: Seneviratne M.G. , Banda J.M. , Brooks J.D. , Shah N.H. , Hernandez-Boussard T.M. .
Source: AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018; 2018, p. 1498-1504.
EPub date: 2018-12-05.
PMID: 30815195
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An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.
Authors: Bozkurt S. , Park J.I. , Kan K.M. , Ferrari M. , Rubin D.L. , Brooks J.D. , Hernandez-Boussard T. .
Source: AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018; 2018, p. 288-294.
EPub date: 2018-12-05.
PMID: 30815067
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Mining Electronic Health Records to Extract Patient-Centered Outcomes Following Prostate Cancer Treatment.
Authors: Hernandez-Boussard T. , Kourdis P.D. , Seto T. , Ferrari M. , Blayney D.W. , Rubin D. , Brooks J.D. .
Source: AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017; 2017, p. 876-882.
EPub date: 2018-04-16.
PMID: 29854154
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Electronic Health Records and Quality of Care: An Observational Study Modeling Impact on Mortality, Readmissions, and Complications.
Authors: Yanamadala S. , Morrison D. , Curtin C. , McDonald K. , Hernandez-Boussard T. .
Source: Medicine, 2016 May; 95(19), p. e3332.
PMID: 27175631
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New Paradigms for Patient-Centered Outcomes Research in Electronic Medical Records: An Example of Detecting Urinary Incontinence Following Prostatectomy.
Authors: Hernandez-Boussard T. , Tamang S. , Blayney D. , Brooks J. , Shah N. .
Source: EGEMS (Washington, DC), 2016; 4(3), p. 1231.
EPub date: 2016-05-12.
PMID: 27347492
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