Leveraging Informatics to Improve Health Outcomes and Value Marc S. Williams, MD Director, Genomic Medicine Institute Geisinger Health System Danville, PA 1
Topic Perspective Genomic Medicine Personalized Medicine Individualized Medicine Precision Medicine 2
Genomic Medicine • Includes o Traditional single gene disorders (genetics) o Analysis of the whole genome (genomics) o Analysis of subsets of the whole genome Exome sequencing Pharmacogenomics o Family History 3
Personalized Medicine-Definition “…use of information and data from a patient’s genotype, or level of gene expression to stratify disease, select a medication, provide a therapy, or initiate a preventative measure that is particularly suited to that patient at the time of administration” – Wikipedia 4
Genomic Medicine ≠ Personalized Medicine “Personalized medicine is the practice of clinical decision-making such that the decisions made maximize the outcomes that the patient most cares about and minimizes those that the patient fears the most, on the basis of as much knowledge about the individual’s state as is available .” Pauker and Kassirer N Engl J Med 316:250-258, 1987* 5
Personalized vs. Precision Medicine • Clinicians practice personalized medicine (and always have) • Currently--Intuitive medicine o Care for conditions that can be diagnosed only by their symptoms and only treated with therapies whose efficacy is uncertain and watching for empiric response. o Empiric ‘trial and error’ • Future — Precision medicine o The provision of care for diseases that can be precisely diagnosed, whose causes are understood, and which consequently can be treated with rules-based therapies that are predictably effective. o Expect genomics to play a key role in this Adapted from The Innovator’s Prescription A Disruptive Solution for 6 Healthcare. Christensen , Grossman and Hwang, 2009
GenomeFIRST TM A N EW P ARADIGM FOR R ETURN OF G ENOMIC R ESULTS 7
6. Order Genetic 8. Review Genetic Patient Provider placed with results and Counselor relevant Labs recommend clinical info treatment 3. If patient is 4. Screen 5. Case review, 1. Patient has 2. Patient fills high risk, patient for order genetic tests encounter, out detailed schedule further for patient and fills out initial genetic FHH and testing optionally family screening app medical Hx app counselor Genomic Risk Risk Genomic Diagnosis and 7. Return narrative, Dynamic Predictive Models codified genomic result assessment Screening Treatment inference Family Health w/ machine History app Applications app Recommendation Engine learning Knowledge CDS base Risk Family Genomic Screening Health CDR EHR Repository Data History The Current Approach —‘Phenome First’ Ideal
• GHS Biorepository started in 2007 – Followed extensive consultation with GHS patients and other stakeholders that informed design of project – Defined as Community Health Initiative as opposed to biorepository • Participants sign broad consent to combine EHR data (prospective, de-identified) and biospecimens • Consent includes the ability to re-contact participants for future projects and communicate medically actionable results • Exome sequencing on participants (~53,000) 9
GenomeFIRST TTM Return of Results The prompt for the clinical encounter is the DNA variant 10
GenomeFIRST TTM Return of Results • 250,000 Geisinger Patients Will Have Their Exomes Sequenced. • We will Look For Medically Actionable Results In That Data And Then Return Results To Patients And Providers. • We will support the patients and providers in the follow- up to the results and long term management planning. • We will be Operationalizing A Scalable Genomic Return Of Results Infrastructure In A Large Integrated Healthcare System 11
GenomicFIRST TM Return of Results The Geisinger 76 (G76) • Focus on 27 conditions (76 genes) • Builds on the ACMG Incidental Findings List (published 2013) • Cancer predisposition (e.g. BRCA1 and BRCA2 ) • Cardiovascular disease (e.g. FH) • Malignant Hyperthermia • Hereditary Hemorrhagic Telangiectasia • Ornithine Transcarbamylase (OTC) deficiency 12
Three Most Prevalent Conditions Half of those Returned GENOMIC POPULATION CLINICAL DISEASE-ALTERING CONDITION PREVALENCE RISK INTERVENTION Early-onset Familial Targeted screening and Coronary Artery Hypercholesterolemia 1 in 175 aggressive medical Disease and ( LDLR, APOB,PCSK9) management Stroke Hereditary Breast and Early-onset Ovarian Cancer Targeted screening with Breast, Ovarian, Syndrome 1 in 400 prophylactic medical and and Prostate ( BRCA1, BRCA2) surgical intervention Cancers Early-onset Targeted screening and Lynch Syndrome 1 in 440 Colon and Uterine management of pre-cancerous ( MLH1,MSH2,MSH6,PMS2) Cancers changes Multiple Cancers Life-saving screening and and TOTAL > 1 in 100 intervention before Cardiovascular development of disease Diseases
Secondary or Incidental Finding of a PATHOGENIC/LIKELY PATHOGENIC VARIANT GENE SPECIFIC EVALUATION Including history, exam, testing, consultation DIAGNOSIS OF GENOMIC SYNDROME NO DIAGNOSIS OF GENOMIC WITH TESTING AND INITIAL EVALUATION SYNDROME WHEN TESTED Both Genotype and Phenotype Present Genotype without Phenotype GROUP 2 GROUP 3 GROUP 4 GROUP 1 GROUP 5 Unifying Existing New No No Genomic Genomic Genomic Genomic Genomic Syndrome Syndrome Syndrome Syndrome Syndrome Diagnosis Diagnosis Diagnosis Diagnosis Diagnosis Achieved Achieved Confirmed Achieved Initially Initially Sub-clinical Previous Previously genotype and phenotype Phenotype Phenotype documented phenotype revealed thru Emerges over phenotype and Does Not time documented evaluation Emerge new genotype No GENOMIC SYNDROME DIAGNOSED Genomic Both Genotype and Phenotype Syndrome 14
Geisinger GenomeFIRST TM Clinical Workflow 3. Telegenomics Clinical Evaluate “at risk” linking CG to Genomics Lab Patient Providers Genomics (CG) patients and Relatives providers 1. A targeted 6. Relatives 5.. Penetrance and “slice” of the 4. Clinical team including patient, 2. EHR test offered expressivity primary care, specialists, CG genome is result reviewed genotyping determined, this carry out phenotyping which by CG then reviewed for and drives case includes family health history pathogenic notifications phenotyping management variants Genotype Genomic Standardized Diagnosis and Genomic Predictive Dynamic Family without inference Models phenotyping Management Health History app Phenotype f/u Engine recommendations Recommendations w/ machine learning Strategies Knowledge CDS base Risk Family Genomic Screening Health CDR EHR Repository Data History
Implementation Barriers • System leadership o Genomic medicine is represented in both the system and research strategic plans • Clinicians o Presentations at system-wide and department level business meetings and conferences o Identifying clinician champions in relevant areas o Take advantage of existing infrastructure Multidisciplinary hereditary cancer clinics Lipid Clinic • Education and support for providers and patients o Goals courses (CME available) o Provider and patient facing genome reports o Genomic Medicine Consultants • Informatics systems 16 16
Measuring Value • Define outcomes for GenomeFIRST program o Health Outcomes Process Intermediate Disease/Health o Patient-Centered Outcomes Satisfaction Engagement Information Access Self-assessed well being o System Outcomes Costs incurred/avoided Utilization Patient experience Visibility/reputation 17
Value from the Health System Perspective 18
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Value: Genomics over the Lifespan Advantages Questions Cost spread out over Storage of information lifetime of care Presentation of information when needed at point of Avoids need to repeat care testing Information available Information can be used as wherever patient receives soon as it is needed care More precise Evidence of benefit (or lack pharmacologic therapy thereof) o Avoid adverse events Updating information o Choose best tolerated Discrimination most effective therapy Health Disparities
Storage 21 21
Information at point of care • Focus on passive clinical decision support • Highlight Clinical Genome Resource (ClinGen) 22
ClinGen The Clinical Genome Resource (ClinGen) aims to create an authoritative resource that defines the clinical relevance of genes and variants for use in precision medicine and research. NHGRI-funded program launched Sept. 2013 FY13-FY16 = $28M Total Costs 3 U grants, working closely with NCBI’s ClinVar Co-funding from NICHD and NCI > 350 researchers & clinicians from 90 institutions 23
Building a genomic knowledge base to improve patient care
Initial Solution https://www.clinicalgenome.org/ 25
Access to ClinGen resource from any OpenInfobutton compliant EHR system http://service.oib.utah.edu:8000/app/#/home 26
e-Resources 27
Add ClinGen to your e-Resources We can create a unique link for your institution so you can add to your own e-resources collection 29
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