Reuse of Electronic Medical Records for Research Our architecture Two examples.

Slides:

Advertisements

Similar presentations

Consolidated User Story 1: Chronic Diseases (cancer, occupational health) Chronic Diseases, Outpatient Flow Patient, Provider/Physician, Laboratory, PH.

Advertisements

Taking Research and Development to the Clinic: Issues for Physicians AAAS/FDLI Colloquium I Diagnostics and Diagnoses Paths to Personalized Medicine Howard.

Lecture 2 Strachan and Read Chapter 13

Genetic Analysis of Genome-wide Variation in Human Gene Expression Morley M. et al. Nature 2004,430: Yen-Yi Ho.

Comparability of Electronic and Manual Influenza-like Illness (ILI) Surveillance Methods Robin M. Williams, Nebraska Department of Health & Human Services/University.

1 February 9, 2007 Indigent Care Collaboration HIE Supports Community Collaboration February 9, 2007 Ann Kitchen  Executive Director Indigent Care Collaboration.

Genetic Analysis in Human Disease

Mining Electronic Health Records

AMIA CRI Summit 2011 CRI-09: Cross-Institutional Systems to Support Phenotyping in Biomedical Research: Experiences from the eMERGE Network Luke Rasmussen.

Area 4 SHARP Face-to-Face Conference Phenotyping Team – Centerphase Project Assessing the Value of Phenotyping Algorithms June 30, 2011.

Preceptor: Louise A. Mawn, M.D. May 30, Medical Documentation Medical record serves many functions For health care providers it facilitates: Communication.

Electronic Medical Records as a Tool in Clinical Pharmacology: Opportunities and Challenges 報告人：蘇為碩宋柏融李曉婷陳凱普洪詩涵 2014/05/19.

Widespread adoption of the electronic medical record (EMR), though expensive and logistically challenging, can potentially establish new frontiers in personalized.

Overview of Biomedical Informatics Rakesh Nagarajan.

Vanderbilt’s DNA Databank:

University of Pittsburgh Department of Biomedical Informatics Healthcare institutions have established local clinical data research repositories to enable.

Biology and Bioinformatics Gabor T. Marth Department of Biology, Boston College BI820 – Seminar in Quantitative and Computational Problems.

Data collection, integration and normalization presented to DIMACS Gil Delgado October 17, 2002.

Positional Cloning LOD Sib pairs Chromosome Region Association Study Genetics Genomics Physical Mapping/ Sequencing Candidate Gene Selection/ Polymorphism.

Identifying RA patients from the electronic medical records at Partners HealthCare Robert Plenge, M.D., Ph.D. VA Hospital July 20, 2010 HARVARD MEDICAL.

Overview of the Synthetic Derivative April 16, 2010 Melissa Basford, MBA Program Manager – Synthetic Derivative.

NEW ENHANCEMENTS IN THE SYNTHETIC DERIVATIVE AND WHAT THAT MEANS FOR THE RESEARCHER Jacqueline Kirby June 7 th, 2013.

Opportunities for Big Data in Medical Records Mike Conlon, PhD

Vanderbilt’s DNA Databank: BioVU. Personalized Medicine Integration of genomic information into clinical decision making Personalized disease treatment.

Elizabeth Karlson, MD Associate Professor of Medicine

Genetic Analysis in Human Disease. Learning Objectives Describe the differences between a linkage analysis and an association analysis Identify potentially.

Private and Confidential – For Discussion Purposes Only OneWorldDr Medical Services Overview  OneWorldDr Medical Services (OWD) is a Mobile phone and.

BioVU and the Synthetic Derivative Erica Bowton, PhD Program Manager, Personalized Medicine.

Epigenome 1. 2 Background: GWAS Genome-Wide Association Studies 3.

Butte Lab Journal Club 16 Aug 2010 Alexander A. Morgan.

Strategic Health IT Advanced Research Projects (SHARP) Area 4: Secondary Use of EHR Data Project 3: High-Throughput Phenotyping Jyotishman Pathak, PhD.

PGPop: PharmacoGenomic discovery and replication in very large patient POPulations PGPop: SUMMARY PGPop was conceived as a network resource to provide.

Square wheels: electronic medical records for discovery research in rheumatoid arthritis Robert M. Plenge, M.D., Ph.D. October 30, 2009 NCRR sponsored.

Data Analysis Summary. Elephant in the room General Comments General understanding that informatics is integral in medical sequencing and other –omics.

SHARPn High-Throughput Phenotyping (HTP) November 18, 2013.

OVERVIEW OF THE SYNTHETIC DERIVATIVE June 29, 2012 Melissa Basford, MBA Program Manager – Synthetic Derivative.

From Genome-Wide Association Studies to Medicine Florian Schmitzberger - CS 374 – 4/28/2009 Stanford University Biomedical Informatics

EXPLORING DATA AND COHORT DISCOVERY IN THE SYNTHETIC DERIVATIVE.

IndianaCTSI ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH Building an Indiana Biorepository Dave A Flockhart Eric Meslin April 19 th, 2010.

Genetic Repositories Australia BACKGROUND GRA supported by an NHMRC Enabling Facility Grant awarded in  GRA supported by an NHMRC Enabling Facility.

Risk Prediction of Complex Disease David Evans. Genetic Testing and Personalized Medicine Is this possible also in complex diseases? Predictive testing.

Rachel Liao, PhD Coordinator of the Clinical Working Group and the BRCA Challenge demonstration project for the Global Alliance for Genomics and Health.

Leveraging Big Data and Electronic Health Records to Create a Data Fluent Culture for Cancer Medicine Mia Levy, MD, PhD October 8, 2015 Komen Big Data.

Data Quality Sharp project 5 June Statistical Problems with Data Quality in EHR Missing Data Missing Data Uncertain Diagnosis Uncertain Diagnosis.

VICTR Data Management CRC Research Skills Workshop Michael Assink April 6 th, 2012.

Phenotype generation from EMR by tensor factorization SEDI Durham Cohort James Lu M.D. Ph.D. Department of Electrical and Computer Engineering Department.

Memphis, TN Thomas Duarte, Executive Director, MSeHA.

Kathleen Giacomini, Mark J. Ratain, Michiaki Kubo, Naoyuki Kamatani, and Yusuke Nakamura NIH Pharmacogenomics Research Network III & RIKEN Center for Genomic.

Preoperative Hemoglobin A1c and the Occurrence of Atrial Fibrillation Following On-pump Coronary Artery Bypass surgery in Type-2 Diabetic Patients Akbar.

BIOSTATISTICS Lecture 2. The role of Biostatisticians Biostatisticians play essential roles in designing studies, analyzing data and creating methods.

Regulatory Guidance for Genetic Testing. Three Specific Areas Laboratory tests Results of genetic testing – Clinical – Research GenomeWide Association.

Acute Infections and Insulin Requirements In pre-diabetic individuals acute infections may induce a temporary state of diabetes requiring short-term insulin.

Understanding GWAS SNPs Xiaole Shirley Liu Stat 115/215.

Brendan Burke and Kyle Steffen. Important New Tool in Genomic Medicine GWAS is used to estimate disease risk and test SNPs( the most common type of genetic.

Novel data source: people living with health conditions

High-Throughput Machine Learning from EHR Data

SNPs and complex traits: where is the hidden heritability?

Phenotyping youth depression

. Troponin limit of detection plus cardiac risk stratification scores for the exclusion of myocardial infarction and 30-day adverse cardiac events in ED.

19 Medical Coding.

Strategic Health IT Advanced Research Projects (SHARP)

Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility Sudhi G. Upadhyaya, MS, Dennis H. Murphree, PhD,

Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility Sudhi G. Upadhyaya, MS, Dennis H. Murphree, PhD,

The Genetic Architecture of Alopecia Areata

Kipp W. Johnson et al. BTS 2017;2:

Fig. 3 Context-dependent inherited risk and the importance of intermediate phenotypes in clinical research. Context-dependent inherited risk and the importance.

Clinical Research Informatics: From Bedside to Silicon and Back

Discovery From Data Repositories H Craig Mak Nature Biotechnology 29, 46–47 (2011) 2013 /06 /10.

Network-wide Milestones – Plan to Address & Achieve Domains of focus for supplemental funding request. Sites will work with workgroups to generate milestones.

Robust Replication of Genotype-Phenotype Associations across Multiple Diseases in an Electronic Medical Record Marylyn D. Ritchie, Joshua C. Denny, Dana.

Presentation transcript:

Reuse of Electronic Medical Records for Research Our architecture Two examples

Francis Collins, NEJM 9/16/2009 VanderbiltBioVU: A clinical laboratory for genomics and pharmacogenomics

Vanderbilt BioVU: an Opt-Out DNA Biobank Extracting DNA from left over blood samples

De-Identification eligible John Doe One way hash 32ef34a6e88c2… scrubbed Extract DNA 32ef34a6e88c2… John Doe 1.7 million records ~135,000 samples (>14,000 children) Research Identifier EMR

Patient Chart

Sample accrual into BioVU Currently >40 active projects w/ DNA >100 projects using Synthetic Derivative

Platform for EMR-clinical research at VUMC De-identified DNA Discarded blood samples Synthetic Derivative De-identification Clinical Notes WizOrder Orders Clinical Messaging StarChart ICD9, CPT Test Results

The “demonstration project” Are genotype-phenotype relations replicated in BioVU? Genotype “high-value” SNPs in the first 10,000 samples accrued. – 21 established loci (>1 SNP for some) – in 5 diseases with known associations: Atrial fibrillation Crohn’s disease Multiple Sclerosis Rheumatoid arthritis Type II Diabetes Develop “electronic phenotype algorithms” to identify cases and controls

Finding cases accurately Billing codes alone o nly 50-80% accurate Negation terms – “I don’t think this is MS” Context clues: – “FAMILY MEDICAL HISTORY: positive for rheumatoid arthritis.” Others – Note titles: “ Multiple Sclerosis Clinic Note“ True cases Natural Language Processing Billing codes Medications & Labs Genetic association tests

Rheumatoid Arthritis–Case Definition Evolution #Definition# Cases (in first 10k in BioVU) Problem 1ICD9 codes for RA + Medications (only in problem list) 371Found incomplete problem lists 2Same as above but searched notes411Patients billed as RA but actually other conditions, overlap syndromes, juvenile RA 3Above + require “rheumatoid arthritis” and small list of exclusions 358Overlap syndromes with other autoimmune conditions, conditions in which physicians did not agree 4Above + exclusion of other inflammatory arthritides 255PPV = 97%; a few “possible RA” or family history items remained

Finding cases: Rheumatoid Arthritis Definite Cases (algorithm-defined) Possible Cases (require manual review) Controls (algorithm-defined) Excluded (algorithm-defined) 7121 Used for analysis

Validating EMR phenotype algorithms (Using first 10,000 patients in BioVU) DiseaseMethodsDefinite CasesControlsCase PPVControl PPV Atrial fibrillationNLP of ECG impressions ICD9 codes CPT codes %100% Crohn’s DiseaseICD9 codes Medications (NLP) % Type 2 DiabetesICD9 codes Medications (NLP) NLP exclusions Labs % Multiple SclerosisICD9 codes or text diagnosis %100% Rheumatoid Arthritis ICD9 codes Medications (NLP) NLP exclusions %100% NLP = Natural language processing Common themes: Billing codes – 5/5 NLP – 5/5 Meds – 4/5 Labs – 2/5 Common themes: Billing codes – 5/5 NLP – 5/5 Meds – 4/5 Labs – 2/5

Results Odds Ratio 2.0 Ritchie et al., AJHG 2010 rs Chr. 4q25 rs Chr. 4q25 rs IL23R rs Chr. 5 rs Chr. 5 rs NOD2 rs PTPN22 rs DRB1*1501 rs IL2RA rs IL7RA rs Chr. 6 rs RSBN1 rs PTPN22 rs TCF7L2 rs TCF7L2 rs TCF7L2 rs CDKN2B rs FTO rs5219KCNJ11 rs5215KCNJ11 rs IGF2BP2 Atrial fibrillation Crohn's disease Multiple sclerosis Rheumatoid arthritis Type 2 diabetes disease gene / region marker observedpublished

The eMERGE Network Coordinating center 135,000 20,000 10,000 4,000 3,000 Goal: to assess utility of DNA collections integrated with electronic medical records (EMRs) as resources for genome science Outcome: GWAS data in >20,000 subjects with EMRs. Vanderbilt phenotype: normal variability in QRS duration

GH Marsh Mayo NW Domain experts define phenotype (VU) Create initial EMR-based algorithm (VU) Evaluate & refine Share algorithm Hypothyroidism: An eMERGE network phenotype

Hypothyroidism algorithm Diagram courtesy Mike Conway (Mayo)

Site Case PPV (%) Control PPV (%) Group Health Marshfield Mayo Clinic 8296 Northwestern Vanderbilt All sites (weighted) Same algorithm, deployed at five sites Denny et al., AJHG 2011 Hypothyroidism Validation

Hypothyroidism: “No-Genotyping” GWAS FOXE1 Denny et al., AJHG 2011

eMERGE Phenotypes SitePrimary phenotypeSecondary Phenotypes Group HealthDementiawhite blood cell counts MarshfieldCataractsdiabetic retinopathy Mayo ClinicPeripheral Arterial Disease red blood cell counts ESR levels NorthwesternType 2 Diabeteslipids and height VanderbiltNormal cardiac conductionPheWAS Network Phenotypes Autoimmune Hypothyroidism Resistant hypertension =novel associations discovered bold=GWAS completed with significant results