Optum Labs- Partners, Data and Design. April 2015

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Optum Labs- Partners, Data and Design April 2015 Paul.Wallace@optum.com

Optum Labs: Driven by Data. Powered by Partners. First open, collaborative research and innovation center to accelerate healthcare change, leading to improved patient care and patient value. Founding partners: Optum and Mayo Clinic State-of-the-art facility in Cambridge, Mass Pre-competitive research collaborative Pre-commercial innovation center Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 2

Our Partnership Platform: Quality Growth Continues Foundation Scientific Integrity 1 st Constellation Quality Growth Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 3

Our Data Today: Claims, EHRs & Consumer Behavior 315 million U.S. population >35 million Consumers >33 million unlinkable claims Clinical Data (EHRs) for >31 million Patients Linkable Claims for >128 million Patients 1,500+ data fields: Medical claims Pharmacy claims Lab claims and results Health risk assessments Standardized costs of care Race Income Education level Household Geography Mortality Expanded insights with Consumer data 300+ additional data fields: Consumer Behavior: general trends Demographic view including Income, Assets, Home Value, Education Level, Marital Status, Occupation, Home Ownership, Household Make-Up (multigenerational, presence of: children, grandchildren, grandparents), Ethnicity Data Psychographic Data including interest and participation in : travel, various leisure activities, charitable giving, advocacy, volunteering, community involvement Tests, Treatments Expanded insights with deeper clinical context 250+ additional data fields: Encounters Vitals (BMI, BP, Heart Rate ) Labs Medication orders Procedures Admissions, discharges and transfers Patient-provided information Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 4

Optum Labs: Five key assets to help solve many problems 1 Linked medical claims/ehr data 2 3 4 Forums to convene collaboration Translation partners Experts on staff, within partners and alongside Optum 5 Data visualization power tools 5

Our Database Goal: DNA to Diet to Disease to Death 315 million U.S. Population Buying Behavior Patient Registries Employer Data Genomic 35 million Consumer Behavior 33 million Claims (unlinkable) Health system 1 Health plan 2 128 million Claims (linkable) Health plan 3 Health system 2 Gov t Data 31 million Clinical Mayo Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 6

What happens here: A diversity of research methods Number of projects by disease category Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 7

What happens here: A diversity of diseases 18 16 14 12 10 8 6 4 2 0 Number of projects by disease category Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 8

Constellations: Solving big problems together Sponsored: The National Heart Failure Collaborative The U.S. Big Data Research Initiative to Fight Alzheimer s Disease In development: Type 1 Diabetes New Quality & Performance Measures New Big Data Methods Oncology Reducing Cost of Complex Co-Morbidity Patient/ consumer organizations Academic institutions Government researchers Life sciences companies Disease or Specific Healthcare Issue Technology leaders Health care providers Commercial payers/ employers Why do partners need one? I need answers to big questions I need a big data strategy I need arms, legs and brains to go faster I want collaboration with domain experts Research Clinical translation Innovation Policy change I need to cut my costs I want to predict a disease because Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 9

Treating Congestive Heart Failure Devices Disease Management Care Personalization Innovation Value Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 10

HF Constellation Roadmap and Partners Heart Failure Heart Failure Constellation Partners Boston Scientific Constellation Leader Optum Labs Mayo Constellation Academic / Clinical Partner Novartis Constellation Sponsor Additional Constellation Partners Current Status Year 1 Environmental Scan Baseline Predictive Model Mayo HF Constellation Projects Year 2 Predictive Models for Patient Clusters HF Patient Pathways for Patient Clusters Optum Labs HF Const. Projects Mayo HF Constellation Projects Novartis HF Constellation Projects Additional HF Constellation Projects Year 3 Impact to Remote Monitoring & Device Diagnostics Optum Labs HF Const. Projects Mayo HF Constellation Projects Novartis HF Constellation Projects Additional HF Constellation Projects Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 11

Precision Medicine for Heart Failure Patients Personalized HF Therapy Rx Devices Rx & Monitoring Phenotypic Profiling & Mapping Care Mgmt Services: Health Coach Patient-centric non-hf Interventions (comorbidities, family, nutrition, loneliness ) Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 12

Precision Medicine for Heart Failure Patients Phenotypic Data - Biomarkers LVEF Heart Rate BP Systolic/Diastolic BNP Creatinine Troponin BMI Age Gender Etc. Genomic Data Precision Medicine: Heart Failure Phenotypic Data - Demographics SES QOL Marital status Church attendance Etc. Phenotypic Data Comorbidities Hypertension Diabetes COPD CKD Sleep Apnea Hyperlipidemia Afib Obesity Dementia Etc. Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 13

Phenomapping and Patient Clustering, key studies Characteristics Ahmad T et al / Duke Study population Patients from randomized clinical trial, HF- ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) Patient Characteristics: Shah SJ et al / Northwestern March 2008 May 2011 420 OP Clinic patients identified after hospitalization for HF HF Constellation patient clustering work in progress Cohort of patients with prevalent HF extracted from OLDW claims data only Confirmed diagnosis of HF between 2009 and 2014 Comparison Get with the Guidelines (GWTG) Patients hospitalized for HF from January 2005 to March 2006 (97 Hospitals) Cohort, n 1619 397 231,764 18,516 Age, years 59 65 72 73 Female, % 27 63 50 50 Race, % White 62 52 69 72 Black 33 38 16 16 Other 5 10 14 12 Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 14

Alzheimer s: Building a Global Big Data Center of Excellence Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 15

Alzheimer s Constellation Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 16

A Research Agenda to Drive Innovation Forward YEAR 1 Launch YEAR 2 Learn YEAR 3 Leverage PREDICTION AND DIAGNOSIS DISEASE PROGRESSION Epidemiological Profile of Alzheimer s Population Early Risk Signals Variation in the Path to Alzheimer s Diagnosis Population characteristics picking up the early signals Clinical Data Model for Alzheimer s from EMR Structured Data Exploratory Study: NLP on Clinical Notes for Alzheimer s Patients Predictive Model for Identifying Early Alzheimer s Risk Exploratory Study: Predictive Power of Consumer Data Predictive Model for Alzheimer s Risk Staging CARE PLANNING Community-based Indicators and Alzheimer s Care Caregiving and Impact on Patient and Caregiver Health Comorbidity in Alzheimer s and Implications for Care PATIENT REGISTRY Develop Prospective Care Registry framework and specifications for Alzheimer s patient and key measures functionality Populate registry www.ceoalzheimersinitiative.org 17

New Data Methods Constellation Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 18

New Data Methods Constellation Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 19

New Quality & Performance Measures Incubator Powered by Optum Labs Optum Labs New Quality Measure Incubator NQF New Measure Standardization Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 20

NQF Quality Measurement Incubator at Optum Labs Designing and delivering quality measures that matter NQF Members/ Other Partners Providers Academics Nonprofits Optum Labs Partners Optum Labs Linked Data: Data, Methods, Technologies (EMR, claims, consumer data) INNOVATIVE MEASURE DEVELOPMENT E-measures Outcome measures Patient-reported Outcome measures Cost/Efficiency/ Value measures Transparent NQF Evaluation Process Effectiveness Efficiency Incubator-enabled evaluation of existing and novel quality measures QMI Advantages Volume Cycle time Patient Relevancy Scope Overall value Innovation Improved patient care & outcomes Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 21

Value Proposition: Seat at the table of health care innovation Lead a high impact national Initiative, called a constellation Collaborate on healthcare s biggest issues Life sciences companies Develop Your Big Data Strategy Create innovation New predictive models, algorithms, and tools Patient/ Consumer organizations Academic institutions Health Care s Biggest Challenges Health care providers Commercial payers/ Employers Accelerate best practice clinical translation Government researchers Technology leaders Advance your policy agenda Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 22

Optum Labs Ways to Engage Constellation Leader Constellation Sponsor Constellation Member Research Partner (Data & Virtual Sandbox Access) Strategic Thought Leader (Special Forums & Advisory/Council Seats) Collaboration Partner (Collaborator w/o Data Access) Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 23

Life sciences at Optum Labs: Accelerating discovery through collaboration Join us to learn how the health care industry's first open, collaborative research and innovative center is bringing together great minds to accelerate discovery through collaboration. And see firsthand how life sciences companies can benefit from and contribute to this great endeavor. Tuesday, June 23 10:00 am 3:00pm One Main Street, 10 th Floor Cambridge, MA 02142 Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 24

Thank You.

Backup Slides

Data from disparate sources can be linked and de-identified Name Address Birthdate SSN Phone, etc. Direct identifiers (EMR / Clinical) Primary hash Shared Salt Code (same for all contributors) Data is then hashed by contributors at their site. OPTUM LABS Name Address Birthdate Member ID Phone, etc. Primary hash Direct identifiers (Insurer example) Secondary hash De-identification Statistically de-identified views Uses Optum Labs Confidential Salt Optum Labs employs certified de-identified data sets, together with a hashing methodology to enable matching individuals from multiple sources, yet preserving statistical de-identification. Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 27

Virtual Sandboxes: How to Access The Data Virtual computing environment Policy-based security Research sandboxes: Specific choice of data view and statistical/visualization tools E.g., NHD, SAS, R, Spotfire Research views (certified as de-identified) Controlled granularity e.g., State, Zip3, Date of Death Linked logical database Linking by secure double-hash algorithm Optum Labs Data Warehouse OLDW Ingestion of de-identified data Housed in Optum Labs Data Center Source databases dnhi Mayo Humedica Etc. De-ID with first-stage hash/salt at source Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 28

Back Surgery Predictive Model: Optum Labs model shows 37% improvement in accuracy over existing Model Dataset Application # Variables Detection Prevalence Sensitivity PPV Current Model (Feb. 2013) Optum Labs Model OptumHealth Outbound (DP = 3.8%) 18 3.80% 29.24% 5.69% 54 3.80% 40.00% 7.79% Identifies 24.9% more patients headed for back surgery 557 evisor IDed 130 427 335 1013 762 New Model IDed 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% IDed by evisor Only IDed by Both IDed by New Model Only Not IDed Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 29