identifying and reducing variation in the supply...

Identifying and Reducing Variation in the Supply Chain

April 14, 2015

Yohan Vetteth, MBA

VP of Healthcare Data & Analytics

DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.

Kari Bignell

Manager, Data Architecture

Conflict of Interest

Yohan Vetteth, MBA Kari Bignell

Has no real or apparent conflicts of interest to report

© HIMSS 2015 2

Learning Objectives Discuss the multidisciplinary approach used by collaborative care teams to implement an analytics platform that helps ask better questions to facilitate clinical and financial improvements

Evaluate the advantages of an adaptive data warehousing approach to build applications for clinical and business analytics

Discuss how the deployment of the Supply Chain

Discovery Application has the potential to improve

health outcomes for patients, cost savings, and

operational efficiency by reducing variation in care

3

An Introduction to the Benefits Realized for the Value of Health IT

http://www.himss.org/ValueSuite

4

Stanford Health Care

5

Stanford Health Care

v2014

v10

6

Clinical & Business Analytics

Stanford Health Care

Information Technology Services

2012 Established

5 Employees

2015 Current Day

35 Employees

Clinical & Business Analytics

Prioritized data-driven quality improvement initiatives

Apps designed for self-service discovery and metric tracking

Strong clinical and business context

Agile project development for evolving user needs

EDW

Reporting Analytics Advanced Analytics

7

Guiding Principles

Make information more accessible

Single source of truth

Secure data

Avoid waste

8

Iterative Multidisciplinary Approach

Evaluate outcomes measurements

Evaluate clinical relevance

Test improvement hypothesis

Modify as relevant

Standardize and

improve workflow

Deploy evidence-

based interventions

Define cohort criteria

Define measurement

metrics

Clinicians

Support

Services

9

Agile Approach

Time to

Market

Design

Data

Focus

Ad-Hoc

Need driven

No consistency

Fragmented

Not always

accurate

Most data

modeling

upfront

Traditional BI

Technology

driven

Multiphased

4-6yr start-up

period

Original

requirements

Adaptive Data

Warehouse

New

functionality

along the

journey

Flexible

ONLY relevant

data tables

aggregated

Clinical

outcomes

Established 2012

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Source Systems

Epic Lawson

Architecture

Enterprise

Data

Warehouse

Clinical & Functional

Data Marts

Clarity

Reporting

Metric & Discovery

Apps

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=

Analytics Journey

Multiple reporting

sources

Inconsistent data definitions

Fragmented

Lack of governance causes confusion

and loss of credibility

12

Analytics Journey

Avoid data staging

through extracts

Standardize technology

architecture

Build strong data

access and guidelines

Strong data governance

13

Data Literacy

Metric Apps have

specific business

needs and require

strong business or

clinical context to

enable using the app

Discovery Apps

empower the users

to learn about the

subject area with

little to no business

or clinical context

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Paradigm Shift to Accountable Care

FROM TO

Variation in care Evidence based standards of

care

Fee for service Pay for performance

Segmented care Coordinated care continuum

Sick care Well care

Vague and unmanageable

cost structures

Cost containment and

transparency

How do we make healthcare less expensive? The levers are ugly.

We can pay doctors and hospitals less; or we can get them to reduce waste.

Dr. Atul Gawande

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Hospital Supply Chain

Incentives to build more accountable care-focused

capabilities have given health systems good reason to

evaluate their total cost structure

Supply-side economics

Purchasing practices at hospitals and health systems

continue to evolve, with the supply chain continuing to be a

target for large non-labor cost savings

As hospital consolidation continues…creating consistency within the

supply chain across the continuum of care will become increasingly

influential to the bottom line

Supply expense growth outpacing all others

Supply costs are growing faster than wages or benefits, driven by the rampant

proliferation of expensive devices. Physician preference items (PPIs) now

account for 60% of med/surg spend, compared with 40% a decade ago. More

than half of orthopedic procedures now use implantable devices, as do more

than one-third of cardiac procedures

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Finding Value

Lawson

SUPPLY

Accuracy of par levels

Over processing

Poor pricing

Epic

DEMAND

Accuracy of preference cards

Wasted Items

Expedited demand

How much does our

procedure supply use

vary between surgeons?

How much are we

wasting?

How accurate are our

preference cards?

What is our average

spend for a procedure?

How often are

we running for

supplies during

surgery?

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Finding Value

EDW

SUPPLY + DEMAND

Lawson

SUPPLY

Epic

DEMAND

SUPPLY CHAIN

DISCOVERY APPLICATION

Variation Insight

Waste Reduction

Cost Awareness

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Approach to Improvement

Challenge:

Single and elective surgeries

Identify high cost &

unnecessary variation

Balance those with high cost

& unnecessary variation with

cultural readiness and

engagement to drive

outcomes and improve quality

Cohort:

Focus:

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Understanding Usage Variation C

oeff

icie

nt

of

Vari

ati

on

Mean Supply Cost (or Quantity)

Biggest

Opportunity

Low Cost

Low Variation

Metrics Influenced:

• Supply Expense per

Adjusted Patient Day

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Measuring Variation - Direct Cost

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2 x 2 representation of

the Procedures

performed illustrating

greatest opportunity

Scorecard trending of

Procedures ranked by

opportunity

Understanding Item Variation To

tal

Un

iqu

e I

tem

s U

sed

Biggest

Opportunity

Mean Unique Items Used • Number of Items (SKUs)

• Inventory Turns

• Number of Preference Cards

• Item Pricing

Metrics Influenced:

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Measuring Variation - Distinct Items

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Search for items to see

how many surgeons

are using an item and

when they used it last

Focus in on highest

variation by Item

Group Types

Pilot Project - ENT Department

?

Pilot Focus: Otolaryngology Department

Two concepts, one view

Iterative, Rapid Development Approach:

Goal:

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Surgery Basket

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Compare how many

of each item is used

and the different

types of items used

across surgeons for

a specific procedure

Implement Intervention

Utilize the discovery app to:

Identify improvement areas

Facilitate conversations

Pinpoint items for removal from

preference cards and item master

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Analyze Results

Use Lean processes to help:

Update and streamline the preference

card system

Establish a solid baseline to enable

improvement measurement

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Conclusions

Evaluate the advantages of an adaptive data

warehousing approach to build applications for

clinical and business analytics

• Driven by clinical outcomes and not by the “IT bling”

• Supports a lean culture of continuous improvement

that requires agile and flexible solutions where

requirements are constantly changing

• Highly scalable design provides faster results for

future needs

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Conclusions

Discuss the multidisciplinary approach used by

collaborative care teams to implement an analytics

platform that helps ask better questions to facilitate

clinical and financial improvements

• Embedding IT with the clinicians and support services

provides a holistic approach and prevents rework

• Spend more time understanding the problem – the real

problem – versus just filling the specs!

• CBA members are viewed as content experts in the

subject matter, not just IT

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Conclusions

Discuss how the deployment of the Supply Chain

Discovery Application has the potential to improve

health outcomes for patients, cost savings, and

operational efficiency by reducing variation in care

• Transparency around item usage for similar

procedures and the challenges preference items bring

• Providing a mechanism to facilitate the appropriate

dialogue around variation of items and usage

• Conversations driven by clinicians around what items

to use enables stronger engagement and cost

containment

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A Review of Benefits Realized for the Value of Health IT

http://www.himss.org/ValueSuite

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Questions

Yohan Vetteth, MBA

VP of Healthcare Data & Analytics

Kari Bignell

Manager, Data Architecture

32