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Data! Information !! ACTION !!! – RESULTS ???

Christopher Looby, FACHEVice President, Agile HealthcareGlenview, Il847-347-0088E-mail: clooby@agilehc.comWebsite: www. Agilehc.com

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NO longer --

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An Ultimate Challengeit is NO longer about doing More w/ Less

NOW you MUST do LESS w/ LESS

How do Healthcare Organizations / Providers BUILD $$$

Completely different way of operating required…

Capital required…

Building Cash & Cash reserves required…

Got -- Got Options

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Even taking into account Quantum Leaps

in performance in current approaches, ie

Benchmarking

Higher Performance

Achieved

Move Beyond More of The Same

Next Generation Approach

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Technology is shaping

organizational success

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When information is cheap,

attention becomes

expensive.

James Gleick,

The Information, a History, a Theory, a Flood

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Objectives

• Describe a robust Business Intelligence /Analytics (BI/A) capability and practice ( including the critical importance of information deployment and visualization ) that drives action, quality and efficiency in delivery of care and services;

• Suggest developments / adjustments / re-alignments for the organization that might be engaged to improve coordination and integration of organizational BI/Analytics efforts;

• Identify key organizational characteristics required to leverage BI/Analytics for dynamic decision-making that delivers --Results.

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Section 1

Big Data:

What’s the Big Deal?

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Big data• Term for a collection of large, complex data sets comprised of

structured and unstructured data elements

• The trend to larger data sets is due to

• More readily allow correlations to be found to "spot” business trends,

population issues, prevent diseases, etc.

• Beyond the BUZZZZZZZZZZZzz of faster more insightful analysis,

understanding of usage patterns and /or interests, the real-time

incorporation of data from sensors, RFID, etc.

-- decisions or actions that are… more targeted, precise,

instantaneous, simultaneous, synchronous enable better results!

separate smaller sets with the same total amount of data

the additional information derivable from analysis of a single large set of related data

vs

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Big dataFocus then, must be on DATA FLOWS rather than Stocks

Resulting are -----

• Data sets of such size and composition --- difficult to process

using on-hand database management tools, traditional data

processing applications and systems

• Challenges in

o Quality* & consistency innately possible in the data

sought

o in capture, curation, storage, search, sharing, transfer, in

capability

o in analysis, reporting, modeling output and visualization

* Quality in --

Accuracy / Completeness / Update / Status / Relevance / Consistency across data sources / Reliability /

Appropriate presentation / Accessibility

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Big data

• Handling the Data --

massive amounts it

• Data of all types structured

and unstructured

• Moving beyond

Warehouses to direct,

recurrent, continuous

access and interactive

capabilities

Big data sets & focus on work Flow means ---

New structures for

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Big dataBig data sets & focus on work Flow means ---

New structures for

• the ‘Social’ Organization

The working environment of connectivity for & between

data scientists / DB admin / business line leaders /

organization leadership / line operations decision making

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Big data• Shift in working with the data

o from traditional areas ( IT, Infromatics, Finance,

decision support, etc. ) to ‘production’ and core

operational / business functions

o towards data scientists and process developersrather than ‘analysts’

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Data Value

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From

BI & Decision Support to

“Analytics”

Section 2

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Info

rma

tion

Fo

resig

ht

Analytics Illuminate

Hin

ds

igh

t

Fields of Vision

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Why “Analytics”

Scientific management is moving from

a skill that creates competitive

advantage to an ante that gives a

company the right to play the game

Ian & Elizabeth Stephens Ten Trends to Watch in 2006, McKinsey Quarterly Jan 2006

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Has been focused on

querying, reporting and online

analytical processing (OLAP)

tools and techniques that can

answer the questions about

something related to:

– Quantities

– Frequencies

– Locations

– Classifications

– Combinations

Business Intelligence

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Analytics…

The science of analysis

The branch of logic dealing with analysis.

Simplifying Data to Amplify Meaning

Data Driven Decision Making

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Analytics

Refers to the skills,

technologies, applications and

practices for continuous

iterative exploration that

answers a set of questions

that answer more definitively

AND…

Move beyond

What is happened ( ing )

& Why

To answer ( provide guidance about )

What’s NEXT

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AnalyticsFields of Vision

What has been happening in my

business?

Are there patterns in my data? ( e.g. What

kind are they – daily,

weekly, seasonal? )

Do these patterns enable decision rules for better operational

control?

What volume picture do demand patterns paint for the future ?

( e.g. What resources are / available ? )

What probably resource fulfillment

level?

Given a probable demand pattern -What is possible ? ( e.g. What resources

are needed, when from

where ? ) What are the permutations

Awareness – Knowledge Action -- Prescription

1000

1100

1200

1300

1400

1500

1600

ED Visits: Semi-Monthly Demand ForecastPredictive Modeling vs. Trend Analysis

85% Service Level Forecast Trend

Business Intelligence Optimization / SimulationDescriptive Analytics Predictive Analytics

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What does…

Business Intelligence / Analytics

Work involve

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1) Reveal ACTIONABLEinformation on What happened

Why is this happening

What if these trends continue

What will happen next -prediction

What is the best that can happen

– (that is, optimize)

What actions are needed

Analytics Capability

2) for Decision Making that embodies

PrecisionConsistency Agility

Speed Low Cost

3) About Decisions that Matter !

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Decision Management Sophistication

Busi

ness

Impa

ct

Precision &Agility

Consistency / Speed ~ Cost

Awareness & Understanding

Enterprise Coordination

Poin

t /Fu

nctio

nal L

ift

Exte

nsiv

e ~

En

terp

rise-

wid

e&

Con

tinua

l Lift

• Rules Management Applications / Capability

• Predictive Analytics• Decision Models• Adaptive Control

• Integrated Decision Engines

• Comprehensive BI monitoring/ tracking & reporting

H

H

Poin

tCo

rrec

tion

‘Exception’Correction Speed

• Information reporting applications

Analytics CapabilityDecision Sophistication Path

Adapted from : The Deciding Factor p 80

25Adapted from : Smart (Enough) Systems p.15

IT Applications--

New Service Line-----

Patient Care Maps-----

Consultants-----

MD Credentialing-----

Market Segmentation

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BAR

Capital Investment

-----

Patient Care Model-----

Strategic Market Positioning

-----

Physician Alignment

Analytics Capability Decisions that Matter

MD’s

FMLA

Bed Assgn

Prevention activities

MEDs

Staffing

Agency

CareMgmt

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Analytics Capability Decision Information - Contextually Powerful

Considers --• What are the decisions I need to

make?• What do I need to make

decisions?• How are my decisions connected

to other people’s decisions?• What new models are required to

make better decisions?

Decision Management focus ondecisions / decision processes for greatest effectiveness.

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Engaging AnalyticsDecisions on what is Stored & Real-time

Connections for Decision GuidanceFully Informs --

Prod Ops

Fin Ops

Analytics

Mktg Ops

Processes

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Statistics

Estimation

Shape

Variation

Location

Probability

Correlation

Simple Regression

Deploy~~~

Operationalize

User InterfaceInferential

Business Intelligence ~ Analytics Practice

Investigation ~ Exploration

Observational Study

Business Understanding

DataUnderstanding

Data Preparation

Modeling

Evaluation

DeploymentOperationalize Data

Designed Experiment

Forecasting

Multiple Regression

Descriptive

Prescriptive Predictive

Experimental design

Link to Data Visualization

DecisionManagement

Analytic Applications – Tools Decision Guidance

Data Visualization

Dispersion / Distribution

Reporting

Descriptive

AlertsCounts Summaries

Numeracy

Functionality

Aesthetic Form

Engaging Analytics

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Analytics Key to Driving Value Achievement

HFMA’S Value Project Value in Health Care: Current State and Future Directions

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Engaging Analytics?Future State of Value

Strategy Options to Drive Value

HFMA’S Value Project Value in Health Care: Current State and Future Directions

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Statistics

Estimation

Shape

Variation

Location

Probability

Correlation

Simple Regression

Deploy~~~

Operationalize

User InterfaceInferential

Business Intelligence ~ Analytics Practice

Investigation ~ Exploration

Observational Study

Business Understanding

DataUnderstanding

Data Preparation

Modeling

Evaluation

DeploymentOperationalize Data

Designed Experiment

Forecasting

Multiple Regression

Descriptive

Prescriptive Predictive

Experimental design

Link to Data Visualization

DecisionManagement

Analytic Applications – Tools Decision Guidance

Data Visualization

Dispersion / Distribution

Reporting

Descriptive

AlertsCounts Summaries

Numeracy

Functionality

Aesthetic Form

Engaging Analytics

Cautions:Avoid Unnecessary • Reinventions• POC’s

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Statistics

Estimation

Shape

Variation

Location

Probability

Correlation

Simple Regression

Deploy~~~

Operationalize

User InterfaceInferential

Business Intelligence ~ Analytics Practice

Investigation ~ Exploration

Observational Study

Business Understanding

DataUnderstanding

Data Preparation

Modeling

Evaluation

DeploymentOperationalize Data

Designed Experiment

Forecasting

Multiple Regression

Descriptive

Prescriptive Predictive

Experimental design

Link to Data Visualization

DecisionManagement

Analytic Applications – Tools Decision Guidance

Data Visualization

Dispersion / Distribution

Reporting

Descriptive

AlertsCounts Summaries

Numeracy

Functionality

Aesthetic Form

Engaging Analytics

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Data Visualization Example

http://modernsurvivalblog.com/wp-content/uploads/2010/06/usa-population-density-map-3d.jpg

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Section 3

The Critical Connection !

Data

Strategy

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Strategy – Adding Value

Retain & Grow

Revenue

Establish

Barriers to Entry

Operational

Efficiency

Reduce Risk

Drive Insight &

Innovation

Improving the quality or accessibility of enterprise data or Big data processing is not an end in itself or a single point

Understanding how information can enable or

improve business processes and decisions at the

heart of achieving strategy.

Creating

Business

Value •Long term in nature

•Crosses multiple systems and business processes

Whitepaper -- www.newvantage.comNewVantage Point: Principles for a Successful Data Strategy, Paul Barth, Managing Partner

The aim is …

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Business Value* ! ! !It is all about …

DeliveringHigh-Value healthcare user experiences:

Care, Safety, Service and Outcomesappropriate to situation at hand

at the

Best Delivered Cost

*Quality

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The Big Picture on Leveraging Data to Create Business Value

Consider; create an approach for how

Business Value

. Data

People

Frontline tools

Analytics Strategy Areas

Coordinate & Leverage Components of BI/A Work Propelling Strategy Execution that Drives Business Value

Adapted from: Big Data: What’s Your Plan, McKinsey Quarterly, March 2013

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The Big PictureCreating Value

Business Value

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The Big Picture on Leveraging Data

Business Value

You have them orTBD as the Strategy

development unfolds over time

More than DATA

Governance

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Data driving business valueConsider 3 Core Components

Adapted from: Big Data: What’s Your Plan, McKinsey Quarterly, March 2013

Universal ID’s• Healthcare user

Demographics• Provider ID ( MD, NP,

PA, RPH, PT LCSW ) • Facility ID ( Hospital,

Clinic, SNF, etc. )

Treatment Data• Diagnosis• Procedures • Drugs, dosages,

medical aids, referrals, visits, LOS

Cost Data• Hospital Care• Primary Care• Specialty Care, • Rx

Predict hospitalization risk for individual patients

Patient risk score calculator; patient-workflow manager

Reduce spending on patients with chronic diseases

Measure cost and quality of treatment, adjusted for patient morbidity

Contract-evaluation tool; pay for performance models

Patient treatment monitor; physician alert tool

Outside-in-productivity-benchmarking tool for hospital staff

Monitor treatment of patients with chronic diseases and compare with medical guidelines

Reduced hospital budgets

More cost-efficient care

Reduced spending –eg. on unnecessary hospital stays

Compare hospital productivity with others, accounting for patient’s health & demographics

Analytic Models

Business Value

Decision Support tools

Interlinked data inputs =

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Section 4

Critical Cultural Characteristics to

Achieving Results !!

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The Big Picture on Leveraging Data

Business Value

TBDas the Strategy development unfolds over

time

A1

L F A2

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Analytic PracticeAssets // Capabilities Required

Data - Strategy & Specific use

A1nalytic Bearing – expectations for decisions based on data

Leadership – A3@ at all levels

Focus - What’s Important? Can’t do it all! - perform inventories

A2ptitude – Knowledge base and execution competence in

disciplines needed to Build Models, Consult, Mentor & Train, etc. [ disciplines – quantitative, business design, etc. ]

Reference - Analytics in the Workplace

✓

✓

✓

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Analytic PracticeAssets // Capabilities Required

A1nalytic Bearing – expectations for

– decisions based on data & analysis

– collaborative search for / action based on ‘One Truth’ – engaged @ all levels, all locations, all times

Leadership – @ at all levels

– A3 analytical / accountable / action orientated

– Model / Teach / Coach / Consultative / Collaborative

– Committed / Persistent / Builders / Developers / Explorers

Reference - Analytics in the Workplace

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Analytic Practiceptitude -- Starting Point….

What is needed

•Significant quantitative horsepower

•Significant consultative and change management

capability

•Significant Organizational Sponsorship

CautionsDon’t just refocus or recruit the Quality people

o Six & Lean -- complimentary yet different disciplines

o Similar / different quantitative tools & processes

New hiring? Maybe Not necessary [ classic make or buy ]

Might avoid hiring a ‘Quant’ [ classic make / lease / buy ]

A2

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The Big Picture on Leveraging Data

Business Value

TBDas the Strategy development unfolds over

time

A1

L F A2

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Reprise

Results are about:

Decision making

Considering the What’s & When’s of BIG DATA

Engaging a BI/Analytics Practice

Connecting Analytics work to Strategy in a way that drives Business Value

Taking an approach A1L F A2

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Christopher Looby, FACHEVice PresidentAgile HealthcareGlenview, Il847-347-0088E-mail: clooby@agilehc.comWebsite: www.agilehc.com

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Speaker Profile – Christopher Looby• Christopher has over 30 years experience in the healthcare industry - 25 years in administrative, general management, and

entrepreneur roles. His career started in manufacturing and sales of consumer goods and services.

• Currently in the midst of launching Agile Healthcare, with his business partners, Christopher is engaged in developing and

bringing to market a predictive modeling application for patient volume forecasting and resource optimization and daily

decision making – an ERP approach for healthcare operations planning & management. Breaking new ground in the

healthcare industry information / business intelligence / analytics space, the company’s aim is helping healthcare provider

organizations improve performance related to the operational management discipline’s triple constraint question (

simultaneously maintaining or improving capacity / quality / cost ), as a key means to address healthcare industry Value

Based purchasing initiatives.

• Over the last 5 years significant contributions to healthcare industry change have been made facilitating national senior

management seminars on analytics and business intelligence for ACHE and HFMA. Additionally, Christopher has authored

the HFMA Certified Specialist Business Intelligence course. Initial work in using analytics as the basis for solving business /

customer issues is related to his assistance with epidemiologic injury control studies, 30 years ago. His training in and use

of Total Quality Management / 6σ / Lean to drives market leading performance began in the early 90’s.

• Christopher’s healthcare roles have covered - day to day clinical services operations leadership – having full business unit

P&L responsibility in outpatient acute care, behavioral health, physical and cardiac rehabilitation, imaging services delivery

areas, among others within a hospital organization environment. Other areas of clinical operations expertise include -

population health and wellness, occupational health, workers compensation and employee safety. Experience also

encompasses - business development in the above areas and senior services, skilled nursing/complex post acute care

services. In all capacities - Chris has lead direct reports across a variety of non-clinical and clinical disciplines.

• An appointment as adjunct professor at the Lake Forest Graduate School of Management { LFGSM), as an MBA program

faculty member has been enjoyed for nearly 15 years. Christopher has taught over 70 course terms since 2001. He is

currently appointed to teach MBA core courses -- Operations Management and Leading Change Management, and the

school’s Healthcare Specialization Capstone course ( which he authored ). He also authored and teaches Management

Skills for Pharmacy Students, for PharmD candidates at Rosalind Franklin University of Medicine & Science. For over 5

years at LFGSM, Christopher has provided lectures, seminars and consulting for the Corporate Learning Solutions division.

Prior teaching with LFGSM, that Chris taught Healthcare Systems and Healthcare Delivery Strategy at National Louis

University.

• Among volunteer activities, Christopher has contributed to CHEF ( ACHE’s largest independent chapter ) with 5 years of

leadership as a board member including Chapter President.