Making Healthcare Personal: Driving Better …...1. Participants will understand why a...

Making Healthcare Personal: Driving Better Outcomes, Care and Patient Experience

Mark Wong, Senior Director, Clinical Programs

Chris Lehmuth, Senior Director, Enterprise Data Science

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© 2019 Express Scripts. All Rights Reserved.

Presenter’s are employed by Express Scripts

Disclosure will be made when a product is

discussed for an unapproved use.

This continuing education activity is managed

and accredited by AffinityCE in collaboration

with AMSUS. AffinityCE and AMSUS staff as

well as Planners and Reviewers, have no

relevant financial or non-financial interests to

disclose.

Commercial Support was not received for this

activity

Disclosure statement

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Learning Objectives

1. Participants will understand why a performance-based clinical outcomes model

focused on delivering personalized clinical care is needed in the health care

system.

2. Participants will be introduced to innovative approaches around data integration

that support a new clinical management model that delivers guaranteed clinical

outcomes and return on investment.

3. Participants will learn this new clinical management model fosters coordination

of care and creates a better healthcare experience for the patient.

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4

“FALL IN LOVE WITH THE PROBLEM, NOT THE SOLUTION.”

- MARTY CAGAN, INSPIRED

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5

OF TOTAL HEALTHCARE

SPENDING GOES TO

UNNECESSARY,

INEFFECTIVE,

OVERPRICED, AND

WASTEFUL SERVICES*

%

*Lyu H, Xu T, Brotman D, et al. Overtreatment in the United States. PLoS One. 2017;12(9):e0181970. Published 2017 Sep 6. doi:10.1371/journal.pone.0181970

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Improving clinical outcomes has stalled

Journal of the American Medical Association Study*

1 in 4

adults with

diabetes

was not

diagnosed

Of those

diagnosed,

nearly 1 in 3

was not

receiving

appropriate

care

Fewer than

1 in 4

achieved

clinical

goals

*Pooyan Kazemian, PhD; Fatma M. Shebl, MD, PhD; et al. Evaluation of the Cascade of Diabetes Care in the United States,

2005-2016. JAMA Intern Med. doi:10.1001/jamainternmed.2019.2396 Published online August 12, 2019.

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*2018 Kaiser Family Foundation Employer Health Benefits Survey

OF LARGE EMPLOYERS INVESTED IN HEALTH AND WELLNESS PROGRAMS IN 2018

%

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Reviews are mixed on Health and Wellness Programs

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Personalization impacts engagement

wardrobe

kits

social

media

feed

movie

promptsonline

shopping

music

feed

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MAKING THE DENTIST OFFICE PERSONALIZED

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Using insights to build a better system

BETTER VALUE

BETTER HEALTH

BETTER SERVICE

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“BIG DATA” Defined

THE TYPES

OF DATA

Data is sourced from

over 3,000 external

providers and 400

internal apps

THE CHANGES

WITHIN DATA

Competencies to

integrate and

enhance ever

changing data

THE AMOUNT

OF DATA

20 petabytes;

placed into

17 data domains,

100+ sub-domains

THE SPEED TO

RECEIVE DATA

35MM daily claims are

received and stored

within seconds of

a pharmacy visit

THE QUALITY

OF DATA

Data governance

applied to produce

clean data feeds and

actionable insights

Big data is further defined by the following attributes:

Datasets that are too large, complex or dynamic forconventional tools to capture, store, manage and analyze

VolumeVariabilityVariety VeracityVelocity

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Data Science: From Analytics to Action

Data are just summaries of thousands of stories —

tell a few of those stories to help make the data meaningful.

– Chip & Dan Heath, authors of “Made to Stick: Why Some Ideas Survive and Others Die”

“ ”

USEFUL

ESI TURNS DATA INTO INSIGHTS BY MAKING IT …

Timely Relevant Accurate Complete Actionable

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ESI Enterprise Data Science Competencies

gradient

solid color

AI (research)Deep

LearningMachineLearning

TextMining / NLP

AnomalyDetection

Optimization GISDesign of

Experiments

Enterprise Data Science Services/Enablement

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PROSPECTIVE / REAL-TIME

Identify risk before the first fill and throughout treatment, then proactively engage

Track changes in patient-level risk

over time

Adjust intensity of engagement as a

patient’s risk changes

Identify the type of interventions most

likely to elicit a positive response

Effectively target patients based on their

behavior profile

Appling data science to healthcare

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Interventions are often happening too late

TIME

RIS

K EARLY INTERVENTION= healthier & safer patients

while reducing waste

CURRENT

intervention timeframe

RECOMMENDED

intervention timeframe

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COMPREHENSIVE HEALTH RISK MANAGEMENT

Building the right insights to drive change

Gap In care Predictive Insights

Therapy Specific Engagement

Channel Engagement models

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L IVE CALL CHANNEL ENGAGEMENT

State or Province

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L IVE CALL CHANNEL ENGAGEMENT

Prescriber AMA School Location Code

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A New Model

Integrated Hub Personalized Interventions

STEP 1 :

Multi-source data

integration

STEP 3 :

Recommendation

Engine

STEP 4 :

Outcomes-focused

Personalization

STEP 2 :

Insights

Engine

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Dynamic Personalization

Diabetes and Hypertension Remote

Monitoring

Provider detailer

Quality Pharmacy Networks

Physician EMR Communications

Personalized Member Communications

TRC

Pharmacist

Care Coordination

Health eating

support

Proactively selecting the right set of evolving engagements for each person’s individual needs…

recalculating as we go for the greatest outcomes.

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Holistic population insights + personal touch

Clinical performance viewed on demand for total

and sub-populations through Care Insights Hub

• Access to all clinical measures and opportunities

• Recommended action plan to meet clinical goals

• Visibility to interventions and clinical/financial

outcomes

• Action plans can be generated based on member

priority and desired clinical focus

Screenshot of Care Insights Hub

Complementing our machine learning recommendations with a personal touch. Our Population Health

Managers are clinicians trained on data analysis—providing daily monitoring and evaluation based on your

goals, using the Care Insights Hub’s rich information at both patient and population levels.

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Diabetes Health Risk, Avoided INTERVENTIONCASE

STUDY

59 y/o female

Has history of diabetes, with high A1c levels (11.3 vs. goal <7.0), nonadherence to metformin and missing

a recommended statin — left untreated, at significant risk for eye, kidney and nerve complications.

BLOOD SUGAR

CONTROL

Elevated A1c levels

11.3

Drastically reduced A1c

levels

6.2

• Statin not prescribed, omission gap

• Interested in lifestyle changes, but not sure

where to start

• Statin prescribed, gap closed

• Dietitian referral to assist with

lifestyle changes

MEDICATION

ADHERENCE

• Doesn’t want to take insulin• Nonadherentto metformin

73%

• Discussed ways to remember to take meds

with TRC pharmacist• Adherent to metformin

99%

PHYSICIAN

VISIBILITY

Several electronic messaging attempts; no change in therapy

• Connected and coordinated

• Academic Detailer discussed statin

omission with provider

CARE

COORDINATION

Information not shared across

medical/pharmacy care team

Provider, case manager, TRC Pharmacist,

Academic detailer and PHM engaged

High risk of complications

• A1c level controlled with ADA diet and exercise• Insulin discontinued

• Adherent to recommended statin

• Significant reduction in diabetes complications

$7.5Kcost savings

BLOOD SUGAR

CONTROL

GAPS IN

CAREMEDICATION

ADHERENCE

PHYSICIAN

VISIBILITY

CARE

COORDINATION

OVERALL

HEALTHSAVINGS

2018

2019

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Final Takeaways

1. Leverage personalized strategies – using actionable data

2. Maximize your clinical outcomes through comprehensive care

coordination

3. Hold health care service organizations (including digital vendors)

accountable for delivering clinical and financial value

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How to Earn CE

If you would like to earn continuing education credit for this activity, please visit:

http://amsus.cds.pesgce.com.

Hurry, CE Certificates will only be available for 30 Days after this event!

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