Drive Healthcare Transformation with a Strategic Analytics Framework and Implementation Plan

Drive Healthcare Transformation with a
Strategic Analytics Framework and
Implementation Plan
1

Contents Covered in This Session
• Chpt 3 of your textbook
• Templates, Artifacts and Samples provided in the Course Content of
Blackboard
• Sample Analytics Interview Questions
• Sample Analytics Use Cases
• BI Analytics Strategy Plan Presentation
• BI Analytics Strategy Plan and Roadmap
• Business Justification Document Sample
• Data Assessment Templates
• Chpts 1 – 3 of Healthcare Data Warehouses provided in the
Reference Books Section of the Course Content
2HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang

Problem Domain
• Healthcare organizations (HCOs) are facing increasing
quality, financial, and regulatory pressures, and must
transform to achieve sustainability.
• The three fundamental information needs of healthcare
improvement are to identify:
• What quality/performance/safety aspects need to improve?
• What processes must change to result in improvement?
• What change (if any) has occurred?
HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang 3

4
What is an Analytics Strategy?
• A strategy that ensures analytics development and
capabilities are in alignment with enterprise quality and
performance goals
 Avoids the “all dashboard, no improvement” syndrome
• Helps to achieve optimal use of analytics
 Can mean the difference between a “collection of reports”
versus a high-value information resource
• Analytics Strategy should align with other relevant
strategies including:
 Business Intelligence (BI) strategy
 Information Technology (IT) strategy
 Quality Improvement (QI) strategy

Building and Executing a Successful Framework
• Understand requirements
 Review strategy components with stakeholders
 Identify how analytics are currently used
 Determine what capabilities will be needed (short & long term)
• Identify gaps and mitigate risks
 List known/potential gaps and their mitigation approaches
 Prioritize gap mitigation based on impact, effort, & cost
• Execute plan
 Assign task owners and target implementation deadlines
 Monitor progress and apply mid-course corrections

Analytics
System
Business
& Quality
Context
Stakeholders
& Users
Processes
& Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
HCAD 6635 Health Information Analytics 6
Strategic Analytics System Framework
An effective analytics system is more than simply a reporting/BI tool
layered on top of a data source.
Copyright © 2016 Frank F. Wang 6

Strategic Planning and Development
7
FiltersCurrent State
Details
Assessment and Strategy Development
Business
Drivers
Technical
Landscape
Executive
Summary
Data readiness
assessment
Information Architecture
Organization Architecture
Project Management
Analysis and documentationInformation gathering
Current
State
Summary
Gaps
Summary
Planning
Documents
Strawman
Vision
Program
Analysis and
Planning
Analytical
Processes
Needs
Assessment
Technical Architecture
Functional Requirements
Best Practices
Relevant Client
Experiences
Applicable Industry
Trends
HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang

Business & Quality Context
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Copyright © 2016 Frank F. Wang

9
Business Context: Enterprise Goals, Objectives, and Strategy
• What are the Organizational Goals and Objectives?
 Are what the organization is aiming to achieve.
 Define the performance and quality targets of the organization
 Answer “why” the organization is (or should be) engaging in
certain activities
• What are the Organizational Strategies?
 Outlines how the organization expects to achieve its goals
• Analytics must provide insight into past, current, and
anticipated future progress towards meeting the
enterprise goals.

Analytics Stack
Presentation
Visualization Dashboards Reports
Alerts Mobile Geospatial
Quality & Performance Management
Processes Indicators Targets
Improvement strategy Evaluation strategy
Analytics
Tools Techniques Team
Stakeholders Requirements
Deployment Management
Data
Quality Management Integration
Infrastructure Storage
Business Context
Objectives Goals Voice of patient
Focus on the Business
An abstracted Business Intelligence and Analytics stack helps maintain focus
on key components of analytics required to address business and clinical goals.
10

Use Business Intelligence, Data Warehousing and Analytics to
achieve the goals:
• Drive Member Value
• Drive Patient Volume and Revenue Growth
• Drive Clinical Excellence
Services will be consistent with the
organization’s vision and mission and will:
• Drive a growing base of patients
and revenues for members
• Build an environment that
facilitates members’ future success
• Continuously reinforce a “value”
message to the members
• Complement corporate values,
goals, and long term objectives of
our members
Aligning Business Objectives and Analytics Objectives (Example)
11

Key Business Objectives & Goals – Goal Alignment
Strategic Objectives Business Intelligence and Helps By…
Increase Operational
Efficiencies
• Minimizing FTE growth while increasing volume of
referrals and cases
−Simplified data access to all data
−Automation of processes (Reforecasting)
• Increases Margin & Contribution
−Enable larger case loads
Improve Predictive Models • Improve Pricing/Budgeting of individual contracts
−Improved Risk identification and mitigation
Scale an Increase in Business
Volume
• Increase prospects, referrals & revenues
−Quantitative/Benchmark analyses depicting value
• Identify/Support new products
−Informatics Products
−Identify market niches and opportunities
Increase Market Penetration
& Open Up New Markets
Perform Clinical Data Analysis
& Studies
• Improve clinical efficiency
−Benchmark analysis (clinical and financial)
−Identify Risks and mitigations
Improve Customer
Satisfaction
• Improved response to customer inquiries
• Backlash from large “winner” contracts
12
• Use Business Intelligence/Analytics to help us…
WhyBI?

Adding SWOT to Strategy
• Traditional “SWOT” analysis can be layered onto the components
(and sub-components) of analytics strategy.
13
Strengths Weaknesses Opportunities Threats
Business &
Quality Context
Stakeholders &
Users
Data & Processes
Tools &
Techniques
Team & Training
Technology &
Infrastructure

SWOT Analysis Brainstorming Example
Services will be Consequence
Services will be • Unprepared to determine impact and prepare for
consumer driven healthcare
• Incapable of efficiently managing “pay for performance”
on a widespread basis
• Unable to respond to bundled payment and ACO models
Services will be • Not leveraging the clinical value of our physician/patient
relationships
• More time shepparding care data than analyzing it
Services will be • No proactive monitoring and remediation of contract and
payment terms
• Limited understanding of network-wide customer base
and how to get the most of our relationships
Services will be • Difficult to:
– Determine the efficacy of programs and services
– Forecast and plan based historical performance and trends

SWOT Analysis Brainstorming Example
• Organization is seen as the connective tissue between
in/outpatient patient experience and the hospitals and medical
staffs. Organization is best positioned to provide an integrated
view of:
Patients
Payers
Providers
Product & Service
Employer
 Migrate from reactive and ad-hoc to proactive and systematic
 Less data, more information and furthermore, predictive and
prescriptive analytics
 Intuitive access (ease of use and quality)
 Informed decision making (data correlation and timeliness)
 Use information to do more with less (or same)
 Protect physician and patient privacy
 Safeguard intellectual property
 Do unto Payers as they do unto us
 Payment
 Care Delivery
 Outcomes

Aligning Strategic and Tactical Quality Objectives
• Analytics is the “glue” which ties strategic objectives and tactical
activities together.
• Objectives of unit- or department-based improvement initiatives
should, where possible, align with the quality objectives of the
organization as a whole.
• Prevents misdirected/wasted activity
• Enables the HCO to monitor progress and evaluate outcomes
Strategic Level Strategic Objectives
Analytics Metrics Indicators Targets
Tactical Level Tactical Objectives
A reminder that the customer
(“the patient”) is the ultimate
reason for the work we’re doing.
16
Voice of the customer

Business Goals: Strategic and Tactic
Strategic Objectives Tactic Goals
Increase Operational Efficiencies • Maintain sub-linear scalability in Operations while
increasing volume of referrals and cases
• Increase Margin & Contribution
Improve Predictive Models • Improve Pricing/Budgeting of individual contracts
through the use of existing cases informatics
Scale an Increase in Business
Volume
• Increase revenues by four-fold within 48 months
• Deploy new products/services through acquisition
and new product development
Increase Penetration of Existing
Market & Open Up New Markets
Perform Clinical Data Analysis &
Studies
• Improve clinical efficiency through the ability to
use improved BI, (i.e., use of trends, benchmarks,
and predictive analysis techniques to identify
opportunities, plan interventions and measure
outcome results)
Improve Customer Satisfaction • Through all of the above
17Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics

18
Quality Strategy / Improvement Approach
• Quality Strategy outlines the steps and approach the organization is
going to be taking to achieve quality goals/objectives.
• Which QI approaches are utilized (i.e., Lean, Six Sigma) will impact what
data is required, how it is analyzed, and how it is communicated.
• Analytics development teams and quality improvement teams must
work closely together
 to ensure that information requirements of users and the delivery by via
analytics are in sync.
• When executing the analytics strategy, always ask “are we taking
appropriate and necessary steps towards achieving the
organization’s quality and performance goals?”

HCAD 6635 Health Information Analytics
Stakeholders & Users
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure

Stakeholder Analysis
• A stakeholder is a person (or group of persons) that are:
 impacted by, users of, or otherwise have a concern (or interest
in) the development and deployment of analytical solutions
throughout the healthcare organization.
• When developing an analytics strategy, it is important to
understand what each of the likely analytics stakeholders
will require, and develop approaches to ensure they are
getting what they need.

HCO Stakeholder Types
21
Stakeholder Description
Patient The person whose health an healthcare experience
we’re trying to improve with the use of analytics
Sponsor The person who supports and provides financial
resources for the development and implementation
of the analytics infrastructure
Influencer A person who may not be directly involved in the
development or use of analytics, but who holders
considerable influence over support of analytics
initiatives.
Customer / User A person in the HCO who accesses analytical tools, or
uses the output of analytical tools, to support
decision making and to drive action.

Source: HealthIT Analytics, "EHRs Don't Do Enough for Care Coordination, Docs Say," Jennifer Bresnick, January
19, 2015 http://healthitanalytics.com/news/ehrs-dont-do-enough-for-care-coordination-docs-say/
83% of physicians are
frustrated by EHR usability,
interoperability and
integration.
If We Do Not Listen to Our Stakeholders

Source: Accenture, "2015 Healthcare IT check-up shows progress (and some pain)--Infographic"
https://www.accenture.com/us-en/insight-2015-healthcare-it-check-up-shows-progress-pain-infographic.aspx
Interoperability: 51% of US doctors in
2015 routinely access clinical data of
a patient who has been seen by a
different health organization, slightly
up from 45% in 2012.
Then We Can Not Expect Higher Adoption Rate

Barriers to Physician Engagement
A McKinsey report highlights four key
concerns and barriers:
• Physicians feel overwhelmed and ill-equipped to
effect change. They lack an understanding of
their part in healthcare waste and inefficiency.
• Hospitals and payers believe that employing
physicians is the primary means of securing
alignment.
• Organizations have the misconception that
compensation is one of the most important
drivers for physicians.
• Physicians have a poor understanding of the
risk-based payment model along with being
risk-averse.

Steps to Gain Physician Buy-in
The Institute for Healthcare Improvement put
together a framework of six elements to
encourage physician buy-in for a shared
quality agenda:
• Discover a common purpose
• Adopt an engaging style and talk about rewards
• Reframe values and beliefs
• Segment the engagement plan and provide
education
• Use “engaging” improvement methods
• Show courage and provide backup

Who We Spoke To (Stakeholder Interview)
Area Resources
Account Management ABC
Clinical Services MD ……
Company Overview Stuart
Controller Michelle
Finance Kevin
Human Resources Erin
Operations Seth
Product Development Stuart
Provider Administration Stuart
Sales, New Business
Development
Tom
QA/Corporate Compliance Sharen
IT Russell
26
CurrentAssessment

Interview Key Stakeholders: Common Themes (Example)
• Data is not centralized; rather it is distributed across multiple systems and
requires multiple tools. Switching tools takes a lot of time.
• Significant time is spent manually consolidating data before it can be
effectively utilized/analyzed.
• The current tools do not readily provide the query capabilities users want.
• Some datasets are stale and don’t reflect the most recent data.
• Some clinical data is still only captured as unstructured data which can only
be searched as free text.
• Lack of clear and consistent definitions of common business terms and data
labels.
• New analyses/reports are funneled through 1-2 very busy individuals.
 No “self service” capability for creating new analyses.
• Lack of “benchmarks” in providing quantifiable benefits of services. Such
benchmarks are not readily available in the marketplace.
27
CurrentAssessment

Analytics Use Cases
• A use case is a brief description of how analytics will be
used by a stakeholder. Analytics use cases can help to:
 identify any gaps in analytics capabilities, and
 reduce the likelihood that critical analytics needs will be missed.
• Analytics use cases help identify:
 what data elements are most important and what indicators will
be necessary to calculate, and
 what types of usability and presentation factors (such as
dashboards, alerts, and mobile access) need to be considered.
• Develop high-level use cases when outlining the
analytics strategy, and drill down in more detail as new
analytical applications are designed and built.

Analytics Use Cases Example
29
Customer /
user
Sample use case(s)
Physician Uses personalized performance
report to adjust care practices.
Unit manager Determine which patients are
likely to exceed length of stay
targets.
QI team leader Identify bottlenecks in patient
flow.
Evaluate outcomes of QI
initiatives.
Healthcare
executive
Evaluate and monitor overall
performance of the
organization.

30
Financial Analytics Business Needs Assessment and Use Cases Example
Typical Business Questions
• What are the utilization rates for a
given procedure?
• Are the service lines making a
higher margin this year than last?
• Which services have a high or low
profit margin? Do we have
unprofitable procedures that act as
‘loss leaders’?
• What is the cost/reimbursement
(actual or estimated) ratio by
procedure or diagnosis? By payer?
• What variability in volume,
reimbursements, revenue or cost
do we see between physician, by
specialty, by patient demographics,
by patient diagnosis or by
procedures provided over time?
Primary Business Functions Enabled
Service line optimization Facilities planning
Staff planning Profit optimization
Investment prioritization
Primary Metrics and KPIs
• Percent growth in net revenue
• Increase in Service Line Market
Share
• Revenue
• Operating Expenses
• Operating / Total Margin
• Supply Expenses
• Salaries and Benefits / Labor
Costs
• Purchased Services
• Utilities, Repair & Maintenance
• Insurance & Rent
• Miscellaneous Expense
• Depreciation/Amortization
• Interest Expense
• Hospital (Entity) Allocation
EBIDA %
• Total Operating Expense per
Adjusted Patient Day
• Net Patient Revenue per
Adjusted Admission
Metric/KPI Context
• Date / Time
• Month / Year
• Visit (ambulatory) / Encounter
(acute)
• Episode (Ambulatory only)
• Procedure
• Payer / Payer Type
• Patient Population
• Patient Type (IP, OP)
• Physician / Nurse / Care Giver
• Group / Care System / Entity /
Dept
• Diagnosis / Condition
• Service Code / Charge Code /
Service Type
• Service Line
Typical Business Questions
• What are the utilization rates for a
given procedure?
• Are the service lines making a
higher margin this year than last?
• Which services have a high or low
profit margin? Do we have
unprofitable procedures that act as
‘loss leaders’?
• What is the cost/reimbursement
(actual or estimated) ratio by
procedure or diagnosis? By payer?
• What variability in volume,
reimbursements, revenue or cost
do we see between physician, by
specialty, by patient demographics,
by patient diagnosis or by
procedures provided over time?
Primary Business Functions Enabled
Service line optimization Facilities planning
Staff planning Profit optimization
Investment prioritization
Primary Metrics and KPIs
• Percent growth in net revenue
• Increase in Service Line Market
Share
• Revenue
• Operating Expenses
• Operating / Total Margin
• Supply Expenses
• Salaries and Benefits / Labor
Costs
• Purchased Services
• Utilities, Repair & Maintenance
• Insurance & Rent
• Miscellaneous Expense
• Depreciation/Amortization
• Interest Expense
• Hospital (Entity) Allocation
EBIDA %
• Total Operating Expense per
Adjusted Patient Day
• Net Patient Revenue per
Adjusted Admission
Metric/KPI Context
• Date / Time
• Month / Year
• Visit (ambulatory) / Encounter
(acute)
• Episode (Ambulatory only)
• Procedure
• Payer / Payer Type
• Patient Population
• Patient Type (IP, OP)
• Physician / Nurse / Care Giver
• Group / Care System / Entity /
Dept
• Diagnosis / Condition
• Service Code / Charge Code /
Service Type
• Service Line

31
With Financial Analytics, We Are Able to …
TO SYNTHESIZETO GATHER TO ANALYZE TO ACT TO INFLUENCE
USE THESE INPUTS
RESULTING
IN
• I:Manage
• Avega
• EPIC
• Master Data / Reference
Data
• Monthly trended
financial results
• Service line financial
scorecards
• Standard Financial
Reports
• Ad-Hoc queries
• Data Mining
• Variance analysis
results
• Revenue opportunities
and challenges
• Long-term revenue
opportunities
• Investment
opportunities
• Service line investments
/ divestitures
• Capital investment
strategies
• Revenue and costs
• Budgeted results
• To optimize revenue
potential of service line
components
• To optimize resource
allocation
• By managing spending
• Revenue loss root cause
• Underperforming service
lines
• Underperforming care
systems
• Changes in cash flow
• Resources focused
on growing service
areas
• Targeted cost
reduction projects
• Staff redeployment
• Practice interventions
• Focused strategic
growth
• Leverage of capital
investments
• Variance to Budget
• Identified
deviations from
expected results
• Identification of
significant revenue
changes
• Gross Revenue
• Gross Margin
• Total Margin
• Income and expense
against budget
• Income statements by
service line
• Balance sheets
• Reference data
normalization
• Variance root cause
analysis
• Isolating improvement
opportunities
• Identification of growth
opportunities or cost
savings
TO SYNTHESIZETO GATHER TO ANALYZE TO ACT TO INFLUENCE
USE THESE INPUTS
RESULTING
IN
• I:Manage
• Avega
• EPIC
• Master Data / Reference
Data
• Monthly trended
financial results
• Service line financial
scorecards
• Standard Financial
Reports
• Ad-Hoc queries
• Data Mining
• Variance analysis
results
• Revenue opportunities
and challenges
• Long-term revenue
opportunities
• Investment
opportunities
• Service line investments
/ divestitures
• Capital investment
strategies
• Revenue and costs
• Budgeted results
• To optimize revenue
potential of service line
components
• To optimize resource
allocation
• By managing spending
• Revenue loss root cause
• Underperforming service
lines
• Underperforming care
systems
• Changes in cash flow
• Resources focused
on growing service
areas
• Targeted cost
reduction projects
• Staff redeployment
• Practice interventions
• Focused strategic
growth
• Leverage of capital
investments
• Variance to Budget
• Identified
deviations from
expected results
• Identification of
significant revenue
changes
• Gross Revenue
• Gross Margin
• Total Margin
• Income and expense
against budget
• Income statements by
service line
• Balance sheets
• Reference data
normalization
• Variance root cause
analysis
• Isolating improvement
opportunities
• Identification of growth
opportunities or cost
savings

Organizational Assessment
• Recently embraced and embarked on a strategy for BI/Analytics
Executive sponsorship exists at VP and Sr. Director level
A data warehouse is under development
• Does not yet have a formal BI/Analytics Executive Steering Committee
Broad and formal representation should exist
• No formal Data Governance or BI/Analytics Competency Center
Focus is on providing analyses – Not on providing users with tools and training to be self-sufficient
Lacks direction toward a single, consolidated approach to business metrics
Lacks formal data governance and data quality (data stewards) roles and processes
• No dedicated Development team with needed analytics skills/experience
 Existing Applications Development team doing all development
 Existing team has little or no experience in data warehousing and BI/Analytics
32
CurrentAssessment

Processes & Data
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure

Data Considerations
• Data is the “raw material” of analytics.
• Modern computerized clinical systems (such as electronic
medical records) contain dozens if not hundreds of
individual data elements.
 The potential exists for thousands of possible data items from which
to choose for analytics.
• An analytics strategy must consider:
 how to determine which data is necessary for quality and
performance improvement
 how the data is managed and its quality assured
 how data links back to business processes for necessary
context.

Data Issue Example
Data Sources • What are the sources of data?
• What data is necessary to address key business
issues?
Data Quality • How good is the quality of available data?
• Is the data “good enough” for analytics?
• What gaps in data exist?
• Does metadata exist?
Data governance • Who is responsible for data management,
governance, and stewardship?
• What policies and procedures exist?
Business Processes • What business processes and procedures align with
important quality issues?
• What data is available for measuring processes? Are
proxy measures available?
Data Considerations for Analytics Strategy
35Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics

Data Assessment
36
• Data is not complete, integrated or
organized for the enterprise
 Multiple versions of the data exist on
different platforms
 Multiple sources of data & tools to answer
a single question
 Common definitions of terms are not
defined or widely understood
• Users spend too much time as
data gatherers and integrators,
rather than as analysts
 No reuse leads to redundant effort and
inconsistent results
 High risk of errors
• Little or no data quality processes
 No audit, balance and control
 No formal Master Data Management (e.g.,
Provider)
• No metadata management
 Business terms are not standardized and
shared
 Business rules are not standardized and
shared
many “data domains”
no single trusted source
inefficient redundancy
no data integration
no data governance
CurrentAssessment

Allergic asthma
389145006
Aspirin-induced
asthma
407674008
Acute asthma
304527002
Drug-induced asthma
93432008
Work aggravated
asthma
416601004
Allergic bronchitis
405720007
Chemical-induced
asthma 92807009
Brittle asthma
225057002
Sulfite-induced
asthma 233688007
Millers' asthma
11641008
Asthma attack
266364000
Asthma night-time
symptoms 95022009
Etc.
SNOMED CT
Asthma
95967001
Asthma, Unspecified
Type, unspecified 493.90
ICD9CM
Metadata is Data of Data
Metadata is a set of data that describes and gives information about
other data.

Business Processes
• Business processes provide essential context to the data.
• Most quality improvement methodologies monitor
progress and evaluate performance and outcomes using
indicators based on process data.
 Requires a strong alignment between key business processes
and the data that measures those processes.
• As part of the analytics strategy, consider:
 if and how current business processes are documented, and
 how data items are mapped to these documented business
processes.
 stacks of Visio charts becomes unmanageable very quickly!

• Using appropriate indicators that align between tactical
and strategic levels are necessary.
 Tactical-level sub-indicators should align with strategic indicators
 Some tactical-level-specific indicators might be necessary for initiatives
that are important at a program, department, or unit level, but don’t
directly align with strategic goals.
Indicator
Sub-
Indicator 1
Sub-
Indicator 2
Sub-
Indicator 3
Strategic
Level
Tactical
Level
Tactical
Indicator 1
Using Appropriate Indicators
39HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang 39

Strategic and Tactical Indicator Alignment Example
40
95% of patients admitted from ED
achieve EDLOS < 8hrs
Time to
physician
assessment
Time to
consult
answered
Time to
consult
decision
Strategic
Level
Tactical
Level
Time to
inpatient bed
assigned
Time to
patient left ED

Analytics Tools and Techniques
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure

Common Analytical Applications
42
Analytical Application Description
Statistical • Used for deeper statistical analysis not available in
“standard” business intelligence or reporting
packages
Visualization • Used for developing interactive, dynamic data
visualizations that aid with analysis
Data Profiling • Helps to understand and improve the quality of an
HCO’s data.
Data Mining • Analysis of large data sets to uncover unknown or
unsuspected relationships.
Text Mining • Analysis of unstructured, text-based data to extract
high-quality information.
Online Analytical Processing • Allows analysts to interactively explore data by
drilling-down, rolling up, or “slicing and dicing”
data.
Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics

Inventory of Existing Analytical Tools
• Analytical tools must meet the requirements of analysts
building analytics solutions/applications, and the end-
users who will rely on the resultant information and
insight.
• Conduct an inventory of existing analytics tools to
determine if:
 Capability is missing that will be required
 Existing capability exists that may not be widely known
• Identify viable best-of-breed vendor solutions that meet
requirements; custom-build from scratch if necessary or if
participating in research.

Analytics Tools Assessment Example
• HCO recently started down the road to BI/Analytics
Development of DW, strategy, processes, and standards underway
Consider evaluation of Information Delivery tools (e.g. SAS, Cognos)
• Current and targeted hardware is appropriate
Size of data and organization does not warrant more powerful hardware
• Current software direction is appropriate
Crystal Reports not fully utilized
Microsoft BI Tool suite is a good fit
Already invested in Microsoft technology (SQL Server, SharePoint, CRM, etc.)
Existing licensing will cover expected needs for near-term
“best of class” tools are overkill with unjustifiable ROI
SAS licenses are not current and tool is not currently in use
Additional software needed
• Data modeling – a more formal tool/process should be adopted
• Metadata – no good tool on the market 44
CurrentAssessment

Team and Training
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure

Team Development Considerations
• People are a critical consideration when developing or expanding an
analytics capability within a healthcare organization
• Although having the best tools are nice, having the best (and right)
people is critical to achieving the goals and objectives of the HCO
• An analytics strategy must consider:
 What kinds of people (and the skills they bring) are necessary
 The optimal size and composition of the team
 Roles and degree of specialization
 What gaps in skills exist, and what training is required
 How to attract the best analytical talent
 How to retain the analytic talent within your HCO
 Optimal organizational structure

Providing Analytics Training as part of Physician Engagement Plan
• Achieving improvements in today’s world
of value-based care requires physician
buy-in because their decisions drive the
majority of quality and cost outcomes.
• Provide administrative support, data
analytics and reporting, and the training
needed for improvement.
• Listen to and address physician’s
concerns to gain their trust and get buy-
in and enthusiasm for quality
improvement efforts.

Technology and Infrastructure
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure

Technology & Infrastructure
• Analytics and reporting are the tip of the iceberg in the
business intelligence stack.
• The current, near-term, and long-term analytics needs of
the HCO must drive how analytics-related technological
capabilities are acquired. The exact complement of tools
will depend on the overall needs of the HCO.
• The analytics strategy is an important input to IT
hardware and infrastructure strategies and planning as
hardware and other system upgrades are considered.

Healthcare BI and Analytics Technology and Infrastructure
50
Source:
Evelson, B. It's Time to Reinvent your BI Strategy.
Forrester Research, Inc.
Reporting and analytics are the
“tip of the iceberg” regarding
the business intelligence
technology stack.

Organizational Considerations
• Different resource management models exist for analytics teams:
 “centralized” analytics office
 “distributed” analytics resources
 “virtual” center of excellence / competency center (combines best
aspects of centralized and distributed models)
51
Virtual Business Intelligence / Analytics Competency Centre
Senior
Management
Decision Support
Services
(Analytics)
Central (“Core”)
Analytics
Analysts
Surgery Program
Program
Analytics
Resource
Medicine
Program
Program
Analytics
Resource
Emergency
Program
Program
Analytics
Resource

53
Strategy Execution Summary
• It is important to implement and adhere to the analytics strategy
• Plan for and schedule activities to address identified gaps
 Establish a selection criteria to determine what projects will get
emphasis in light of needs of the business and analytics strategy
 Prioritize activities and desired capabilities to balance resources as new
(possibly conflicting) work arises
• Monitor progress towards achieving goals of the analytics strategy
• Ensure that the strategy is a living document that serves as a
roadmap for guiding action and doesn’t become “shelfware”
53

Implementation Challenges
Program Needs Healthcare Challenge
Executive Support Executives have to manage organization’s staff to get
their cooperation and buy-in.
Well-Defined Business
Challenge
Business challenges are everywhere. The real problem is
prioritizing which one to address first.
Lots of Data There’s lots of data but a lot of it is locked in departmental
silos which ultimately makes all the data useless.
Right Team The challenge will be finding qualified people in an already
scarce resource pool and getting them to accept the lower
wage healthcare may pay. Outsourcing might need to be
an option. Bottom Line: GET HELP!
Integral Part of Organization Everyone must buy-in to the results of the analytics
program including clinical, finance and operational staff.
Track Results and Update
Models
With the right team in place this should not be an issue.
54

Strategic Planning and Development
55
FiltersCurrent State
Details
Assessment and Strategy Development
Business
Drivers
Technical
Landscape
Executive
Summary
Data readiness
assessment
Information Architecture
Organization Architecture
Project Management
Analysis and documentationInformation gathering
Current
State
Summary
Gaps
Summary
Planning
Documents
Strawman
Vision
Program
Analysis and
Planning
Analytical
Processes
Needs
Assessment
Technical Architecture
Functional Requirements
Best Practices
Relevant Client
Experiences
Applicable Industry
Trends

Gap Analysis
• Identify important gaps between current and future state, what the corrective
action(s) will be, who owns the actions, and what the due date for corrective
actions is.
56
http://www.mindtools.com/pages/article/gap-analysis.htm
Category Current State Target State Corrective Action Priority Owner Due Date
Business & Quality
Context
Stakeholders &
Users
Data & Processes
Tools & Techniques
Team & Training
Technology &
Infrastructure

Prioritizing Gap Corrective Actions
• Use the Impact / Effort matrix to help quantitatively determine priority
for addressing analytics gaps.
57
Q1
Impact(increasing)
Effort/Resources Required (increasing)
Q4
Q2 Q3
Low impact, Low effort
“Consider”
High impact, Low effort
“Immediate”
High impact, High effort
“Evaluate”
Low impact, High effort
“Avoid”

Assessing Business Value and Process and Data Readiness
58
Score Profile Ranking
0.0
1.0
2.0
3.0
4.0
5.0
Clinical Quality (In Setting)
Patient Experience / Satisfaction
System Performance Analysis
Cost Tracking & Variance Analysis
Safety Tracking
Patient Flow Optimization
Clinical Quality (Out of Setting)
Corporate Top Level KPI's
Physician Demand Management
Patient Demand Management
Revenue Cycle / Charge Integrity DNFBRevenue Cycle / Patient Access
Staffing Management / Utilization
(at department/low level)
Service Design / Redesign
Strategic Workforce Planning
Materials Management
Engagement
Payer Analysis;
Contract Negotiation; Pricing Analytics
Revenue Cycle / Patient Financial Services'
Clinical Trial Inception and Monitoring
Research Grant Application and Tracking
Expected Business Value
Process… Readiness
Data Readiness

59
Prioritizing Data Subject Areas Example
Sales /
Acct Mgmt
Clinical
Claims
Financial
Network Mgmt
Provider
Contracts
Lower HigherImplementation Readiness
Higher
Lower
BusinessValue
Business Value: qualitative, mission-based assessment
Readiness: ease of data integration, given quality, number of sources, completeness, etc.
• Incrementally delivering BI value begins with an understanding
of data readiness and its value to the business
Case Mgmt
ImplementationRoadmap
1
3
2

At the End of a Strategy Planning, Detailed Documents and
Presentation Are Prepared to Obtain Management Buy-in
• Project Objectives & Approach
• Current Environment Assessment
 Data
 Organization
 Technology
• Future State Recommendations
 Business Process & Data Gaps
 Architecture
 Organization
• Implementation Roadmap
 Recommended Priorities
 Recommended Phasing
 Resource & Budget Estimates
• Why BI/Analytics?
 Benefits & ROI Considerations
• Summary & Next Steps to Success
60

Current Environment Assessment

62
Overall BI and Analytics Assessment – Where we are Now
Data
Organization
Technology
Best in
Class
CurrentAssessment

63
Assessment Summary – Using the Analytic Maturity Model
STAGE 1
REPORTING
WHAT
happened?
Primarily Batch
with Pre-
defined
Queries
STAGE 2
ANALYZING
WHY
did it happen?
Increase in
Ad Hoc Queries
STAGE 3
PREDICTING
WHAT
will happen?
Analytical
Modeling
Grows
STAGE 4
OPERATIONALIZING
What
IS happening?
Continuous Update &
Time Sensitive Queries
Gain Importance
STAGE 5
ACTIVE
Analytics
How do
we MAKE it happen?
Event Based
Triggering
takes hold
Batch
Continuous
Update /
Short Queries
Event-Based
Triggering
Ad Hoc Analytics
You are
here
CurrentAssessment

Current Assessment: Data Assessment Findings
• Implement New Accounting Method
• Evaluate and Deploy Enhanced Accounting System
• Employer Industry Coding – SIC/NAICS Codes
• Contract Reject Reason Codes
• Claims OCR and Pending Claims
• Service Code Mapping Update
• Revised Reforecasting
• Obtain Industry Benchmarks
• Fully deploy Customer Relationship Management
• “Other” Clinical Data
• Data Product Strategy Definition
64
FutureStateRecommendations

65
Current Landscape BI/Analytics Architecture (AS IS Sample)
Source
Systems
Existing
Planned
Retiring
External
Data Flows
Existing
Planned
Manual
Serve
Excel and/or
Access
Store
(RDB/ODS/DW/DM)
Siemens
Cred File
Quest
Labs
Hoovers
Ecare Online
EPIC
CHS
Claims
PMMC Contract
Pro
ECHO
Care
Science
Web Server
Payer
Master
Employer
Database
Member
Invoicing Tool
Agreement
Summary
Transplant
Great Plains
Fee Schedule
Colon Cancer
Screening
Medassets
Cost DataEligibility
Acct Payable
Fixed Asset
GL / Invoicing
Physician,
Clinical,
&
Fin. Data
Find a
Doctor
(Web)
Hosp Clinical
And Financial
Data
Clinical
Performance
Inits
Transplant/
Distribution
Invoicing/
Receivables
Employer
Relations
Reporting
Reinsurance
Recovery
Meditech
Patient
Registry
Lab
Data
Central Benefit
Verification Planned
Central
Benefit
Verification
Unit
Employer
(Access)
Reference & Ad Hoc
(Access)
Patient
Charts
PMMC Physician
Pro (CDR)
DW
Various Physician App
Feeds (Medisoft, Misys, etc.)
Lab Data
Transplant
(Access)
Clarity
UHC
Med Labs

Process and Data
Future State & Recommendations

Future State and Recommendations – Data Example
• Implement New Accounting Method
• Evaluate and Deploy Enhanced Accounting System
Issue Action
• Change in accounting method
impacts requirements for Finance
data
• Current process/tools for creating
financial (GAAP) results:
− Are not efficient or timely
− Do not readily support BI &
integration to a Data Warehouse
• Select and fully implement new accounting
method before integrating this data with a BI
solution
• Evaluate project-based accounting systems as
these support business activities for:
− Contracting for a defined body of
work/services (a project)
− Budgeting for delivery of products and
services
− Defining project tasks and track status
− Assigning resources to a project/task
− Collection of expenditures (i.e. Claims) for the
delivery of products and services
− Invoicing of customers
− Revenue recognition based on project
activities (using various methods)
Result
• More efficient and timely accounting close cycle
• Robust data source of financial results for use in BI
67

• Employer Industry Coding – SIC/NAICS Codes
Issue Action
• NAICS Industry codes are not currently
being captured even though ARCH
supports this
• Industry information is needed to
support Contracts Analytics
• Implement processes to ensure
collection of Industry codes via:
− Employer contact
− Web-base service
− D&B service
Result
• More complete demographics information to support industry-based analysis (i.e.,
Marketing)

• Contract Reject Reason Codes
69
Issue Action
• Reject reasons are not currently
captured accurately for all declined
contracts
− 50% of rejected contracts since the
beginning of 2006
− $13,000,000 of contracts
• Limits Client’s ability to analyze
rejected contracts and forming
strategies to increase conversion rates
• Implement process and system
changes to require a Reject Reason be
specified when a contract is rejected
Result
• Basis for understanding why contracts are rejected
• Definition of goals and processes to reduce specific types of rejects
• Increase conversion rate and revenue
Reject Reasons
By Contract Value
No Reason
Cost
Carrier to Manage
Noncompensable
Rescinded Contract
Employer Request
Other

• “Other” Clinical Data
Issue Action
• Valuable clinical data is currently
being captured as “Other Data” (free
text in CATS)
• Hinders BI support of clinical
analyses
− Manual searches of clinical records for
conditions and risk factors not
predefined in CATS
• Assess the benefits of capturing this
data as structured data
• Weigh against the costs of
implementation options:
− Replacing InfoPath forms to enable
capture of structured data at point of
care
− Implement new processes (CATS) to
identify and structure (with user input)
such “Other data” after the point of
initial entry
− Deploy Knowledge Management or
search tools to enhance search-ability
of clinical records
Result
• Codification of all diagnoses, treatments, etc. for a case
• Enhanced clinical analysis
• Improved risk identification/mitigation and treatment plans
70

• Data Product Strategy Definition
Issue Action
• Data products generally utilize
industry standard coding schemes
(i.e., CPT, HCPCS, ICD, etc.)
• Not all Client data is collected using
such standards:
− Clinical assessments (CATS)
− Contract budgets and classifications
(ARCH)
• Only Claims data is captured using
such standards
• In defining a product strategy based
on Client’s existing data, weigh the
costs to:
− Convert existing to appropriate
industry standards (at a sufficient level
of detail)
− Modify processes and systems to
capture data in accordance with such
standards
Result
• Viable product strategy (including all costs to deliver)
71

Future Technical Architecture Recommendation Example
• Current and targeted hardware is appropriate
Size of data and organization does not warrant more or different
• Current software is appropriate, but should be augmented
Microsoft BI Tool suite is the right size and fit for Paradigm
Already licensed for SQL Server, and SharePoint (incl. SSIS, SSAS, SSRS, and Excel
Services)
Given analytics maturity and size, growing with Microsoft BI solutions makes sense
Probable upgrade to Enterprise Edition of SQL Server
Adopt SAS (or equivalent tool) on limited basis where/when needed (i.e., with Clinical data)
• Data modeling – a more formal tool/process should be adopted
(Microsoft or ERwin)
• Metadata Management
72

Organization

74
Enterprise Business Intelligence/Analytics Governance
• Ensures EDW/BI/Analytics
projects align with the
business vision so that
 Right projects done at the
right time, driving optimum
business benefit
 Data standards are followed
 Data integrity and quality
 Facilitate data ownership
issue resolution
 An enterprise-wide ‘business’
perspective is taken into
account
Development Team
• Define, Design, Build, Test, &
Deploy
• Tool Evaluation and Support
• Technical Support
• BI Architecture and Infrastructure
Data Governance Team
(Data Stewards)
• Develops Business Rules
• Enforces data policies in terms
of data validity, accuracy,
ownership
BI and Analytics
Executive Committee
• Strategic Direction &
Business Alignment
• Sets Policy
• Proposes Funding
• Meets quarterly
• Business & IT Leaders
• Tactical Direction & Cultural
Change Agents
• Resolves cross-functional Issues
• Presents recommendations to
Executive Committee
• Meets monthly
Advisory Committee
Competency Center (Analytic
Stewards)
• End-user Support
• Tips & Techniques
• Exchange Successes
• Usability Feedback
• Standard Measures
• Liaisons to customers

Architecture

TECHNOLOGY – HIGH LEVEL LANDSCAPE (VISION STATE)
SatisfySource
UHC
Store
Cred File
Quest
Labs
Hoovers
eCare Online
CHS
Claims
PMMC Contract
Pro
ECHO
Care
Science
Web Server
Eligibility
Meditech
Med Labs
Patient
Charts
PMMC Physician
Pro (CDR)
DW
Various Physician App
Feeds (Medisoft, Misys, etc.)
Stage
Web Site
Enterprise
BI Tool
Executive
Dashboards
Enterprise
Reports
Ad hoc & OLAP
Reports
Data Mining/Modeling
Organization, Stewardship and Governance
Data Quality and Meta Data Management
Systems
Existing
Planned
External
Data Flows
Existing
Planned
Manual
Data Back
to Sources
EDW
Analytics
Master & Ref
Data
EPIC
Lab
Data
Data
StewardsMatch/Merge
Data GovernanceMaster
Data Management
MedAssets

EDW and Analytics System Hosting Options
77
With this model, the vendor connects
your data sources to a secure, HIPAA-
compliant environment in the cloud.
Vendor-Hosted Solution in the Cloud
The vendor purchases the base
hardware, customizes it, and installs
the appropriate software offsite.
Vendor Appliance Hosted by Client
Many clients acquire the hardware and
software licenses required and the
system is set it and hosted in their own
data center.
Client-Hosted Solution (On-Premise)
Benefits of outsourcing EDW/Analytics
• No need buy, manage, maintain, or
worry about hardware and software
assets residing in your own data center.

Implementation Roadmap And Resources
An Consultant’s Approach

79
Implementation Roadmap & Timeline
Legend:
20xx 20xx 20xx
Q3 Q4Q1 Q2 Q2Q4Q3
“Other” Clinical Data
DataTools
XLS’s
Industry
Coding
Q1
Reject
Reasons
Prerequisite Process &
Data Enhancements
Deploy Subject Area/
Functionality
Sunset Existing
Tool/Process
Deploy Architectural
Component
Data Architecture &
Modeling Tools
ETL (SSIS)
Architecture
Information Delivery
(SSRS) Architecture
Data Governance &
Stewardship
Phase 1: Contracts
Industry Standard
Coding
SAS Access
(as needed)
Phase 2: Clinical Phase 6: Clinical V2
Data Product
Strategy
Phase 3: Claims &
Providers
Claims OCR &
Pending Claims
Service Code
Mapping Update
Revised
Reforecasting
Phase 4:
Sales, Account Mgmt,
Referrals & Benchmarks
Fully Deploy CRM
Industry
Benchmarks
Scorecard
(as needed)
Phase 5:
Finance
New Accounting
Method Implemented
Evaluate/Deploy
Accounting System
DataTools
XLS’s
WC_
Reporting
Crystal
Reports
(Claims)
Finance
MDB’s
Future
Phases
Prerequisite Data
PRN Integrated
into ARCH
Meta Data
OLAP Tools
(as needed)
Continuous
Refinement
Master Data Management
(Provider, Customer, etc.)

Phase 1
80
Source
ServeStore
Stage
(SSIS) Enterprise
ID Tool
(SSRS, AS)
Functional Scope:
• Contracts (ARCH)
& Pending Contracts
• Non-GAAP Contract
Performance
Data and Metadata Management
Enterprise
Reports
Ad hoc
Reports
P_Central
ReferralComplex
Kwiktag
ARCH
PRNCRM CFMS
CATS
SQL
NuView
(HR)
Hosted
Access DBs
EBS
(Payroll)
Health-eSystems
(Rx)
Access DBsWC_
Reporting
RPT
CS Stars
(Paid Claims)
Data Flows
Existing
Planned
Manual
Data Back
to Sources
Systems
Existing
Planned
Retiring
External
DW
Analytics
Data
Steward
Tasking
Various Access DBs
(Arch, Tools, etc.)
CATS_
ReportingSQL
Excel
Access
Crystal
(Contract
& Claims)
Excel
Access
Master
Data
IW Addr
• Mentor Client Team in full “life cycle” BI/Analytics development
methodology
• Implement basic data & metadata management (KPIs & governance)
• Provide initial ad hoc reporting as pilot (rapid prototype)
• Begin to build out reports with EBI tool to replace existing tools

Phase 2
81
ServeStore
Source
Stage
(SSIS)
Enterprise
BI Tool
(SSRS, AS)
Functional Scope:
• Clinical (CATS)
• “Other Data” as-is
• Link to Contracts
P_Central
ReferralComplex
Kwiktag
ARCH
PRNCRM CFMS
CATS
NuView
(HR)
Hosted
Access DBs
EBS
(Payroll)
Health-eSystems
(Rx)
Access DBsWC_
ReportingCS Stars
(Paid Claims)
• Continue mentoring with Clinical Data from CATS, demonstrating
conformation of metrics and dimensions, and data cleansing
• Expand on Data and Metadata Management capabilities with MDM
(Provider), data lineage, and more mature/complete KPIs.
• Mature data stewardship and governance processes.
• Introduce OLAP into ID solutions suite.
DW
Analytics
OLAP
Ad hoc
Reports
Enterprise
Reports
Data
Stewards
Tasking
Excel
Access
Crystal
(Contract
& Claims)
Master
DataIW Addr
Systems
Existing
Planned
Retiring
External
Systems
Existing
Planned
Retiring
External
Data Flows
Existing
Planned
Manual
Data Back
to Sources

Phase 3
82
Source
SatisfyStore
Functional Scope:
• Claims (CFMS Feed)
• Service Code Maps
• Provider Master
(PRN & Claims)
• Provider Analysis
• Link Claims to
Contracts & Clinical P_Central
ReferralComplex
ARCH
PRN CFMS
Kwiktag
CRM
CATS
Basic
Scorecards
OLAP
Ad hoc
Reports
Enterprise
Reports
Data
Stewards
• Continue mentoring with Claims data from CS Stars & Health-eSys.
• Expand on Data and Metadata Management capabilities.
• Continue to mature data stewardship and governance processes.
• Prototype defined KPIs for score-carding solutions.
NuView
(HR)
Hosted
Access DBs
EBS
(Payroll)
Health-eSystems
(Rx)
WC_
ReportingCS Stars
(Paid Claims)
Access DBs
Stage
(SSIS)
DW
Analytics
CFMS
SAS
Client
Web Site
Enterprise
BI Tool
(SSRS)
SAS
Tasking
Crystal
(Claims)
Master
Data
Provider
IW Addr
Data Flows
Existing
Planned
Manual
Data Back
to Sources
Systems
Existing
Planned
Retiring
External

Phase 4
83
Source
SatisfyStore
Stage
(SSIS)
Functional Scope:
• Sales/Acct Mgmt
(CRM)
• Referrals
• Benchmarks
(External)
P_Central
ReferralComplex
ARCH
PRN CFMS
Kwiktag
CRM
Hosted
EBS
(Payroll)
Health-eSystems
(Rx) CS Stars
(Paid Claims)
NuView
(HR)
CATS
DW
Analytics
• Continue with Sales & Account Management data. Ensure
standard ETL approach and dimensional conformity.
• Expand on Data and Metadata Management capabilities.
• Complete stewardship and governance processes maturity path.
Benchmark
Web Site
Enterprise
BI Tool
(SSRS)
SAS
Tasking
etc.
Provider
IW Addr
Master
Data
CFMS
Scorecards
OLAP
Ad hoc
Reports
Enterprise
Reports
Data
Stewards
SAS
Data Flows
Existing
Planned
Manual
Data Back
to Sources
Systems
Existing
Planned
Retiring
External

Phase 5
84
Source
SatisfyStore
Stage
(SSIS)
Functional Scope:
• Financial (GAAP)
Results
• Link to Contracts
P_Central
ReferralComplex
ARCH
PRN CFMS
Kwiktag
CRM
Hosted
EBS
(Payroll)
Health-eSystems
(Rx) CS Stars
(Paid Claims)
NuView
(HR)
CATS
DW
Analytics
Financial
Systems
• Ensure ETL & dimensional conformity.
• Complete core Data and Metadata Management capabilities (MDM,
Lineage, Quality, KPIs, etc.).
• Continue to leverage stewardship and governance to perfect
B/Analytics Competency Center thru user and web-site support, and
training.
Paradigm
Web Site
&
Enterprise
BI Tool
(SSRS)
SAS
Benchmark
Tasking
Scorecards
& Dashboards
OLAP
Ad hoc
Reports
Enterprise
Reports
Data
Stewards
SAS
Data Flows
Existing
Planned
Manual
Data Back
to Sources
Systems
Existing
Planned
Retiring
External

Phase 6+
85
Source SatisfyStore
Stage
(SSIS)
Functional Scope:
• Clinical “Other”
Data
P_Central
ReferralComplex
ARCH
PRN CFMS
Kwiktag
CRM
Hosted
EBS
(Payroll)
Health-eSystems
(Rx) CS Stars
(Paid Claims)
NuView
(HR)
CATS
DW
Analytics
Financial
Systems
• Bring in remaining clinical data using all established process and
tool infrastructure.
• Expand on Data and Metadata Management capabilities, and well
as overall Governance, to ensue long term sustainable solutions.
Master
Data
Match/Merge
Master Data Management
Paybase
Benchmark
Tasking
Paradigm
Web Site
&
Enterprise
BI Tool
(SSRS)
SAS
Scorecards
& Dashboards
OLAP
Ad hoc
Reports
Enterprise
Reports
Data
Stewards
SAS
Data Flows
Existing
Planned
Manual
Data Back
to Sources
Systems
Existing
Planned
Retiring
External

Resource Requirements Estimate
NOTE: The Paradigm FTE includes
~.5 FTE of non "Core Team"
personnel such as:
~.2 FTE for Executive Sponsors
~.2 FTE for Data Stewards.
~.1 FTE for IT Support
(i.e., DBA, SysAdmin)
86
FTE Per Roadmap Phase
7.25
5.91
2.57
- -
4.68
5.91
6.03
7.52
7.23
6.28
0.36
3.60
3.09
6.03
4.14
3.92
5.92
-
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
1 2 3 4 5 6
Phases
FTE
Total FTE
HP FTE
Paradigm FTE
Client and
Consultant
FTE

Resource Allocation & Cost By Phase
87
Budget estimates provided in this presentation should be considered estimates
to provide Board with a budget range for planning purposes
Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6 TOTAL
Internal Resources 315,300$ 275,000$ 280,100$ 340,900$ 272,600$ 258,000$ 1,741,900$
Professional Services (wt Expenses) 968,400$ 719,900$ 641,800$ 101,000$ -$ -$ 2,431,100$
Hardware & Software 7,000$ 5,000$ -$ 42,000$ 20,000$ -$ 74,000$
Total By Phase 1,290,700$ 999,900$ 921,900$ 483,900$ 292,600$ 258,000$ 4,247,000$
Capitalized Dollars
1,148,200$ 906,800$ 798,500$ 422,900$ 262,200$ 234,200$ 3,772,800$
Expense Dollars
142,500$ 93,100$ 123,400$ 61,000$ 30,400$ 23,800$ 474,200$
• Estimates do not include any resource space costs
• Consulting costs are based on 20xx standard rates
with a 5% discount applied
• Consulting work week is based upon 45 hours
• Internal Resources are at a $55-$76 / hour
• Existing hardware is sufficient for the
duration of this roadmap
Cost Assumptions

Value Proposition and ROI Analysis
A Consultant’s Approach

DRIVING MEMBER VALUE
Initiative Revenue Management Member Dashboard Portfolio Management
Capabilities Proactive surveillance of
claims underpayment and
systematic billing and
collections issues
Member operational
measures for problem “Early
Warning” and best practices
identification
Network wide analytics and
modeling of payer volume,
revenue contribution and service
issues. Systematic “Threat
Level Assessment”
Contribution to
Organizational
Excellence
• Ensures equitable
member reimbursement
• Enables monitoring of
contract terms compliance
• Reduced work for
practices and hospitals
• Proactive identification of
issues and root cause
analysis
• Identification of future
contract protections
• Achievement of contract
value
• Identification and remediation
of sub-optimal contract
performance
• Optimization of contract
portfolio value over time
• Sophisticated information
based contract negotiations
Value to Others Members:
• Decreased revenue loss
• Decreased time to
resolution
Patients:
• Fewer billing issues
• Better patient experience
Members:
• Operational improvement
opportunities based on best
practices identification
• Greater understanding of
the customer base
Members:
• Better contract terms
• Increased operational
efficiencies
• Increased patient volume and
revenue
Market:
• Predictability/stability

DRIVING PATIENT VOLUME, REVENUE GROWTH
Initiative Patient Referral Catchment Eligibility & Benefits
Capabilities Patient source, treatment
sought and referral-out
analytics
Patient, employer, payer and
practice profiling
Eligibility and benefits verification
analytics
Contribution to
Organizational
Excellence
• Physician outreach and
feedback programs
• Direct patient and
employer outreach and
education
• Disease management
• Targeted marketing
opportunity identification
• Enriched employer
relationships
• Directed patient volume
growth
Deeper understanding of:
•Trends in benefit products
•Covered services
•Bad debt allocation guidelines
Enhances contracting and
employer relations efforts
• Increased patient and
revenue bases from “new”
and existing markets
• Input into service and
network design
Patients/Employers:
• Continuity of care
Members:
revenue bases from “new”
and existing markets
• Input into service and
network design
Employers:
• Customized services
based on need
Members:
• Improved patient registration
guidelines, collection of co-
payment at time of service
Patients/Employers:
• Awareness of benefits and
payment expectations
• Fewer service issues

DRIVING CLINICAL EXCELLENCE
Initiative Performance
Indicators
Physicians Dashboard Product Modeling Patient Continuum
of Care
Capabilities Encounter based
P4P and Bundled
payment measure
benchmarking
Measure clinical quality &
outcomes by clinical
integration program, case
mix and disease state
Design new products &
services to grow
organization’s network
and quality
Episodic based
quality and outcome
measure
benchmarking
Contribution to
Organizational
Excellence
Provides
systematic
performance
feedback
Helps develop advanced
population-based care and
provides tools for change
Enables employer-
sponsored health
improvement program
innovation
Differentiates
organization in quality
and patient outcome
• Demonstrated
performance
under contracts
• Clinical
leadership as
Clinical
Integration and
ACO initiatives
evolve and
expand
Members:
• Increased understanding
of patient base
• More timely feedback,
and guidance for change
Patients/Employers:
• Reduced cost of care
• Better care and outcome
Members:
revenue bases from
“new” markets
Employers:
• Focus on improving
employee health
• Customized services
based on need
Members:
• Highest reputation
in market
• Patient loyalty to
brand
Patients/Employers:
• Best value in health
care

92
Client’s Improvement Opportunities
Minimize Headcount as Revenue
Grows
• Use BI & Analytics to integrate data and
provide faster access to more complete
data for more efficient:
 Budget creation for Referrals
 Responses to customer inquiries
 Research of provider/claim issues
 Reforecasting
• Assumptions
 If revenue increases four-fold, DCS FTE
would increase from 9 to 36 (27 new FTE)
 Process and BI changes would enable case
load to increase 50%
 Eliminates 14 of 27 new FTE at $135K/yr
Potential Impact
Phase 1 – 3:
2 FTE @ $135K/Yr
$270K/Yr
Phase 3 onward:
14 FTE @ $135K/Yr
$1.9M/Yr
NOTE: Does NOT include reduced FTE for the
DCS Administrative Team
Currently 2+ FTE per DCS (28 FTE total)
WhyBI?
Operational
Efficiencies
Customer
Satisfaction
Clinical
Analysis
Predictive
Modelling
Market
Penetration
 

Client Improvement Opportunities
93
Enhance Pricing Accuracy
• Use BI/Analytics to reduce the risk of
additional outlier or “losing” contracts by:
 Simplifying access to complete contract/ case
history during pricing
 Deeper analysis of clinical history to determine
key Risk Factors (and related treatment and
cost impacts) for use in pricing
• Assumptions
 Client enjoys a 99.5% budgeting accuracy rate
(across all contracts)
 Negative outliers total $13.5M (18 mos)
 15 contracts over budget by > $500K ($750K
average)
 3 contracts are over budget by > $1M ($1.5M
average)
 $9M/yr impact at current contract volume
WhyBI?
Operational
Efficiencies
Customer
Satisfaction
Clinical
Analysis
Predictive
Modelling
Market
Penetration
   
Potential Impact
− Phase 2 onward
− Total potential:
$9M/Yr
− 50% increase in
accuracy of negative
outliers (at current
volumes):
$4.5M/Yr

94
Improve Conversion Rate / Reduce
Rejects
• Utilize BI/Analytics with combined datasets
with benchmarks to support Sales and
Marketing efforts, including:
 Quantitative analyses supporting Client’s
value proposition
 Marketing and brand awareness
 Customer/Case specific Referral or
Opportunity
 Identify market niches and opportunities not
previously identified which contribute to new
products/services.
• Assumptions
 $26M of rejected contracts (from 1/06)
 $11M (or more) rejected due to “Cost” or
“Carrier to Manage”
Potential Impact
Phase 2 & Phase 4
Assume 20% of $11M could
be converted
$1.5M/Yr
WhyBI?
Operational
Efficiencies
Customer
Satisfaction
Clinical
Analysis
Predictive
Modelling
Market
Penetration
   
Reject Reasons
By Contract Value
No Reason
Cost
Carrier to Manage
Noncompensable
Rescinded Contract
Employer Request
Other

Potential Impact of BI/Analytics
$8-12M/Yr potential savings
versus
$4M BI investment
Payback period would be under 2 years
95
WhyBI?

Drive Healthcare Transformation with a Strategic Analytics Framework and Implementation Plan

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