CSBI Course 1 Understanding the Industry

CSBI Course 1: Understanding the Industry
● Business Intelligence for the Healthcare
Industry
● Healthcare Services Delivery Components
● The Broader Healthcare Delivery Environment
● Health Services Across the Health Continuum
● Healthcare Services Delivery and Component
Independence
CSBI Course 2: The Business of Providing
Healthcare Services
● Introduction
● Basic Business Functions
● Changes in the Business of Providing
Healthcare Services
● Stakeholder Analysis
● Applying Analytics

CERTIFIED SPECIALIST
BUSINESS INTELLIGENCE
Study Guide
Certified Specialist Business Intelligence
Table of Contents
Course 1: Understanding the
Industry………………………………………………………………
……………………………………..3
Course 2: The Business of Providing Healthcare
Services………………………………………….……………………
………..8
Course 3: The Discipline of Business
Intelligence……………………………………………………………
………………………11
Course 4: Business Intelligence Technical
Skills…………………………………………………………………
…………………..14

Course 5: Business Intelligence Analytical and Quantitative
Skills………………………………………………………….17
Course 6: Relationship, Change Management and Consulting
Skills……………………………………………………….21
Course 1: Understanding the Industry
Introduction: This module provides an overview of the changing
healthcare industry for the healthcare
business intelligence consultant. The topics discussed include
healthcare service delivery components,

healthcare delivery environment, healthcare services in relation
to the health continuum, reform and
change in healthcare delivery and the key points of leverage
that analytics brings into the healthcare
industry.
Learning objectives
Section 1: Business Intelligence for the Healthcare Industry
• Define the phenomenon big data.
• Define and illustrate the applicability of and need to engage
use of small data.
Section 2: Healthcare Services Delivery Components
• Recognize the internal components of healthcare service
delivery.
Section 3: The Broader Healthcare Delivery Environment
• Recognize the key external influencers of the healthcare
delivery environment.
Section 4: Health Services Across the Health Continuum

• Identify the three areas where misalignment between hospital
components and healthcare
users may occur.
• Identify the services performed at various points on the health
continuum.
Section 5: Healthcare Service Delivery and Component
Independence
• Recognize what strongly influences medical care decisions in
regards to supply-sensitive care.
Section 6: Reform and Change in Healthcare Delivery
• Identify foundational drivers for change that are taking place
in the industry.
Section 7: HIPAA and HITECH
• Define the terms HIPAA and HITECH.

Key points to remember:
Big data is understanding and using combinations of large data
sets, both clinical and non-clinical, which
are generated by healthcare industry organizations in the course
of doing business. The definition of big
data is the same in the non-healthcare industry, such as retail,
communications, media, socio-
demographic and education, etc. We are coming to know this
phenomenon as big data.
The internal components of healthcare service delivery system
are identified on the following graphic.

Key external influencers of the healthcare delivery environment
include the following:
• Economic factors: General economy, consumer sentiments and
demand elasticity, economic
development
• Social values: Diversity, social cohesion, established
precedents for actions, religious preferences
• Global influences: Immigration, vacation travel, medical
tourism, epidemics, terrorism, demands
for equity in medication distribution
• Population characteristics: Population demographics, socio-
economics, morbidity related to
ethnic and gender groups, social morbidity
• Political climate: Elected officials, interest groups
• Technology development: Engineering sciences, information
science, decision management,
mathematics
• Physical environment: Pollution, sanitation

• Demand elasticity: Market liquidity
There are three areas where a misalignment between hospital
components and healthcare users may
occur:
• Lack of coordination
• Healthcare users on their own
• Service coordination
Consumer Health Conditions:
Medical services provided on the continuum of care are
identified on the graphic below.
In the case of supply-sensitive care, according to Wennberg et
al. “Decisions surrounding medical

necessity are strongly influenced by capacity, rather than
medical evidence or severity of illness.”
The foundational drivers of change within the healthcare
services delivery system include the following:
• Transparency
• Understanding costs
• Community-based services
• IHI Triple Aim
HIPAA = Health Insurance Portability and Accountability Act;
HIPAA applies to organizations that are
defined as a covered entity (CE) and, now, directly to business
associates as well.
• Sections of HIPAA
o Privacy Rule
o Security Rule

HITECH = Health Information Technology for Economic and
Clinical Health Act.
• HITECH covers application of the rule:
o to both CE and individuals (i.e., employees)
o to business associate contractors
• Breach notification requirements ; Accounting of PHI
disclosures; Allows for sanctions for non-
compliance, including fines of up to $1.75 million and 10 years
imprisonment
Elements of HIPAA and HITECH cover how PHI is handled and
protected. Handling and protecting PHI is
an important aspect of BI/analytics work.
Course 2: The Business of Providing Healthcare Services
Introduction: This course furnishes insights into the business of
providing healthcare services. The topics
discussed include the basic business functions of finance,

marketing and operations vis-à-vis the
business of providing healthcare services, the role of decision
support, the stakeholders in the business
and their analysis, and finally, the financial processes involved
in the business.
Learning objectives:
Section 1: Introduction
• Identify the fundamental purpose of engaging in analytics.
Section 2: Basic Business Functions
• Recognize the basic business functions of finance, marketing
and operations.
Section 3: Changes in the Business of Providing Healthcare
Services
• Recognize the dimensions of changes in the work and
relationships of players in the business of
providing healthcare services.
Section 4: Stakeholder Analysis
• Recognize the steps involved in a stakeholder analysis
process.
Section 5: Applying Analytics
• Recognize the three general way to access productivity.

Engaging analytics is key to understanding what is happening
and to finding a path forward.
Operations is the function that meets the demand for a service
or product (an output that might be
traditionally thought to be the focus of operations) by
marketplace entities.
An organization must have a financing function to ensure that
monetary resources are available to
conduct operations.
The marketing function provides the market interface function
that is focused on understanding what
the marketplace overtly seeks, specifically needs, anticipating
shifts and ensuring a strong marketplace
presence.
The players involved in the business of providing healthcare
services dimensions of change include the

following:
• Role of Nurses: CHI’s floor nurses will move beyond the
traditional role of supportive bedside
care and following physician orders to an integrated role within
a team-based model of care
with a focus on standardized ways of work aimed at reducing
variability in practice and
improving outcomes.
• Role of Case/Care Managers: This role will be driven, in
particular, by the focus on mitigating
and minimizing 30-day readmissions.
• Quality and Performance Improvement: Work will be
performed in direct collaboration with
clinicians, clinical informaticists, decision-support
professionals and patient access team
members.
• Operational Management Decision: There will be an increased
focus on procurement sourcing
and management of suppliers and supply lines rather than on
managing inventory and
processing orders.
• Decision support becomes a BI/Analytics function: The future

holds the development of a of
BI/Analytics practitioner working in concert with clinical
informaticists - most likely Nurse
informaticists - unlocking the big data and surfacing and
sharing data.
• Internal Financial and Payer Experts: These professionals
must work closely with their external
counterparts.
• Providers, Suppliers and Payers: Providers must work in
concert with suppliers and payers.
The four steps involved in the stakeholder analysis process are
as follows:
1. Identifying stakeholders.
2. Analyzing stakeholders’ profiles.
3. Analyzing stakeholder relationships.
4. Analyzing stakeholder participation.
The three general ways to assess productivity are:
• Partial productivity
• Partial productivity is concerned with efficiency of one

particular characteristic.
• Partial productivity measures output against a specific input,
e.g., services rendered/employee.
Multifactor Productivity (MFP)
• Multifactor productivity is an index of output obtained from
more than one of the resources
used in product/service production.
• MFP is the ratio of output to a group of inputs, such as labor
and material.
Total Productivity
• Total productivity is the broadest measure of productivity and
is concerned with the
performance of the entire organization.
• Total Productivity includes all inputs in an organization, i.e.,
labor, materials, overhead, capital.
• Total productivity = Revenues, profits/all inputs

Course 3: The Discipline of Business Intelligence
Introduction: This section provides an overview of the
discipline of business intelligence, as applied to
the business of healthcare service delivery for the improvement
of decisions. It includes the types of
analytics and examples, timeframe-based viewpoints that
engaging analytics provides and presents
these viewpoints in relation to decision-making power
generated. This section will also discuss the
concept of decision management, decision types and analytic
tools.
Learning Objectives:
• Define the term business intelligence.
Section 2: Business Intelligence Defined: Types of Analytics
• Identify three types of analytics.

Section 3: Business Intelligence Basics
• Identify areas that may provide significant opportunities for
improved organizational
performance if analytics are applied.
Section 4: Business Intelligence Provides Decision Making
Power
• Identify areas that may provide significant opportunities for
improved organizational
performance if analytics are applied.
Section 5: Engaging Business Intelligence for Improved
Intelligence
• Identify the three automation levels related to any analytic
type.
This section has covered the three types of analytics:
descriptive, predictive and prescriptive. We have
also covered how they can be used related to:
• Departmental KPIs (moving these beyond the current static
monitoring lagging indicators to

enable development of co-incident and leading indicators
driving action)
• addressing daily operational issues causing poor outcomes and
drivers of significant cost, such
as addressing potential sepsis situations, or staffing: agency
versus overtime or poorly staffed
units
The examples provided illustrate that well-displayed analytics
output is truly a key method to simplify
the data and amplify the meaning.
We introduced focus related to decisions and application of
analytics. The focus should be on
continuous operating/process decisions (e.g. sepsis situation
mitigation) rather than focused on one-off
situations and/or infrequent project/issues.
Lastly, organizations have to determine how to embed the use of
these analytic tools firmly into the

organizational decision-making process/workflow - linking the
insights to decisions to taking ACTION -
through appropriate automation of decisions.
Business intelligence is a set of methodologies, processes,
architectures and technologies that
encompass the three types of analytics. It is a broad category of
applications and technologies for
gathering and analyzing data, transforming it into accurate,
current and relevant actionable information
and deploying it to users to be available for the purpose of
helping enterprise users make better
business decisions.
The three types of analytics:
• Descriptive analytics provides a look at, and possibly an
understanding of, past performance.
• Predictive analytics is the practice of relating what you do
know to what you do not know,
providing better information that is valuable when a decision is
needed.
• Prescriptive analytics is a new and still emerging area that
uses hybrid data along with business

• rules and mathematical models to indicate what should be
done.
The areas of significance for analytic application are:
• Data-rich: EHR/Revenue Cycle/DRG
• Information-intensive: EHR and Revenue Cycle/DRG/ICD
codes
• Asset-intensive: OR and ED room use
• Labor-intensive: Clock time versus unit volume
• Dependent on speed and timing
• Dependent on consistency and control: Patient access areas
• Dependent on distributed decision-making: Population health
management decisions across
medical homes
• Cross-functional and cross-business in scope: 30-day
readmission
• Low average success rate: Could be anywhere

The three decision-making viewpoints:
• Hindsight: Perception of the significance and nature of events
after they have occurred.
• Insight: The capacity to discern the true nature of a situation;
knowledge derived from modeling
and experimentation.
• Foresight: Perception of the significance and nature of events
before they have occurred; care in
providing for the future; prudence; the act of looking forward
Automation levels related to any analytic type:
• Fully automated: Decisions are within a process flow that
triggers subsequent process flow(s)
and decisions
• Partially automated: Indicates exceptions, overrides desired
outcomes and is specifically built in
• Assisted prediction: This level is complex, revealing
unpredictable or unprecedented variables
and mathematical models to indicate what should be done.

Course 4: Business Intelligence Technical Skills
Introduction: This course provides an overview of business
intelligence technical skills, including how to
apply the concepts and tools of BI to understand what to work
on and how, as well as how to use
database and related report-writing applications. The section
also provides explanations of business
intelligence applications and approaches that are used to derive
information from large clinical,
financial, and other databases to support better decision-
making. Methods of presenting and displaying
information in a clear manner are also discussed.
Learning objectives:
• Identify the fundamental goal of business intelligence
analytics.
Section 2: The Basics
• Identify the attributes related to database and reporting

application usage and output in
healthcare provider organizations.
Section 3: Getting it Done
• Identify the five key Power Decision attributes related to real -
time decision making.
Business Intelligence (BI) analytics: The goal is to obtain the
information that addresses the questions or
issues at hand. We can refer to this as one truth, and this one
truth needs to be clearly conveyed when it
matters.
Historically, healthcare provider organizations’ use of databases
and reporting has been narrowly
directed and concentrated with concomitant issues:
• The BI/analytics work traditionally performed, and much of
the work done today, is a decision-
support function involving the framing and formatting of
reports and relatively basic descriptive
analytics, if any analytics at all.
• This work in health care often is still performed within the
silos of individual process
applications.

• Most of this work has been financially focused in nature.
• This work is typically based on performing recurring, routine
reporting and analysis.
• Regardless of the approach, the output is typically of a
simplistic, descriptive and analytic nature
providing quantities, comparisons, percentiles and maybe trend
lines on graphs.
• Most often, application report writers are insufficient to reveal
the information needed for
powerful decision-making.
The five key Power Decision attributes are:
• Targeted results
• Replicable - done in the same way, repeatedly
• Adaptable to differing circumstances
• Expeditious
• Low cost
Reporting and Analysis Tools:

Course 5: Business Intelligence Analytical and Quantitative
Skills
Introduction: This course is designed to place statistical work in
the proper context so that it can be
leveraged most effectively in driving organizational
performance through Business Intelligence (BI). This
course provides an overview of the analytical and quantitative
skills required in BI. It also elaborates
upon the rudiments of experimental design, sampling, common
mistakes of analysis, how to seek
opportunities and problems to solve, meaningful analytic
structures and how to work through a
situation. The course also provides an example in the form of a
case.
Section 1: Thinking About the Basics

• Recognize the interconnected relationship between various
processes and tools used in business
intelligence analysis
Section 2: The Basic Elements of Experimental Design
• Identify the intended outcome of an experiment.
Section 3: Sampling
• Identify the primary purpose of sampling.
Section 4: Common Mistakes in Analysis
• Identify key common mistakes made in business analytics.
Section 5: Opportunities and Problems to Solve
• Illustrate methods for identifying areas of research questions,
issues to be resolved,
opportunities for improvement when considering the application
of analytics resources.
• Recognize the six steps that comprise the prioritization matrix
method for high-level sorting.

Section 6: The Low Severity Level ED (SL5P) Case Setup as an
Example of BI Work
• Recognize the components of the iterative process of creative
analytic thinking engaged by
BI/Analytics consultants.
Section 7: Meaningful Analytic Structures
• Identify the critical resource allocation issues that must be
addressed outside of the clinical
services delivered.
The interconnected relationship between various processes and
tools used in business intelligence
analysis are as follows:

The experiment provides insight into true cause-and-effect by
demonstrating what outcome occurs
when a particular factor is manipulated.
A sample is the data set used to make inferences about the
entire population.
The common mistakes made in business analytics are as
follows:
• Sophistication compensating for a lack of data
• Difficulty isolating and explaining patterns shown by data
• Equating correlation with causation
The six steps that comprise the prioritization matrix method for
high-level sorting are as follows:
Step 1: Develop a list of items in the following categories,
which also can be classified as within an ASAA.
Step 2: Each characteristic on the left should be weighted as a
fraction of 1.0, so that item ratings can be
compared.
Step 3: Rate each item’s performance related to each
characteristic, with 1 being low and 5 being high.
Step 4: Multiply the ratings by the weight to obtain an item
score.

Step 5: Compare scores to see priority focus areas.
Step 6: Be sure analytics of all three types are developed and in
use.
BI/Analytics consultants will be asked to address situations like
that in the following example. It is an
iterative process of creative analytic thinking -
preparation/immersion/incubation/insight - that the
BI/Analytics consultant must engage.
Directly linking and recognizing interplay between healthcare
user condition, service location, cost and
coverage are critical resource allocation issues that need to be
addressed outside of the clinical services
delivered.

Course 6: Relationship, Change Management and Consulting
Skills
Introduction: This course provides an overview of the way in
which the business intelligence consultant
can lead and manage change, handle relationships and hone
consulting skills in the changing healthcare
delivery environment. The topics discussed include exercising
influence and stimulating action, finding
opportunity and seizing it, communicating the analytic process
and information and proving of the
BI/Analytics consultant.
Section 1: Leading Change
• Identify the significance of the six leadership styles
Section 2: Finding Opportunity
• Identify how performance is viewed in change management.
Section 3: Communication Within the Organization
• Identify the payoff related to involving directors, managers or
other staff members in the

experiment design process.
Section 4: Proving Value
• Recognize the outcomes of working with clinical
informaticists.
Leadership Styles and Competencies:
The six leadership styles provide guidance in how to exercise,
influence and stimulate action in different
circumstances.
• Authoritative
• Democratic
• Affiliative

• Coaching
• Coercive
• Pacesetting
Performance, as viewed using external benchmarks and
predictive analytics to perform what if testing
and optimization analysis, will deliver predictions of work
volume and the organization-defined specific
resources needed to provide services for this volume.
The real payoff when involving directors, managers or other
staff members in the experiment design
process is threefold:
• The group will have a greater level of understanding and
analytic sophistication
• An outcome will be defined in advance in terms the
stakeholders understand (negotiating with

key stakeholders and managing expectations)
• Policies and practices, whether they are good, absent or
lacking in performance, will become
transparent and can be appropriately addressed.
Working with clinical informaticists can lead to much richer
experimentation and analysis, such as
investigation of particular clinical factors, interventions,
processes, outcomes, etc. related to operational
aspects (such as unit coverage, timing of shifts, availability of
supplies, etc.).

CSBI Course 1 Understanding the Industry

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