Approach to Generating Evidence of Drug Safety and Efficacy David - PowerPoint PPT Presentation

EHR-fueled Trials: A New Approach to Generating Evidence of Drug Safety and Efficacy David D. Dore, PharmD, PhD Chief Research Officer Optum Analytics – Life Sciences 1

Mission • Be the gold-standard solution for • Create a fully scaled, end-to-end EHR-fueled trials solution for clinical trial design, patient identification trial execution • Transform our EHR platform into and analytics a pliable research platform that • Employ industry-leading experts enables the learning health care system and connecting sponsors, care delivery organizations, and research participants to move research closer to clinical practice Extending our analytics for faster, cheaper, better, more relevant clinical research to drive patient engagement, improve outcomes, reduce costs, facilitate population health management and speed medical product development. 2

https://healthpolicy.duke.edu/sites/default/files/atoms/files/rwe_white_paper_2017.09.06.pdf 3

Why we do randomized trials Hernan and Robins. Epidemiology • Volume 17, Number 4, July 2006

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Optum’s unique sourcing model enables most comprehensive clinical data Multi-specialty Small group Physician practices practices offices EMR2 EMR1 EMR2 EMR 3 EMR1 EMR3 Integrated delivery networks Rx platform Rx platform Rx platform Rx platform Billing system Billing system Billing system Billing system Medical groups Hospitals Staging Area • Provider notes • Demographics • Lab results • Procedures (NLP) • Diagnosis • Medications • Outpatient visits • Vital signs • Hospitalizations • Observations Processing: Validation. Normalization, Standardization. Mapping. Analytics for Data & Analytics for Longitudinal Providers Life Sciences Comprehensive Dataset: 70M+ Lives

Optum EHR-fueled clinical trial solution Optum is building an end-to-end EHR-fueled clinical trial platform to be embedded within the model of care delivery in order to reflect real-world practice and drive patient engagement. $$ $$$$ $$$$ $$ SITE SELECTION & DATA ANALYSIS, DATA DESIGN PATIENT REPORTING & OPTIMIZATION RECRUITMENT TRANSLATION EHR data-informed and Optum-cultivated cadre of EHR data-driven Real-world data science science-driven fit-to-study study sites (CDOs) design • Protocol development, • Optimized, data-informed • Platform-enabled data • Data analysis including statistical design choice of site based on trial collection, • Analytics to drive in-trial elements needs management refinements and cleaning • Patient recruitment • Efficient start-up due to • Reporting and research • Centralized monitoring previously-built • Implementation program translation infrastructure and clinician and QA processes • Medical communications engagement • Patient identification, recruitment and retention 9

Extending on current infrastructure EHR- fueled trial “Re - mastered Data” • Separate data process at appropriate Funded stage innovation (e.g., Stage Environment, CDR) • Compartmentalized, compliant hardware Optum analytics New build • Separate team of researchers, data data factory scientists, engineers, and operations • Handled, with permission, on behalf of based on Optum to drive Care Delivery Organization provider client data innovative data • Analyzed within Optum, CDO, and analytics offerings sponsor, and/or regulatory agencies (e.g., FDA) • Supplementary electronic data capture • Tools and automation for centralized data verification, edit checks • Command center intervention enabled by data visualization 10

Moving Research Closer to Practice Current Paradigm Research Practice Translate Optum pRCT Platform Translate Research Practice Inform 11

Where we’re going – subsequent development/launches Trial offerings • Launch single Phase IV trial across multiple CDO sites • Launch full Phase IV program (i.e., multiple studies, multiple sites) • Phase III pilot Program scope • Protocol development, refinement, and targeting • Development of cadre of CDOs sites ready to deploy for study needs • Automation of data capture • Clinician engagement and training • Patient engagement • Integration of remote patient monitoring tools, telemedicine capabilities 12

Value opportunities across trial lifecycle Study conduct Analysis and Patient and data reporting Site initiation Protocol recruitment Site selection handling Opportunity development identification Provide match- Data-driven Quantification of Identification of Identification of Replace Centralized data making service design patients at site specific patients specific patients primary data auditing collection, data between and providers and providers sponsors CDOs monitors, and … Eligibility criteria Advanced on-site quality informed by data analytics to Enable providers Recruitment on assurance Assess for greater identify best to quantify the behalf of suitability of efficiency sites and value of sponsor and population patients (e.g., participating CDO by Optum Passive follow- Value likely (e.g., # of up of patients Pre-trial participants) patients, cost, Simulating trials analytics ensure Group-level financial risk) before that trial will randomization Light-touch recruitment target most Sponsor research (enabled by data appropriate preferred sites Coordination Advanced platform) population can be on- across CDOs analytics to Track boarded, driving choose efficient participants lost growth of Optum populations to follow-up One 13

Current Workstreams NETWORK EXPANSION – onboarding preferred research sites NEW DATA PIPELINE – hardware, data engineering, compliance, security UPSTREAM DATA ACCESS – working with care-delivery organization as healthcare operations analysts DATA MEASUREMENT PROJECT(S) – comparing classical data collection to EHR-based Real-world Real-world Real-world Data Information Evidence 14

Current Workstreams NETWORK EXPANSION – onboarding preferred research sites NEW DATA PIPELINE – hardware, data engineering, compliance, security UPSTREAM DATA ACCESS – working with care-delivery organization as healthcare operations analysts DATA MEASUREMENT PROJECT(S) – comparing classical data collection to EHR-based Real-world Real-world Real-world Data Information Evidence 15

DURATION-3 Results (Selected) HbA1c (%) Weight (Kg) Diamant, et al. Lancet Diabetes Endocrinol. 2014 Jun;2(6):464-73.

DURATION-3 Results (Selected) HbA1c (%) Weight (Kg)

Summary • Most healthcare entities base policy decisions on clinical trials – Pros: Clinical trials are carefully done and give accurate answers – Cons: Answers may apply only to highly selected populations, ideal settings • Efficacy = Effectiveness? • For appropriate applications: With advances in data and research methods, we can conduct OBSERVATIONAL real-world effectiveness studies to directly measure patient outcomes. • For many applications: We will need to conduct RANDOMIZED trials. This journey is just starting. Please join us. 18

Thank you Thank you. david.dore@optum.com david.dore@optum.com Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 19