Big Data in Pharma: Current & Future Trends for Big Data Utilization

Across the Health Outcomes Research Function

Best Practices, LLC Strategic Benchmarking Research Study with HEOR Functions

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Table of Contents

I. Executive Summary pp. 3-8

Research Overview pp. 4

Universe of Learning pp. 5-6

Big Data Team Overview and Key Study Insights pp. 7-8

Quantitative Key Findings pp. 9-12

II. Defining Big Data pp. 13-20

III. Data Types and Sources pp. 21-26

IV. Data Producers, Dissemination & Requestors pp. 27-31

V. Centralization pp. 32-34

VI. Governance and Leadership pp. 35-51

VII. About Best Practices, LLC pp. 52

Best Practices, LLC, conducted a customized study – with responses segmented by medical,

commercial and Health Outcomes Research (from now on called either Health Outcomes or HEOR)

functions - to better understand the growing influence of Big Data in the biopharmaceutical sector and

how it impacts HEOR.

Best Practices, LLC engaged 15 leaders

from 13 pharmaceutical companies

through a benchmarking survey.

Research analysts also conducted

seven deep-dive executive interviews

with selected benchmark participants.

Research

Goal

Research

Methodology

Produce reliable industry metrics on

current and future trends for Big Data

utilization across medical, commercial

and HEOR groups.

Topics Covered

Types of Big Data Projects Used to Support

Medical, Commercial and HEOR Decisions

Big Data Capabilities and Governance

Types and Value of Data Used for Big Data

Projects

Big Data Staffing and Budget Levels

Value Rating of Partnerships on Big Data

Projects

Policies and Procedures Governing Big

Data Activities

Investigate data types, data partnerships,

and staffing/budget levels companies

are using as they move to a more

analytically based approach to

commercial, HEOR & medical decisions.

Research

Overview

Research Project Objectives & Methodology

Benchmark Class:

Thirteen Companies Participated in the Benchmark Study

Best Practices, LLC engaged 15 leaders from 13 pharmaceutical companies through a benchmarking

survey to discuss how their companies approach Big Data utilization within HEOR. Executive

interviews were also conducted with function leaders and others from Medical Affairs and Commercial.

Copyright © Best Practices, LLC 5

Analytics

Team

Big Data

Function

Understanding Big Data Use in Medical, HEOR & Commercial Decision-Making

Big Data Questions • Medical

• Commercial

• HEOR

Big Data Info Types • Electronic Health Records

• Government Cost Data

• Health Outcomes

Big Data Projects • Value Proposition Development

• Post-Launch Performance

• Real World Studies

Big Data Decisions • Go/No Clinical Decisions

• ID Market Opportunities

• Developing Economic

Models/Assessments

Copyright © Best Practices, LLC 6

Quantitative Findings

The following key Big Data findings were observed in this study:

Only 5 of 36 types of Transactional, Reported, Online, Scientific and Machine-

Generated data were rated highly valuable by a majority of study participants.

They were: Claims; EHR (Electronic Health Records); Health Outcomes

(provider/payer reported); Real World Studies; and Registries. No types of

Online or Machine-Generated data were rated highly valuable by a majority of

any segment.

Six out of ten benchmark participants used post-launch studies around health

outcomes. The second most highly rated reported data type is patient reported

outcomes data.

Half of the study participants said they have a centralized/dedicated group (Big

Data team or function) to support Big Data projects.

Post-Launch and Customer Segmentation Studies Most Common

Big Data Projects

Most Have Centralized or Dedicated Big Data Team

or Function

Only 5 of 36 Types of Data Rated as Highly Valuable

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Health outcomes(provider/ payer

reported)

Patient reportedoutcomes (PRO)

Governmentsurveys (e.g.,

NHANES)

Internally-drivenmarket research

surveys

Reported adverseevents

Call center &customer care

Focus groups

Impact of Reported/Survey Data (HEOR)

Highly impactful Somewhat impactful Not impactful Not used

Reported Data: HEOR Highly Values Health Outcomes Data

Sixty percent of the study participants in HEOR roles said for Big Data studies they highly value

health outcomes data from providers and payers. Patient reported outcomes data was the second

highest rated reported data type.

N=15

Q: How impactful (or valuable) has each of the following types of reported/survey data sources proven to be?

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Impact of Data Producers (HEOR)

Highly impactful Somewhat impactful Not impactful Not used

HEOR: Commercial Payers Seen as Most Valuable Data Producers

HEOR leaders found commercial payers to be most impactful. HIEs may constitute a larger share of

data in the future because of federal payments for participation in data sharing programs.

N=15

Q: How impactful (valuable) is each of the following types of data producers?

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Division On Centralization Persists for HEOR

HEOR leaders split evenly on the question of whether analytics was centralized. Across functions,

the industry is still figuring out what Big Data is, who executes it, and where it lives.

N=15

Q: Do you have a centralized/ dedicated group of individuals to support Big Data projects?

Yes 50%

No 50%

Dedicated Big Data Team (HEOR)

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0%

10%

20%

30%

40%

50%

60%

70%

80%

North America EU Europe (nonEU) Asia

Big Data Capabilities and Governance by Region (HEOR)

Regions with Big Data capabilities Region where governance resides

HEOR Reports A 40% Governance Gap in North America

HEOR leaders say their Big Data governance is more likely to be based in the EU than North

America, but their capabilities are more often in western hemisphere.

N=15

Q: Please indicate the regions below where your organization has Big Data capabilities, and where Big Data

governance resides.

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Rules about what analysis commercial functions can perform using BigData

Rules about what analysis medical functions can perform with Big Data

Rules on Big Data insights-sharing between commercial and medical

Rules governing disclosure of findings to public

Rules on proactive vs. reactive use of insights from Big Data

Rules on disclosure from regulatory perspective

Rules on publishing

Policies establishing clear ownership for various data types across the company’s information silos

Policies and procedures for accessing data (e.g., who can see what)

Policies governing protecting identification/ de-identification of patientlevel data

Policies governing clear ownership of IP generated through apartnership

Policies regarding review/ approval of research protocols

Prevalence of Data Governance Policies (HEOR)

HEOR: Majority have Range of Data Governance Policies

HEOR leaders reported relatively similar policy frequencies to those reported by medical leaders.

N=15

Q: Which of the following policies and procedures are in place at your company to govern Big Data activities?

Copyright © Best Practices, LLC 12

Best Practices, LLC is a research and consulting firm that conducts work

based on the simple yet profound principle that organizations can chart a

course to superior economic performance by studying the best business

practices, operating tactics, and winning strategies of world-class companies.

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Chapel Hill, NC 27517

www.best-in-class.com

About Best Practices, LLC