Mapping the Patient Journey: Harnessing the power of big data and analytics
Can Big Data & analytics make the dream of patient-centric Pharma a reality?
Get a guided tour of the Big Data landscape for Pharma, find out why it’s so difficult to extract actionable information, learn how to engage patients and payers, and understand the growing pains you’ll face as you transition to a data-driven culture.
With Big Data and analytics, Pharma can finally map the patient journey—developing better, more targeted treatments by knowing when and how to get involved. But companies without the skills to harness Big Data face a steep learning curve.
This timely report brings you up to speed with case studies, best practices, and insight from 12 data and analytics experts. Required reading for Pharma companies.
“With the advent of Big Data… we're able to glean insights from hundreds of thousands and sometimes millions of patients to understand what's really going on in terms of patient care…”
Reasons to Purchase
Practical Advice for Harnessing Big Data
Answering key questions:
- Breaking down the patient journey: Understand the questions you need to ask—and the kinds of data you’ll need to answer them—as you map each stage of the patient journey.
- Where does the data come from? Learn about the major sources of health data available to Pharma, what they tell you about patients, and what they leave out.
- Putting it all together: Get up to speed on the complex web of technologies and analytical techniques you’ll need to make Big Data’s disparate parts tell a coherent story.
- From Big Data to business insight: Discover a three-step approach for turning mountains of health data into actionable intelligence.
- Handle with care: Find out how to protect sensitive patient-related information as data use becomes more widespread in your organisation.
- All aboard! From analysts and scientists all the way up to a Chief Data Officer, hear about the new talent you’ll need to build in-house data expertise, and where to find it.
- The new normal: What organisational and cultural changes will you need to make to become a truly data-driven organisation?
- What’s in it for patients? How will mapping the patient journey improve the way diseases are diagnosed, treated, and managed?
- What’s in it for Pharma? What new commercial opportunities will mapping the patient journey unlock? How will it change the way you develop, price, and launch new drugs?
- Partnering up: Big Data fluency requires special skills that Pharma has yet to fully appreciate. Should you outsource your analytics to companies that have them?
- Signal vs. noise: Will much-hyped wearables and mobile apps deliver on their promise of engaging patients and providing usable real-time data?
- What’s next? The future of data-driven care will focus on precision, prediction, and prevention. What are the key technologies and data sources to watch?
This report is based on interviews with 12 data and analytics experts from leading pharma, consulting, marketing, and healthcare-associated companies.
- Dr. Andree Bates. President, Eularis – Pharma Analytics
- Carl Bilbo. Corporate Vice President, Novo Nordisk
- David Coleiro. Partner, Strategic North
- Dr. Susan Dorfman. Chief Commercial Officer, CMI/Compas
- Clement François. Vice President, HEOR, Lundbeck US
- Rajeev Gangal. Programme Director, Saama Technologies, Inc
- Andrew Maric: Business Information Manager, Chugai Pharma UK Ltd
- Nigel Hughes: Director of Integrative Healthcare Informatics, The Janssen Pharmaceutical Companies of Johnson & Johnson
- Usman Iqbal. Senior Medical Affairs Leader – Neuroscience, Global Medical Affairs, AstraZeneca
- Priya Sapra. Chief Product Officer, SHYFT Analytics
- Ramon Vega. Senior Director, Pfizer UK
- Abhimanyu Verma. Head of Real World Evidence and Big Data Solutions, Novartis
- James Woodland. Chief Operating Officer, CMI/Compas
Interviews were conducted in May and June of 2016.
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- 1 Executive Summary
- 2 Research Objectives
- 3 Research Methodology
- 3.1 Experts interviewed
- 3.1.1 Definitions
- 4 The growing role of Big Data in pharma
- 5 The importance of Big Data in mapping the patient journey
- 5.1 Key insights
- 5.2 A wealth of clinical opportunity
- 5.3 A commercial revolution
- 5.4 The data needed to successfully map the patient journey
- 5.5 SWOT Analysis for mapping the patient journey
- 6 From knowing the data needed to being able to use them successfully
- 6.1 Key insights
- 6.2 Creating a data strategy
- 6.3 Sources of data
- 6.4 Harmonising data from multiple sources
- 6.4.1 The pros and cons of different data sources
- 6.5 Complementing data sources
- 6.6 Outsourcing and partnerships
- 7 Modelling and simulation to extract business insights from Big Data
- 7.1 Key insights
- 7.2 Modelling the stages of the patient journey
- 7.2.1 Stages 1 and 2: Awareness/screening and diagnosis
- 7.2.2 Stages 3 and 4: Treatment landscape and disease management
- 7.2.3 Stage 5: Health outcomes
- 7.3 Performance-based research networks
- 7.4 Selecting and leveraging multiple databases
- 7.5 Mapping the major stages of the patient journey
- 7.6 The impact of mapping the patient journey
- 7.6.1 A mapped journey leads to improved awareness and diagnosis
- 7.6.2 A mapped journey leads to improved and more targeted treatments
- 7.6.3 A mapped journey leads to improved adherence
- 7.7 Bringing patients on board
- 7.7.1 A caveat about digitally sourced patient data
- 7.8 Targeted marketing strategies and sales messages: Big Data’s competitive advantage
- 8 The challenges of handling patient‑related data
- 8.1 Key insights
- 8.2 Fragmented internal and cross-organisation data
- 8.2.1 Cloud computing to accommodate Big Data
- 8.3 Security of data
- 8.3.1 Cloud-based solutions for reduced data vulnerability
- 8.4 Organisational structure, talent and maturity for Big Data
- 8.4.1 A data-driven organisation and culture
- 8.4.2 New talent
- 8.4.3 Maturity
- 8.5 The dynamic nature of the patient journey
- 9 The best future opportunities for the use of Big Data in patient engagement
- 9.1 Key insights
- 9.2 Genome-based precision medicine
- 9.3 Using predictive analysis
- 9.4 Expanding the continuum of care and focusing on preventive care
- 9.5 Transforming drug development
- 9.5.1 Clinical trial design
- 9.5.2 Pricing
- 9.5.3 Commercial launch
- 9.6 Maintaining the virtuous circle of trust between patients and industry
- 10 Conclusion
- 11 Appendix
- 11.1 Biographies