Transcript Slide 1

Big Data in the Pharmacy Benefit
Douglas Mager, MA. Director of Research
HIMSS Midwest Gateway Chapter Speaking Event
March 11th, 2015
Internal Information
© 2014 Express Scripts Holding Company. All Rights Reserved.
1
Express Scripts Overview
National Leader in
Pharmacy Benefits
• 1.4 billion prescriptions per year
• 85 million members
• 3,500 clients
• 30,000 employees
Respected and Recognized
• Business model aligned with
our clients’
• Scientific research to develop
meaningful prescription-drug
solutions
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2
The Role of a Pharmacy Benefit Manager
Member
Pharmacy
PBM
Take prescription and
ID card to pharmacy
Submit online claim
to PBM
Verify eligibility
Determine benefit
Drug utilization review
Receive
prescription drug
Fill prescription
Collect copayment
Send online response
Store information
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3
What is ‘Big Data’ in the Pharmacy Benefit?
We actively manage a large volume of administrative data, resulting
from the daily operations with its clients and patients that it serves.
VO LU M E
VA R I E T Y
V E LO C I T Y
More than 150
data stores
Various data sets
(structured, unstructured)
Streams from applications
and devices
65,000 pharmacies
Claims
1 million prescribers
Web Data
Per second:
100 claims
85 million members
Fax/Rx Images
1.4 billion Rx per year
Call center records
Per day:
500,000 calls
3.6 million pharmacy events
1.7 million member contacts
We manage 20+ PETABYTES of data across our data ecosystem
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4
Wiring Healthcare: ePrescribing
ePrescribing has become the standard
channel for physicians to route
prescriptions to pharmacies
• Over 66% of home delivery new
prescriptions are ePrescribed
• Over 50% of retail prescriptions are
ePrescribed
• Over 2M eligibility requests daily — eligibility
provides formulary data and identifies home
delivery pharmacy
74%
of U.S.
physicians
actively
ePrescribe
• Over 1M medication history requests daily
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5
The Two Most Important Things to Know
About Administrative Data
The primary purpose of a claim is payment
From the provider’s and payor’s perspective,
if a claim is good enough to make an
accurate payment, IT IS GOOD ENOUGH.
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6
Advantages of Administrative Data
S
Vast Amounts
of Information
Relatively
Inexpensive
Longitudinal
Look
Observations/records
Data is captured
as part of the
adjudication process
Typically spans
multiple years
Data fields (over 300
fields captured on each
pharmacy claim alone)
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Limitations of Administrative Data
Continuity
Population Biases
Difficult to track members
or clients longitudinally if
they do not remain with ESI
“Sample of convenience”
data from commercially
insured members
Not Always
Generalizable
Cannot Measure All
External Factors
Coverage may vary by
region or demographically
depending of client mix
Other, unmeasured factors
influencing utilization and
program acceptance
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8
What Can We Do With
Administrative Data?
• Outcomes research
• Research on trends and patterns of
medication cost and utilization
• Drug Trend Report
• Forecast cost and utilization based
on market shifts and patent expirations
• Predictive modeling
• Focus resources based on predicted
future behavior
• Combine with outside data (often via
collaboration with other institutions)
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9
Example: Predictive Modeling (PM) and Medication
Adherence
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1
What is predictive modeling
2
Why is medication adherence important
3
Benefits of PM in medication adherence
10
Predictive Model Life Cycle
3
4
Develop
Model
Set Campaign
Goals
Pass
2
8
7
Gather
and
Explore
Data
Reestimate
Model
Monitor
Model
Performance
Execute
Campaign
6
1
Set
Modeling
Goals
5
Marginal
Analyze
Campaign
Success
Fail
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11
Predictive Modeling in Action
Identification:
• Members most likely to be
non-adherent on medication
• Multiple therapy classes
• New starts and continuing utilizers
Investigation:
• Factors most predictive of future nonadherence
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12
Benefits of Predictive Modeling in Medication Adherence
New Starts
Compliance Self-Correction By
Predicted Terciles
• Enables intervention before
problems become well established.
• Mitigates the impact of selfcorrection and regression to the
mean
All Users
• Stop driving by the rearview mirror
alone
• What really matters is what’s ahead
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90%
Population Distribution
Continuing Utilizers
100%
80%
70%
60%
Post
Period
Compliance
50%
>80%
40%
50-80%
30%
<50%
20%
10%
0%
Bottom Third Middle Third
Top Third
Predicted Compliance
Pre-Period Compliance < 80% For All Members Analyzed
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Why Is Medication Adherence Important?
Each Year
$308B Annual Direct Costs1
23M ER Visits2
125K Deaths3
1.
2.
3.
4.
75
%
Exhibit some
form of
medication
nonadherence4.
Express Scripts 2010 Drug Trend Report
New England Healthcare Institute: Thinking Outside the Pillbox, August 2009
R McCarthy “The Price You Pay For The Drug Not Taken”, Bus Health 1998
National Community Pharmacists Association: “Take As Directed: A Prescription Not Followed” December 15, 2006
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14
Predictive Modeling in Action
Who will miss their medication?
Alex
Milagro
Andrea
Chris
Marcus
Simone
Victor
Yvette
Brendan
Patricia
Prescription
Fill
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15
Predictive Modeling in Action
Who will miss their medication?
We have to wait to find out.
Alex
Milagro
Andrea
Chris
Marcus
Simone
Victor
Yvette
Brendan
Patricia
Scheduled
Fill
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16
Predictive Modeling in Action
Who will miss their medication?
We have to wait until a refill to find out.
Alex
Milagro
Andrea
Chris
Marcus
Simone
Victor
Yvette
Brendan
Patricia
Scheduled
Fill
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17
Predictive Modeling in Action
Who will miss their medication?
Interventions are reactive.
Alex
Milagro
Andrea
Chris
Missed
Scheduled
Refill
Marcus
Simone
Victor
Yvette
Brendan
Patricia
Scheduled
Fill
Intervention
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18
Predictive Modeling in Action
Who will miss their medication?
We need to intervene earlier. But how?
Alex
Milagro
Andrea
Chris
Marcus
Simone
Victor
Yvette
Brendan
Patricia
?
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Scheduled
Refill
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Predictive Modeling in Action
How do we predict individual behavior?
Crunching the data gives us insight into each member.
Express Scripts
Adherence
IndexSM
+
Simone
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+
+
+
+
=
43
• Over 400
total factors
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Predictive Modeling in Action
How do we apply it?
Every script gets an index that identifies at risk members.
Express Scripts
Adherence IndexSM
32
38
Chris
Brendan
39
Andrea
43
Simone
67
Marcus
73
Victor
76
Patricia
82
Alex
84
Yvette
87
Milagro
Scheduled
Refill
Prescription
Fill
(Predicted Result)
Interventions
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21
Predictive Modeling in Action
How do we apply it?
Early intervention improves results..
Express Scripts
Adherence IndexSM
32
38
Chris
Brendan
39
Andrea
43
Simone
67
Marcus
73
Victor
76
Patricia
82
Alex
84
Yvette
87
Milagro
Scheduled
Refill
Prescription
Fill
Interventions
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Summary – Big Data at Express-Scripts
• Vast amounts of data available
• Gain insights into opportunities to drive out waste
• Understand the drivers of trend and utilization
• Help clients maintain the pharmacy benefit for their
employees/members
• Drive down prescription cost for clients and patients
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23
Questions?
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