Voices 2014 Role of Analytics in Delivering Health Information to help fight Cancer in Australia Katerina Andronis, Deloitte Consulting, Australia and Chandana Unnithan, Deakin University, Australia

1. Role of analytics in delivering
health information to help fight
cancer in Australia
Katerina Andronis
(Deloitte, Melbourne)
&
Chandana unnithan
(Deakin University)

2. Background
 Challenges in Health Information Management is about appropriate
data governance that is; using, analysing and understanding health
data is managed properly so everyone is on the “same page” when
accessing and using data (Only oranges, not apples and oranges!)
 Robust management of an organization’s data assets is a mixed bag
in the health environment - there are areas of good structured
codified data and other unstructured valuable data that cannot be
used for data mining, management and research opportunities.
 Australian Health sector is complex and not well integrated. Healthcare
funding, delivery and management are changing – these rely critically on
information management.
 Detailed asset utilization management and strong financial analysis are
necessary to understand service costs and optimize revenue. This is critical
for financial viability under an Activity Based Funding regime which is currently
codified and provides accurate and rich information
March 7, 2014
2
2

3. Health Sector
 The health sector is one of the most complex
organisations of any industry.
 The entire clinical overlay with its obvious importance and
potential for impact tends to overshadow other
information governance perspectives.
 This may support the creation and use of clinical data for
clinical purposes but generally does not address nonclinical information domains or properly manage clinical
information to support broader use.
 Most health organisations have various degrees of data
governance and are currently coming to grips of the
importance and the impact of a lack of data governance
March 7, 2014
3
3

4. Big Data in Health
 Data is primarily created in the context of individual
service delivery processes and is often fragmented
and not sufficiently well formed to support the
required analysis.
 Data is a “lateral asset” spanning multiple functional
areas. It is used for multiple purposes across the
health care organisation and in ways that may not
be known or seem important in the context of where
the data is created.
 Effective management is challenging, especially
considering that this “lateral” characteristic does not
necessarily align well with organisational
management arrangements.
March 7, 2014
4
4

5. Data Governance – Selected Definitions
The data management association
Data governance is the exercise of authority and control (planning, monitoring and
enforcement) over the management of data assets.
International association for information and data quality
The management and control of data as an enterprise asset.
“Governance” is what information management is mostly all about. Information management is
the process by which those who set policy guide those who follow policy.
Governance concerns power and applying an understanding of the distribution and sharing of
power to the management of information technologies.
(from Paul A. Strausmann’s work circa 2001).
Providing management and control over enterprise information assets in order to harness
maximum value.
5

6. Data governance – common
themes
Data is an asset
Key point
There is nothing new here.
These statements are fairly
self-evident and we believe
they would be generally
accepted as valid.
So conceptually it is not
difficult – the challenge is in
giving form and substance
to the concepts
6
So data is recognised as having value but the more common perspective is that poor data quality
causes harm (rather than data being valued per se).
Governance involves authority and control
Governance therefore involves people with appropriate authority and there must be defined control
processes through which governance can be exercised. It can be inferred that there should be
appropriate standards which the controls are intended to achieve.
There should be an understood and agreed purpose
For data governance to be meaningful (and to help understand when enough has been done) there
must be a known purpose. This should be well defined with a clear means of assessing compliance.

7. Data Governance
 What is data governance in this context?
 Is data governance being done?
 The business imperatives
 A data governance framework
 Data governance in a health care provider
 Valuing and tackling data governance
7

8. Basis of informal research
(IAIDQ)
Strategy and governance
Definition
Strategy
We have defined and implemented an
information quality strategy designed
to manage information as an asset
Standards
We have defined information quality
principles, policies, and standards that
are used to guide decisions and
actions affecting information quality
Management
We have implemented a data
governance model covering key roles
and responsibilities, formalised
accountability, established decision
rights, and identified channels for
management actions related to
managing our data
Environment and culture
Accountability
We have defined accountabilities for
information quality across all functions
throughout the organisation
Data governance is the definition and
exercise of authority and control over
data assets encompassing the entire
data
lifecycle(creation, storage, access, use,
archiving, disposal).
Measurement and monitoring
Education
We actively educate management and
staff regarding data quality and our
approach to managing it
Measurement
There are well defined data quality
standards, and associated reporting
Process
Personnel can readily access the
information they need to understand
data quality requirements and
processes related to their jobs
Monitoring
Achievement of data quality standards
is actively monitored and compliance
is an accountable element of job
responsibilities
Sustaining information quality
Question responses
Projects
Data quality implications are actively
and appropriately addressed during
computer application implementation
or upgrade projects
8
Operations
Information quality is explicitly built
into our business operations,
processes and systems
1. Haven’t started to do this
2. Have made a start but it’s early days
3. Significant progress but not complete
4. Have largely completed and embedded
Based loosely on IAIDQ framework

9. Preliminary Results
Largely complete
Key point
Data governance
is not a
significant
capability within
health care
providers
Significant progress
Started
Haven’t started
9

10. The information challenge for
health care providers
Key point
Much of the work in these
areas is process- and
system- related, but
sustainable capability and
improvement requires the
allied data governance to be
in place to ensure that data
is defined and captured
correctly and can be reliably
used for
accounting, management
and analysis purposes.
Activity based funding pays for the health service outputs delivered at an established “
efficient price” which requires diligent counting/billing processes and an accurate knowledge
of service cost.
So, from a revenue perspective
• Need to manage patients and services with a view to best revenue alignment and
reduced revenue leakage within obligation framework and acceptable practices
• Need to code promptly and accurately under appropriate guidelines
• Need to identify and rectify individual DQ problems not “code around” them or rectify
on best-efforts basis after the fact.
… and from a cost perspective
• Ideally need to understand cost per service instance
• Need detailed current service profitability reporting and trended reporting
• Need to understand cost driver and levers.
Then there are the rules
• Significant funding, regulatory and compliance requirements.
10

11. Health service output functional footprint
Many areas are involved directly and indirectly in delivery of funded health care outputs.
Specialty
Clinical
Service
Delivery
Cathlab &
HDU & Cardiology
ICU
IPU
Services Services
Theatre
Services
Mgmt
Medical &
Rapid Women’s/
Surgical Assessment Children’s
&
Inpatient Medical Paediatric
Services
Unit
Services
Mgmt
Services
Mgmt
Mental
Health Community
Inpatient
Services
Services
Mgmt
Mgmt
Cancer
IPU
Services
Inpatient Ambulatory
Services
Services
Mgmt
Mgmt
Hotel
Services
Care Delivery Support Services
Federal
Government
Research
Networks
Reporting
Directories
Pharmacy
Services
Pathology
Services
Patient
Information &
Health Records
Management
Specialist
Consulting
Services
Imaging
services
Integration
Patient ID
PCEHR
Payments
Corporate
Network
Transport
Services
Allied Health
Services
Interpreter
Services
Transcription/
Typing Services
Specialist
Testing
Services
Transit Lounge
Services
Education & Research Services
Document
Management
Service
Library Services
Data Extraction,
Storage &
Analysis Service
State Dept.
Health Network
Finance system
Clinical system
Identity
Resources &
Appointment
Management
Research
Collaboration
Services
Publishing
Services
Research Unit
Specific
Services
Professional
Development &
Education
Services
Simulation
Services
External Clinical
Knowledge
Sources
Customer
Mgmt
Clinical Care Management
Clinical Knowledge
Theatre
Clinical
Care
Mgmt
Risk
Management &
Continuous
Improvement
Patient Management
Critical Care
Management
Care Planning & Management
MediHotel
Internal Clinical
Knowledge
Sources
3 Party Testing
Services
Sub-Acute
Mental Health
Patient & Client Management
Home &
Emergency Community Out-patient
Management Based Care
Mgmt
Services
(HIH)
rd
Inpatient
Appointment & Access Management
Satellite Site &
Partner Access
Remote Clinical Access
Quality Services
Emergency
Clinical
Services
Management
Real-time
Tracking
Critical Care
Hospital Based Access
Audit Services
Ambulatory Services
Public Health Access
Incident
Reporting &
Management
External &
Onsite Access
Home Access
Real-time Data
Access & Capture
GPs, Specialists, MultiDisciplinary Teams &
Tele-medicine
Patients &
Citizens
Clinical Reporting (Audit, Risk & Performance)
Remote monitoring
Tele-medicine
Operational Support Services
Biomedical
Engineering
Services
Cleaning
Services
Building &
Engineering
Maintenance
Management
Manage
Material
Distribution &
Logistics
Laundry
Services
GP/Specialist
Procurement
Patient & Staff
Food Services
Clinical
Operations
Support
Equipment
Distribution &
Management
Mortuary
Services
Mail Room &
Courier Services Waste Services
Reception &
Switchboard
Management
Customer
Service
Management
Business Support Services
Internet
Volunteer &
Fundraising
Services
Manage
Accounting &
Financial
Decision Support
Manage
Capital & Risk
Human
Resource
Management
Manage
Capital
Projects
Manage
Payroll
Manage Staff
Rostering
Other Network
Not health
service output
funded
11
Health service
output funded
Procure
Materials &
Services
ICT
Management
Plan & Manage
Business
Business/
Statutory
Reporting &
Analysis
Security
Services
Management
Legal Services
Management

12. Strategic
Alignment
Capacity planning
Service delivery
management
Capacity planning
Patient Care Services
utilisation analysis
Patient care costing
analysis
Clinical Care Support
utilisation analysis
Clinical Care costing
analysis
Casemix funding
Capacity planning
Capacity planning
Business and capital
planning
Service delivery
management
Service delivery
management
Service delivery
management
Non-clinical Care
utilisation analysis
Operation Support
utilisation analysis
Inventory
management
Research project
management
Rostering and
workload analysis
Incident reporting
and management
Cost analysis
Costing analysis
Costing and funding
analysis
Education service
delivery
Remuneration
analysis
Quality monitoring
and analysis
Revenue analysis
Capital project
management
Training and
accreditation
Risk management
Asset management
Accreditation
compliance
Patient flow analysis
Personnel
management
Human
resources
Audit and risk
Financial
management
Costing analysis
Casemix funding
Education and
research strategy
Workforce capacity
planning
Audit/risk mgt
planning
Financing strategy
Capital analysis
Dimensions
Decision Support
Health service output revenue
information footprint
Information Groups and Subjects
Patient care
services
Clinical care
support
Non-clinical
care support
Operational
support
Business
support
Education and
research
Demographic data
Clinical results
Appointments
Operational
support mgt data
Volunteer and
fundraising
Education content
Employees
Risk data
General Ledger
Inpatient episodic
data
Medication data
Care delivery
support resources
Operational
support services
Procurement
Education events
and records
Recruitment and
Terminations
Incident data
Revenue
Billing data
Medical images
Care delivery
support events
Customer service
data
Capital projects
Research projects
Payroll
Audit data
Costing
Ambulatory event
data
Clinical
information
Supply and
inventory
Security
management data
Research data
Rostering
Project Accounting
Engineering and
maintenance
Legal services data
Publications
Credentialing
Asset accounting
Clinical coding
data
Employee
performance
Patient Administration
Data sources
Patient
Admin
System
Patient
billing
ICD coding
Client
management
Community
care
Emergency
department
management
Clinical care
delivery support
Pathology
Radiology
Business support
Audit & Risk
Biomedical
engineering
Laundry
Waste
management
Human
Resources
Security
Services
Financial
Risk
Building and
engineering
maintenance
Supply
Research
Customer
service
management
Rostering
Procurement
Capital
Project
Quality
Library
Cleaning
services
Mortuary
Call
Management
Payroll
Legal
Services
Asset
Audit
Food services
Equipment
management
Credentialing
Volunteer &
Fundraising
Publishing
Theatre
Mental
Health
Resource
scheduling
Anaesthetic
Operational support
Education &
Research
Transport
management
Medication
management
12
Non-Clinical
care delivery
support
Specialist
clinical
Dictation
system
Document
management

13. Health service output costing functional footprint
Many areas directly incur costs, or incur costs that are attributed to the delivery of health service outputs
Specialty
Clinical
Service
Delivery
Cathlab &
HDU & Cardiology
ICU
IPU
Services Services
Theatre
Services
Mgmt
Medical &
Rapid Women’s/
Surgical Assessment Children’s
&
Inpatient Medical Paediatric
Services
Unit
Services
Mgmt
Services
Mgmt
Mental
Health Community
Inpatient
Services
Services
Mgmt
Mgmt
Cancer
IPU
Services
Inpatient Ambulatory
Services
Services
Mgmt
Mgmt
Hotel
Services
Care Delivery Support Services
Federal
Government
Research
Networks
Reporting
Directories
Pharmacy
Services
Pathology
Services
Specialist
Consulting
Services
Imaging
services
Integration
Patient ID
PCEHR
Payments
Patient
Information &
Health Records
Management
Resources &
Appointment
Management
Corporate
Network
Allied Health
Services
Interpreter
Services
Transcription/
Typing Services
Specialist
Testing
Services
Transit Lounge
Services
Education & Research Services
Document
Management
Service
Library Services
Data Extraction,
Storage &
Analysis Service
Research
Collaboration
Services
State Dept.
Health Network
Finance system
Clinical system
Identity
Transport
Services
Research Unit
Specific
Services
Publishing
Services
Professional
Development &
Education
Services
Simulation
Services
External Clinical
Knowledge
Sources
Customer
Mgmt
Clinical Care Management
Clinical Knowledge
Theatre
Clinical
Care
Mgmt
Internal Clinical
Knowledge
Sources
Patient Management
Critical Care
Management
Care Planning & Management
MediHotel
Risk
Management &
Continuous
Improvement
Sub-Acute
Mental Health
Patient & Client Management
Home &
Emergency Community Out-patient
Based Care
Management Services
Mgmt
(HIH)
3rd Party Testing
Services
Inpatient
Appointment & Access Management
Satellite Site &
Partner Access
Remote Clinical Access
Quality Services
Emergency
Clinical
Services
Management
Real-time
Tracking
Critical Care
Hospital Based Access
Audit Services
Ambulatory Services
Public Health Access
Incident
Reporting &
Management
External &
Onsite Access
Home Access
Real-time Data
Access & Capture
GPs, Specialists, MultiDisciplinary Teams &
Tele-medicine
Patients &
Citizens
Clinical Reporting (Audit, Risk & Performance)
Remote monitoring
Tele-medicine
Operational Support Services
Biomedical
Engineering
Services
Cleaning
Services
Building &
Engineering
Maintenance
Management
Manage
Material
Distribution &
Logistics
Laundry
Services
Patient & Staff
Food Services
GP/Specialist
Procurement
Clinical
Operations
Support
Equipment
Distribution &
Management
Mortuary
Services
Mail Room &
Courier Services Waste Services
Reception &
Switchboard
Management
Customer
Service
Management
Business Support Services
Internet
Volunteer &
Fundraising
Services
Manage
Accounting &
Financial
Decision Support
Manage Capital
& Risk
Human Resource
Management
Manage
Capital
Projects
Manage Payroll
Manage Staff
Rostering
Procure
Materials &
Services
Other Network
Other cost
element
13
Direct cost
element
Indirect
cost
element
ICT Management
Plan & Manage
Business
Business/
Statutory
Reporting &
Analysis
Security Services
Management
Legal Services
Management

14. Strategic
Alignment
Capacity planning
Service delivery
management
Capacity planning
Patient Care Services
utilisation analysis
Clinical Care Support
utilisation analysis
Patient care costing
analysis
Clinical Care costing
analysis
Casemix funding
Capacity planning
Capacity planning
Business and capital
planning
Service delivery
management
Service delivery
management
Service delivery
management
Non-clinical Care
utilisation analysis
Operation Support
utilisation analysis
Inventory
management
Research project
management
Rostering and
workload analysis
Incident reporting
and management
Cost analysis
Costing analysis
Costing and funding
analysis
Education service
delivery
Remuneration
analysis
Quality monitoring
and analysis
Revenue analysis
Capital project
management
Training and
accreditation
Risk management
Asset management
Accreditation
compliance
Patient flow analysis
Personnel
management
Casemix funding
Costing analysis
Education and
research strategy
Workforce capacity
planning
Audit/risk mgt
planning
Financing strategy
Capital analysis
Dimensions
Decision Support
Service costing information
footprint
Information Groups and Subjects
Patient care
services
Clinical care
support
Non-clinical
care support
Operational
support
Business
support
Education and
research
Human
resources
Audit and risk
Financial
management
Demographic data
Clinical results
Appointments
Operational
support mgt data
Volunteer and
fundraising
Education content
Employees
Risk data
General Ledger
Inpatient episodic
data
Medication data
Care delivery
support resources
Operational
support services
Procurement
Education events
and records
Recruitment and
Terminations
Incident data
Revenue
Billing data
Medical images
Care delivery
support events
Customer service
data
Capital projects
Research projects
Payroll
Audit data
Costing
Ambulatory event
data
Clinical
information
Supply and
inventory
Security
management data
Research data
Rostering
Project Accounting
Engineering and
maintenance
Legal services data
Publications
Credentialing
Asset accounting
Clinical coding
data
Employee
performance
Patient Administration
Data sources
Patient
Admin
System
Patient
billing
ICD coding
Client
management
Community
care
Emergency
department
management
Clinical care
delivery support
Pathology
Radiology
Business support
Audit & Risk
Biomedical
engineering
Laundry
Waste
management
Human
Resources
Security
Services
Financial
Risk
Building and
engineering
maintenance
Supply
Research
Customer
service
management
Rostering
Procurement
Capital
Project
Quality
Library
Cleaning
services
Mortuary
Call
Management
Payroll
Legal
Services
Asset
Audit
Food services
Equipment
management
Credentialing
Volunteer &
Fundraising
Publishing
Theatre
Mental
Health
Resource
scheduling
Anaesthetic
Operational support
Education &
Research
Transport
management
Medication
management
14
Non-Clinical
care delivery
support
Specialist
clinical
Dictation
system
Document
management

15. Compliance requirements and standards
Privacy Act (state based variations)
Regulates how personal information is handled (captured, accurately maintained, stored, used,
disclosed and disposed of)
Freedom of Information Act 1982
Framework for access to information held by the state or institutions.
Burden of proof falls on the information provider to explain non-provision.
Australian Council on Healthcare Standards (ACHS) EQuIP5
Accreditation standard for private and public hospitals.
The non-mandatory information (system) related standards are:
Key point
Data governance
appears to be largely
confined to a direct
response to mandatory
compliance areas
2.3 Information management systems enable the organisation’s goals to be met.
2.3.1 Health records management systems support the collection of information and
meet the consumer / patient and organisation’s needs.
2.3.2 Corporate records management systems support the collection of information and
meet the organisation’s needs.
2.3.3 Data and information are collected, stored and used for strategic, operational and
service improvement purposes.
2.3.4 The organisation has an integrated approach to the planning, use and
management of information and communication technology (I&CT).
Health Level 7 (HL7)
Messaging specification for clinical and administrative information to enable (system
interoperability. Adopted by the Australian health sector and e-health community, and software
providers as a data transfer standard.
International Statistical Classification of Diseases and Related Health Problems (ICD-10
Standard for codifying diseases, signs and symptoms, abnormal findings, complaints, social
circumstances, and external causes of injury or diseases.
Mandatory and fundamental to billing, costing and Activity Based Funding.
15

16. Data Governance framework - overview

An effective Data Governance framework
includes the following elements:

Principles: Define the high level objectives
(mission statements) for Data Management

Organisation: Defined roles and
responsibilities, defined accountability for meeting
objectives, strong executive leadership &
commitment from
Business/IT stakeholders

Policies: Translation of the guiding principles into
pragmatic, actionable and measurable
organisational objectives including adherence to
standards, monitoring and continuous improvement

Standards and processes: Standards promote
common terminology and data definitions across the
enterprise, including quantitative metrics for data
quality
Processes provide procedural direction over how the
Governance organisation will operate

16
Technology: Technology tools and practice
capability that enable definition, execution and
compliance measurement of data governance
policies, standards and processes.

17. Cascading dependencies across framework
Guiding principles
Foundational capabilities required to achieve excellence in Data Management
Provides the high level
objectives for DM Policies
Provides traceable
requirements to principles
Policies
The mechanism for translating guiding principles into pragmatic, actionable and measurable organisational objectives
which will deliver upon the overarching objectives of DM
Informs how & when policies will be
executed and compliance measured
Direct the formalisation of standards
to achieve an outcome
Standards
Define the minimum requirements for data management, including data definition, quality and control
standards to deliver upon the policies of the organisation.
Provides the boundaries for the
processes to achieve the standards
Inform how the minimum
standards can be met
Processes
Define the “how to” aspect of standards, detailing the logical sequence of tasks to achieve and measure
the standards and policies set out by the organisation.
17

18. Organisation overview – Key Actions
• Establish functional organisation capability to manage, deliver,
and ensure quality data
• Enable the business areas to move beyond a project or program
centric approach to an enterprise data management capabilities
• Establish Data Owners that are accountable for decision making,
monitoring and continuous improvement of data assets
• Establish Data Working Teams, comprised of information
specialists within each data domain to drive development of
enterprise policies, standards and processes for effective
management of data
Promote global enterprise stewardship of information in
accordance with defined data policies, standards and processes.
Managing Information
as a Strategic Asset
Governance Framework
Organisation
Policies
Standards &
Processes
18
Founded on Principles
Technology

19. Policies overview – Key Actions
• Translate guiding principles into
pragmatic, actionable and measurable
organisational objectives
• Develop and document minimum expectations
for the management of data, such as
security, data quality and controls
• Identify and document roles within the
organisation which will be tasked to comply with
these policies, in addition to those who will
monitor the adherence to them
• Provide the framework for the creation of
standards and processes, ensuring clear
traceability to guiding principles.
Managing Information
as a Strategic Asset
Governance Framework
Organisation
Policies
Standards &
Processes
Founded on Principles
19
Technology

20. Standards & processes overview – Key Actions
• Define compliance and monitoring standards, including
frequency of auditing
• Develop enterprise terms and definitions for data,
promoting common structures, codification rules and
naming conventions
• Define data quality standards
• Define security, accessibility and control standards
• Develop processes to effectively govern data throughout its
lifecycle, including clear guidelines and accountability for
change control, issue management, impact assessment
and communications
Managing Information
as a Strategic Asset
Governance Framework
• Develop processes for formal compliance measurement of
governance mechanisms.
Organisation
Policies
Standards &
Processes
Founded on Principles
20
Technology

21. Technology overview
• An appropriate area of the organisation should provide Information
Architecture representation within the Data Governance Organisation.
This representation is essential to ensure compliance with enterprise
information management frameworks and standards
• There is also a need to provide tools and technology practice capability
to the Data Organisation to enable analysis, documentation, data
quality assessment and compliance measurement
• There are key enabling information management capabilities that are
important to achieving and sustaining excellence in Data Management
(pictured right). Some of these may fall outside of the domain of the
Data Governance Organisation
• Strategy development and robust governance functions around all
enabling information management capabilities should be defined at the
Enterprise level.
Managing Information
as a Strategic Asset
Key point
The data governance organisation and capabilities should integrate with, rather than
overlay, business as usual processes and key functions required for broader information
and technology management
Governance Framework
Organisation
Policies
Standards &
Processes
Founded on Principles
21
Technology

22. Conceptual data governance model
Managing Information
as a Strategic Asset
Governance Framework
Organisation
Policies
Standards &
Processes
Technology
Founded on Principles
Data governance
Governance organisation capabilities
Data owners
Support functions
Executive
sponsor(s)
Governance lead
Technology and change/comms specialists
Governance working teams
“Information specialists”
Business data stewardship
22

23. Conceptual data governance model - typical current status
Managing Information
as a Strategic Asset
Governance Framework
Organisation
Policies
Standards &
Processes
Technology
Founded on Principles
Data governance
Governance organisation capabilities
Usually missing
Skills challenged
(outside technology)
Data owners
Business as usual
Support functions
Executive
sponsor(s)
Governance lead
Governance working team
“Information specialists”
Business data stewardship
23
Technology and change/comms specialists

24. Organisational capabilities in more detail
Functional capability
Description
Basis
Executive sponsor(s)
• Facilitates the setting of strategic direction for data management
• Provide visible executive and senior management support for the Data Governance.
Demand
driven
Data owners
• Data owners from across process and business unit lines - leaders for each data subject
area
• Reviews and approves required policies, standards and processes
• Clear accountability for all aspects of data governance for their subject area.
Demand
driven
Governance lead
• Responsible for the day to day operation of the data organisation, across subject area,
process and business unit boundaries
• Custodian of all data governance processes from definition through to execution and
continuous improvement.
Full time
Governance working
team
• Serves as information specialists for their data subject
• Group that defines and executes corporate data policies, standards and processes
• Provides recommendations for continuous improvement and monitoring.
Demand
driven
Support functions
Business
stewardship
24
•
•
•
•
Supports in creating data management policies, standards and processes
Ensures consistency and quality across different types of data.
Create and administrate the Issue Tracking and Resolution process
Establish a program to effectively communicate data governance to the business and
technology community, including supporting training activities
• Designs and implements regular compliance reviews against policies and standards.
• Business personnel who maintain the data in the systems
• Enters and maintains the data following established data standards, polices, and
procedures
• Manage operational based issues and conduct initial impact assessment.
Part/full
time
shared
Part/full
time
shared

25. Operating view of the data governance organisation
Managing Information
as a Strategic Asset
Governance Framework
Organisation
Provides executive
support and budget
approval
Data Ownership functions are
expected to have infrequent
day-to-day involvement
however will be accountable
for their data subjects
Data owner
Data owner
Governance lead
Escalation of issues
that cannot be resolved
by the Working Team
Issue resolution and
endorsement of
developed governance
mechanisms
Provides
guidelines and
task direction
Facilitate impact
assessment and
issues management
processes
Support functions
Governance working teams
Data quality mgt
Subject area
Subject area
Subject area
Proposes new ideas and
policies, standards and
processes
Work together to
develop
standards, analyse
issues and manage
data issues
Metadata mgt
Change management
Issue management
Measure and
communication
compliance with
standards
Support
issue
management
process
Raises Issues
and concerns
Business data stewardship
Data steward community
Data Stewards
Data Stewards
Data Stewards
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Contributes to a
body of knowledge
Technology
Request for budget
and status reports
Data owners
Data owner
Standards &
Processes
Founded on Principles
Executive
sponsor(s)
The domain data
management function have
delegated authority to make
agreed decisions as
authorised by the data owners
Policies
Subject processes
Subject processes
Subject processes
Provide tools and
technology
capabilities
Information
technology

26. Managing Information
as a Strategic Asset
Data governance organisation in health care provider
Governance Framework
Organisation
Policies
Standards &
Processes
Technology
Founded on Principles
CXX
Governance working teams relate to
the information groups from the
information model shown earlier.
Seek to keep core teams smaller and
engage other people as required
Provides executive
support and budget
approval
Request for budget
and status reports
Data owners should be selected
on the basis of relevance to
information groups and subjects
within them as well as having a
suitable level of authority to
make and ratify related decisions
Data owners
Health
information
manager
Business
manager(s)
Operations
managers
Quality manager
The domain data management function
have delegated authority to make agreed
decisions as authorised by the data
owners
Finance
manager
Education &
research
manager
HR manager
Governance lead
Escalation of issues
that cannot be resolved
by the Working Team
Governance working teams
Issue resolution and
endorsement of
developed governance
mechanisms
Facilitate impact
assessment and
issues management
processes
Provides
guidelines and
task direction
Data Ownership functions are
expected to have infrequent
day-to-day involvement however will
be accountable for their data subjects
Support functions
Patient and
clinical care
Non-clinical
care support
Operational
support
Business
support
Education &
research
Human
resources
Audit and risk
Finance
Data quality mgt
Work together to
develop
standards, analyse
issues and manage
data issues
Proposes new ideas and
policies, standards and
processes
Existing roles operating with
Raises Issues
suitable principles,
and concerns
standards and training
supported by systems and
Data steward community
issue resolution processes
Data Stewards
Data Stewards
Data Stewards
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Metadata mgt
Change management
Issue management
Measure and
communication
compliance with
standards
Support
issue
management
process
Business data stewardship
Patient care
processes
HR processes
Finance processes
Contributes to a
body of knowledge
etc
Provide tools and
technology
capabilities
Information
technology

27. Data governance RACI model
This table shows a view of functional responsibilities across the data governance areas
Master data subjects
Executive sponsor(s)
Policies
Standards
Processes
Executive sponsor is accountable for mandating the MDM Governance Organisation
charter and ensuring its effective execution
Governance lead
C
R
R
A
Data ownership
A
A
A
R
Domain data management
R
R
R
C
Data quality management
C
C
C
C
Metadata management
C
C
C
C
Comms and change management
I
C
C
C
Issues management
I
I
I
C
Data stewardship
R
C
C
I
R: Responsible | A: Accountable | C: Consulted | I: Informed
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28. The $64,000 question – justifying the exercise
Attempting to justify a complete whole-of-enterprise data governance exercise on the basis of principles will fail (at least
experience shows that this is very unlikely to be approved or to succeed).
Opportunities to consider include:
Key point
Attach data governance
initiatives to something that
already matters and is on the
executive agenda
• Responding to a problem that has occurred. The danger here is that this has a strong
tendency to remain narrowly focused on a one-time approach to addressing the effect of
the problem rather than fixing the cause and preventing further occurrences by
institutionalising the changes required
• Focusing on a single important data subject area and deliberately establishing only a
basic capability to contain scope, cost and risk. However, it may still be difficult to justify
in terms of benefits unless there significant known issues so focus in information
imperative areas
• Leveraging a systems project that will require data migration to justify the effort
required to handle data related work soundly and transition the management capability
into business as usual. In other words, incubate the capability in the context of a project
and sustain beyond the project
• Searching through the benefits in business cases of substantial approved projects
for benefits that are strongly data-linked and unlikely to deliver the planned benefit unless
there is an appropriate effort put into managing associated data quality. This can expose
“business value at risk” or benefit shortfall. Generally the cost of addressing the required
data governance is much less than the project and can be positioned as a worthwhile
supplementary activity
• Align with process improvement initiatives which almost always have a significant
relationship with data. Process improvement is usually short lived or limited if the
associated data governance is not also addressed as part of the change.
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29. Business value model
Consider using a value driver model of some kind that allows business functions to be viewed in
terms of the business value they produce and therefore confers a corresponding level of
importance on the data that these functions need to operate effectively and efficiently.
Data value can then be linked to the business value delivered by the function.
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30. Some guidelines for tackling data governance
• There is no magic bullet for data governance (or the data quality that is a common goal)
• Have a framework (such as the one we have presented) to provide some context for
whatever activity is undertaken so that there is some leverage and convergence over time
Key point
Build to a framework but
deploy in small focused
steps with an emphasis on
ensuring
changes, monitoring and
management are integral
to business as usual. It is
better to have modest
complete portions than a
broad based initiative that
remains incomplete.
• Build the data governance arrangements into the business as usual organisation or they
will evaporate
• Execute modestly scoped activities in areas that are a clear priority
• While it is reasonable to have a plan in mind, recognise that you should only move forward
at a pace and to an extent where there is support and relevance. Expansion is likely to
cease when enough has been done which is certain to be well short of implementing a
completely comprehensive approach to data governance across the enterprise
• Take steps with permanence in mind. A once-of improvement in data quality achieves little
over the longer term if the required governance is not assimilated going forward
• Data governance is not a spectator sport – it is a team participation sport. It can only take
place effectively when people understand the purpose, know that they are on the team and
know what there role is
• The adage that “what gets measured gets managed” is true when bit comes to data quality.
Even very basic data quality reporting helps instil it as a relevant business activity
• Keep it simple – for example just go for a basic data dictionary in the first instance
• Implement the governance organisation as data subjects are addressed
• Implement data quality reporting as subject areas are addressed.
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