Sanofi Press Breakfast on Behavioral Science. Friday 22 September 2017

Transcription

1 Sanofi Press Breakfast on Behavioral Science Friday 22 September 2017

2 Agenda WHY UNDERSTANDING BEHAVIORS CAN UNLOCK CARE SUCCESS Welcome coffee 9.00 Kick-off Introduction by Alexandra Rocca, Global Head of Communications Reducing the efficacy gap between the clinical and real world settings, the impact of patient behavior in clinical outcomes. Anne Beal, M.D., M.P.H, Global Head of Patient Solutions, Sanofi How Sanofi is active in the space of Real World Evidence? Bernard Hamelin, M.D., Global Head Medical Evidence Generation, Sanofi Evidation: a concrete case study to understand the technology behind behavioral science Christine Lemke, Co-founder and President, Evidation Health Q&A with the floor Close 2

3 Leveraging behavioral science to improve health outcomes Anne C. Beal, MD, MPH Global Head of Patient Solutions, Patient Solutions Unit

4 Pharma is facing unprecedented change In the real world, when people have to manage their conditions, they re not skilled at self-management, nor are they utilizing their treatments appropriately 50% of health outcomes are determined by behavior, yet physicians are not well trained for this part of their job 1 30% of people don t fill prescriptions for chronic conditions 2 50% of people with a chronic disease don t take their medication as prescribed 3 Helps people to achieve improved health outcomes by supporting optimal utilization of Sanofi products and services and enhancing their activation and self-management 1 Bipartisan Policy Center, 2012; Volpp, Kevin. NEJM Catalyst, Tanblyn et al. Annals of Internal Medicine, WHO,

5 OUTCOMES GAP Leveraging behavioral science to close the gap between real world effectiveness & efficacy Behavioral Science can address clinical inertia, patient activation and non-adherence which are critical to improving outcomes CLINICAL TRIAL EFFICACY* REAL WORLD EFFECTIVENESS FACTORS CONTRIBUTING TO GAP: PATIENT self-management, co-morbidities, concomitant medications PHYSICIAN patient interaction, care coordination, Rx behavior... SYSTEM access (formulary, reimbursement, quality of care, affordability CONTEXTUAL SES, zip code, race, ethnicity, social support, family, etc. Medical can bridge this gap through evidence-based interventions by: Understanding patient factors behind the gap and associate them with outcomes Designing interventions to influence key factors that will lead to improved outcomes *Relative scale of impact for patient factors, HCP, health system, and contextual factors varies case by case. Broader results/ outcomes differences in clinical trial efficacy and real world effectiveness may vary on a case by case basis. 5

6 Hibbard: Patient Activation Measure (PAM) LEVEL 2 LEVEL 3 Taking action LEVEL 4 Maintaining behaviors LEVEL 1 Overwhelmed & disengaged Becoming aware, but still struggling 10-20% 10-20% 25-30% 20-25% point scale 6

7 Hibbard: Activation and Medication Adherence Source: 2004 National Sample 7

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9 Access To Treatment Patient Knowledge Acceptance Of Therapy Symptoms / Quality Of Life Adherence Patient Experience With Treatment Management Of Side Effects Self Management Skills Habit Formation Patient Experience With The Service / Patient Satisfaction Health Outcomes Improve HCP Engagement / Activation Support HCP Dialogue With Patients Enhance HCP Management Of Chronic Illness Improve Patient s Relationship With HCP Improve HCP Experience / HCP Satisfaction Support Value Leverage Product Characteristics Differentiate From Competitors Position As A Healthcare Provider Support Market Access Enhance Efficiency Of Service Delivery Generate Data On The Impact Of The Service Advice and Input, Behavioral Science Toolkit 1 STRATEGIC AREAS OF IMPROVEMENT (ex: improve adherence. develop patient self management skills etc) 2 PRACTICAL OBJECTIVES (ex: improve patient enrolment, physician engagement, develop tool personalization etc) 1 Selection of the strategic area of improvement THEN PLEASE SELECT YOUR SPECIFIC STRATEGIC AREA OF IMPROVEMENT, BY CLICKING ON THE TOPIC PATIENTS HCP SANOFI 1 Recommendations for segmentation 2 3 Recommendations for segmentation Operational objectives highlighted *Prior to accessing information on your chosen operational objective, you will be presented with key segmentation reminders PHYSICIANS / NURSES / CHANNEL OTHER HCPS PERSONALIZATION AND HCP penetration Peer experience content AUTOMATION HCP Monitoring Differential messaging Typology of channels HCP activation / Patient Monitoring engagement Number of interactions / Value optimization contact frequency Patient initiation PATIENT Outcomes Patient persistence Educational content Patient engagement Motivational content Content Channels Enrollment Monitoring 2 Selection of the operational objective Enrollment Content Channels Monitoring 4 Exploration of Tips & Tools, Case studies and References Peer / Carer content Differential messaging 3 Exploration of Tips & Tools, Case studies and References 9

10 Sanofi and Real World Evidence Bernard Hamelin, MD Global Head of Medical Evidence Generation

11 Pharma is facing unprecedented change Physicians seeking peer-peer interaction Increasing safety concerns Vocal patient populations Tougher regulatory controls; societal expectation Rising development costs Digital Health Revolution Greater requirements for postmarketing evidence Payors pushing for Real World Evidence Shifting global demographics Increased transparency expectations Evidence generation needs to evolve to better understand and improve patient outcomes 11

12 Evidence required Evidence requirements are increasing Development Growth Phase Mature Phase Budget impact Post-marketing commitments (safety etc.) Unmet need/ disease burden Adherence Head to head safety, comparative effectiveness Effects of switching on outcomes Understand standard of care Patient recruitment Trial design Utilization/ prescribing patterns Long-term safety, clinical outcomes Differentiation in sub-populations Target populations Usage difference Differentiate with or vs. protected formulation Development Submission Launch Pricing Review New Competition New Indication / Formulation Competitor goes generic 12

13 Evidence generation methodologies Randomised Clinical Trial Pragmatic Clinical Trial Observational Study 13

14 Real World Evidence is based on data from multiple sources RCT Source : jama, 22 may

15 What we do: methodologies we use and partners we work with Methodologies Partnerships Traditional analytics Traditional RWE statistics Meta-analysis Propensity-score matching OMOP data modelling Predictive modelling Rule extraction Advanced analytics Natural Language Processing (NLP) Unsupervised clustering Machine learning Model bootstrapping 15

16 New data, new platforms, and new analytics make new insights possible NEW SOURCES OF DATA NEW PLATFORMS AND VISUALIZATION NEW ANALYTICS 16

17 Quantifying impact of behaviors on health outcomes

18 Evidation Health is a technology and services company that helps individuals and healthcare companies understand the link between everyday behaviors and health outcomes. 18

19 Patients and their outcomes have been characterized by using limited data sets based on what was visible to the system. DATA POINTS Visible & Episodic (in clinical settings) TIME Invisible & Continuous (in real life) 19

20 Evidation captures previously invisible everyday behavior data and combines it with traditional clinical data sets to understand behaviors and health outcomes. REAL WORLD PRACTICE TRIALS clinical trial data provider system registries EHR data pharmacy and medical claims REAL LIFE OF THE PATIENT behavior data (activity, sleep, diet, social media, cognition, technology interaction, etc.) contextual data (weather, pollen count, geolocation, census data, occupation, etc.) patient-reported metrics (symptoms, outcomes, anytime, anywhere) 20

21 This explosive new data source - behavior data - shows promise to quantify health outcomes more quickly and observe new effects. BEHAVIOR Evidation Platform Applications Lifestyle Activity Voice/Speech Heartrate Weight Social Location Sleep Other CONTEXT DEMOGRAPHICS PLACES WEATHER OTHER.. CLINICAL EMR CLAIMS LABS OTHER.. Data Analytics for discovery Digital Biomarkers to identify and quantify: TREATMENT EFFECTIVENESS CONDITION ONSET INTERVENTION WINDOWS CONDITION PROGRESSION 21

22 It requires a scalable system to connect directly with individuals to gather, contextualize, and combine behavior data with clinical data. QUANTIFIED IMPACT REAL LIFE DATA CONNECTED POPULATIONS >1.5 BILLION new activity events recorded each month >3 MILLION patients on the platform, across multiple therapeutic areas 22

23 and services combined with a platform to reach individuals for permission-based data sharing Find people 10x faster Design research studies Execute privacy safe, virtual study protocols Interpret and deliver results Peer review standard Sanofi Press Breakfast on Behavorial Science - 22 September Paris 23

24 Results: faster, more proactive care Digital Biomarker Discovery Digital Evidence Generation Digital Biomarker Discovery Challenge Understand medication adherence in patients with diabetes Assess the effectiveness of medication adherence application Quantify cognitive decline through voice and speech signals Data inputs Weight, activity, adherence measured through pharmacy claims data Connected monitors, engagement data, patient reported outcomes Voice, speech, clinical data Results Discovery of behavior pattern that led to adherence drop Recruited and observed 400+ patients, recruited 10x faster Predict cognitive decline scores solely based on voice and speech (research embargoed) Application Monitor patients and deliver diabetes education at right time Evidence package for use in market commercialization Improved screening, monitor therapeutic impact (e.g. oncology) Sanofi Press Breakfast on Behavorial Science - 22 September Paris 24

25 Questions September 2017 evidation.com

26 Thank you

27 Q&A