CSBI Journal

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

Certified Specialist Business Intelligence

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.

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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.

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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

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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.”

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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.

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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.

Key points to remember:

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.

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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.

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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

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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:

Section 1: Introduction

• 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.

Key points to remember:

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)

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• 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

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• 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.

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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:

Section 1: Introduction

• 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.

Key points to remember:

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.

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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:

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Course 5: Business Intelligence Analytical and Quantitative Skills

Learning Objectives:

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

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• 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.

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Key points to remember:

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.

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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.

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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.

Learning Objectives:

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.

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Key points to remember:

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.

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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.).