Big Data/Real World Analytics can be the catalyst for dramatic change in U.S. healthcare. Big Data informs many commercial, medical and HEOR decisions. On an average, Pharma Companies use 35-50% of analytics techniques to support commercial, medical and HEOR decisions. Data acquisition and infrastructure represent a majority of spending for Big Data. Data management cost-sharing
across functions could drive savings & boost effectiveness. Howwever, the pharmaceutical industry is still in the early stages of utilizing large data sets from different sources to inform critical aspects of medical, commercial and HEOR operations.
Best Practices, LLC published this study by engaging 22 leaders from 18 pharmaceutical companies through a benchmarking survey. This study aims to produce reliable industry metrics on current and future trends for Big Data utilization across medical, commercial and HEOR groups. A majority of study participants think partnerships with health plans/payers and data aggregators have a high impact on Big Data projects and programs. The respondents said about 20% of data is sourced from partnerships.
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Big Data Trends & Utilization Across Medical, Commercial & HEOR Functions
1. Big Data in Pharma:
Current & Future Trends for Big Data Utilization
Across Medical, Commercial and HEOR Functions
Best Practices, LLC
Strategic Benchmarking Research Study with Segmented
Responses by Medical, Commercial and HEOR Functions
2. 2
Table of Contents
I. Executive Summary pp. 4-12
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 / Sources by Medical, Commercial and HEOR Segments pp. 21-36
IV. Data Producers, Dissemination & Requestors by Medical, Commercial
and HEOR Segments pp. 37-49
V. Centralization pp. 50-56
VI. Governance and Leadership pp. 57-87
3. Best Practices, LLC, conducted a customized study – with responses segmented by medical,
commercial and HEOR functions - to better understand the growing influence of Big Data in the
biopharmaceutical sector and how it impacts medical, HEOR, and commercial operations in the U.S.
Best Practices, LLC engaged 22 leaders
from 18 pharmaceutical companies
through a benchmarking survey. There
were multiple responses from 3
companies but they each represent a
different functional area (medical,
commercial, or HEOR).
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
4. Benchmark Class:
Eighteen Companies Participated in the Benchmark Study
22 analytics, marketing and HEOR leaders from 18 different companies participated in this study.
Participants were recruited because of their presumed investment in Big Data analytics. Three companies
had multiple responses - each representing a different functional area (medical, commercial, or HEOR).
9. 9
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Point of Sale (POS) Claims Electronic Health
Records (EHR) /
Electronic Medical
Records (EMR) /
HIE (Health
Information
Exchanges)
ePrescription /
pharmacy fulfillment
Wholesalers /
Group Purchasing
Organizations
(GPOs)
Government (e.g.,
cost data)
Credit card
Impact of Transactional Data (Commercial)
Highly impactful Somewhat impactful Not impactful Not used
While a majority of commercial participants rated claims and Electronic Medical Records (EMR) as
the most valuable types of transactional data for Big Data studies, 50 % also cited point of sale as
highly impactful or valuable.
N=12
Q: How impactful (or valuable) has each of the following types of transactional data sources proven to be?
Transactional Data: Commercial Rates Claims, EMR Most Valuable
10. 10
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Impact of Online Data (HEOR)
Highly impactful Somewhat impactful Not impactful Not used
Online Data: HEOR Finds Online Information of Limited Impact
Participants in HEOR roles – like their peers in Medical – didn’t give online data high impact ratings
for using in Big Data studies.
N=15
Q: How impactful (or valuable) has each of the following types of online data sources proven to be?
11. 11
Medical Leaders Describe Analytics As Centralized
Medical leaders were the most likely to describe their analytics efforts as having centralized or
dedicated personnel.
N=12
Q: Do you have a centralized/ dedicated group of individuals to support Big Data projects?
Yes
58%
No
42%
Dedicated Big Data Team (Medical)
12. 12
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Partnership Value (Medical)
Highly impactful Somewhat impactful Not impactful Not used
Medical: Health Plans/Payers, Aggregators and Health
Systems Seen as Highly Impactful Partners
Medical leaders were most likely to rate partnerships as highly valuable across all varieties of
collaborations. Most popular were collaborations with payers and data aggregators.
N=12
Q: Which of the following partners are most impactful/ valuable on Big Data programs and projects?
13. 13
No Obvious Trends Between Functions
Certain functions do not clearly outpace the others.
Q: Types of Big Data projects currently used to support these medical decisions:
N=10,9,12
0%
10%
20%
30%
40%
50%
60%
70%
Targets for Drug Development Other Drug Development Decisions
% of Surveyed Techniques Employed in Decisions
Medical Commercial HEOR