role of analytics in delivering health information to help fight cancer in australia
DESCRIPTION
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, AustraliaTRANSCRIPT
Role of analytics in delivering health information to help fight cancer in Australia
Katerina Andronis (Deloitte, Melbourne)
&Chandana unnithan (Deakin University)
22
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
April 12, 2023
April 12, 2023 33
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 non-clinical 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
April 12, 2023 44
Big Data in HealthData 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.
5
Data Governance – Selected DefinitionsThe 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.
6
Data governance – common themes
Data is an asset
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.
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
7
Data GovernanceWhat 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
8
Sustaining information quality
Measurement and monitoring
Environment and culture
Strategy and governance
Basis of informal research (IAIDQ)Strategy
We have defined and implemented an information quality strategy designed to manage information as an asset
StandardsWe have defined information quality principles, policies, and standards that are used to guide decisions and actions affecting information quality
ManagementWe 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
AccountabilityWe have defined accountabilities for information quality across all functions throughout the organisation
EducationWe actively educate management and staff regarding data quality and our approach to managing it
ProcessPersonnel can readily access the information they need to understand data quality requirements and processes related to their jobs
MeasurementThere are well defined data quality standards, and associated reporting
MonitoringAchievement of data quality standards is actively monitored and compliance is an accountable element of job responsibilities
ProjectsData quality implications are actively and appropriately addressed during computer application implementation or upgrade projects
OperationsInformation quality is explicitly built into our business operations, processes and systems
Question responses
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
Definition
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).
Based loosely on IAIDQ framework
9
Preliminary Results
Haven’t started
Started
Significant progress
Largely completeKey point
Data governance is not a significant capability within health care providers
10
The information challenge for health care providers
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.
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.
11
Health service output functional footprintMany areas are involved directly and indirectly in delivery of funded health care outputs.
Not health service output
funded
Health service output funded
Inpatient
Rapid Assessment
Medical Unit
Services
Education & Research Services
Simulation Services
Clin
ical
Rep
ortin
g (A
udit,
Ris
k &
Per
form
ance
)
Qua
lity
Serv
ices
Real-timeTracking
Real-time Data Access & Capture
Sub-Acute
Inpatient Services Mgmt
External &Onsite Access Public Health Access Hospital Based Access Remote Clinical Access Satellite Site &
Partner AccessHome Access
3rd Party Testing Services
Ambulatory Services Critical Care Mental Health
Care Planning & Management
Emergency Clinical Services
Management
Home & Community Based Care
Services (HIH)
Out-patient Mgmt
Specialty Clinical Service Delivery
Patient ManagementAppointment & Access Management
Patient & Client ManagementCritical Care
Management
HDU & ICU
Services
Cathlab & Cardiology
IPU Services
Theatre Clinical
Care Mgmt
Theatre Services Mgmt
Clinical Care Management
Medical & Surgical
Inpatient Services Mgmt
Women’s/ Children’s
& Paediatric Services Mgmt
CancerIPU
Services
Clin
ical
Kno
wle
dge
Care Delivery Support Services
Pharmacy Services
Pathology Services
Imaging services
Specialist Consulting
Services
Patient Information & Health Records Management
Resources & Appointment Management
Transport Services
Allied Health Services
Interpreter Services
Transcription/ Typing Services
Specialist Testing Services
Document Management
ServiceLibrary Services
Data Extraction, Storage &
Analysis Service
Research Collaboration
ServicesPublishing Services
Research Unit Specific Services
Professional Development &
Education Services
Operational Support Services
Building & Engineering
Maintenance Management
Manage Material
Distribution & Logistics
Laundry Services
Patient & Staff Food Services
Clinical Operations
Support
Equipment Distribution & Management
Business Support Services
Inte
grati
on
Federal Government
Research Networks
State Dept. Health Network
Internet
Patient IDPCEHRPayments
ReportingDirectories
Finance systemClinical systemIdentity
GP/SpecialistProcurement
Patients & Citizens
GPs, Specialists, Multi-Disciplinary Teams & Tele-medicine
Remote monitoringTele-medicine
Mortuary Services
Cleaning Services
Mail Room & Courier Services
Transit Lounge Services
Waste ServicesBiomedical Engineering
Services
Inci
dent
Re
porti
ng &
M
anag
emen
tAu
dit S
ervi
ces
Risk
M
anag
emen
t &
Conti
nuou
s Im
prov
emen
t
Mental Health
Inpatient Services Mgmt
Community Services Mgmt
Ambulatory Services Mgmt
Exte
rnal
Clin
ical
Kn
owle
dge
Sour
ces
Inte
rnal
Clin
ical
Kn
owle
dge
Sour
ces
Emergency Management
Medi-Hotel
Manage Accounting &
Financial Decision Support
Manage Capital & Risk
Human Resource
Management
Manage Capital
ProjectsManage Payroll
Manage Staff Rostering
Procure Materials &
ServicesICT
ManagementPlan & Manage
Business
Business/ Statutory
Reporting & Analysis
Volunteer & Fundraising
Services
Customer Mgmt
Hotel Services
Security Services
Management
Corporate Network
Other Network
Reception & Switchboard Management
Customer Service
Management
Legal Services Management
12
Health service output revenue information footprint
Financial management
Human resources
Education and research
Businesssupport
Audit and risk
Patient Administration Operational support Business support Audit & RiskClinical care delivery support
Stra
tegi
c A
lignm
ent
Dec
isio
n Su
ppor
t
Patient care services
Clinical care support
Operational support
Non -clinical care support
Education & Research
Non -Clinical care delivery
support
Clinical results Operational support mgt data
Recruitment and Terminations
Payroll
Education content
Procurement
Legal services data
Risk data
Revenue
Volunteer and fundraising
Rostering
Audit data
Credentialing
Volunteer & Fundraising
Pathology
Medical images
Project Accounting
Billing data
Clinical Care costing analysis
Capacity planningPatient flow analysis Business and capital planning
Inventory management
Clinical Care Support utilisation analysis
Capital project management
Costing and funding analysis
Research project management
Rostering and workload analysis
Education service delivery
Remuneration analysis
Training and accreditation
Incident reporting and management
Quality monitoring and analysis
Audit/risk mgt planning Financing strategy
Capital analysis
Cost analysis
Revenue analysis
Research projects
Education events and records
Risk management
Customer service data
Operational support services
Supply and inventory
Demographic data
Inpatient episodic data
Dim
ensi
ons
Info
rmati
on G
roup
s an
d Su
bjec
tsD
ata
sour
ces
Costing
General Ledger
Education and research strategy
Capacity planning
Patient Care Services utilisation analysis
Incident data
Ambulatory event data
Clinical coding data
Medication data
Clinical information
Appointments
Care delivery support events
Care delivery support resources
Research data
Publications
Employees
Employee performance
Asset accounting
Capital projects
Security management data
Engineering and maintenance
Radiology
Specialist clinical
Medication management
Mental Health
Anaesthetic
TheatreTransport
management
Resource scheduling
Dictation system
Publishing
Research
Library
Document management
Capital Project
Financial
Asset
Rostering Quality
RiskHuman
Resources
Payroll
Credentialing
Procurement
Legal Services
Security Services
Audit
Client management
Community care
Emergency department
management
Patient billing
ICD coding
Patient Admin System
Biomedical engineering
Cleaning services
Building and engineering
maintenance
Food services
Laundry
Supply
Equipment management
Mortuary
Waste management
Customer service
management
Call Management
Casemix funding
Service delivery management
Capacity planning
Service delivery management
Costing analysis
Capacity planning
Service delivery management
Costing analysis
Operation Support utilisation analysis
Workforce capacity planning
Personnel management
Asset managementCasemix funding
Patient care costing analysis
Service delivery management
Accreditation compliance
Non-clinical Care utilisation analysis
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
Other cost element
Direct cost element
Indirect cost
element
Inpatient
Rapid Assessment
Medical Unit
Services
Education & Research Services
Simulation Services
Clin
ical
Rep
ortin
g (A
udit,
Ris
k &
Per
form
ance
)
Qua
lity
Serv
ices
Real-timeTracking
Real-time Data Access & Capture
Sub-Acute
Inpatient Services Mgmt
External &Onsite Access Public Health Access Hospital Based Access Remote Clinical Access Satellite Site &
Partner AccessHome Access
3rd Party Testing Services
Ambulatory Services Critical Care Mental Health
Care Planning & Management
Emergency Clinical Services
Management
Home & Community Based Care
Services (HIH)
Out-patient Mgmt
Specialty Clinical Service Delivery
Patient ManagementAppointment & Access Management
Patient & Client ManagementCritical Care
Management
HDU & ICU
Services
Cathlab & Cardiology
IPU Services
Theatre Clinical
Care Mgmt
Theatre Services Mgmt
Clinical Care Management
Medical & Surgical
Inpatient Services Mgmt
Women’s/ Children’s
& Paediatric Services Mgmt
CancerIPU
Services
Clin
ical
Kno
wle
dge
Care Delivery Support Services
Pharmacy Services
Pathology Services
Imaging services
Specialist Consulting
Services
Patient Information & Health Records Management
Resources & Appointment Management
Transport Services
Allied Health Services
Interpreter Services
Transcription/ Typing Services
Specialist Testing Services
Document Management
ServiceLibrary Services
Data Extraction, Storage &
Analysis Service
Research Collaboration
ServicesPublishing Services
Research Unit Specific Services
Professional Development &
Education Services
Operational Support Services
Building & Engineering
Maintenance Management
Manage Material
Distribution & Logistics
Laundry Services
Patient & Staff Food Services
Clinical Operations
Support
Equipment Distribution & Management
Business Support Services
Inte
grati
on
Federal Government
Research Networks
State Dept. Health Network
Internet
Patient IDPCEHRPayments
ReportingDirectories
Finance systemClinical systemIdentity
GP/SpecialistProcurement
Patients & Citizens
GPs, Specialists, Multi-Disciplinary Teams & Tele-medicine
Remote monitoringTele-medicine
Mortuary Services
Cleaning Services
Mail Room & Courier Services
Transit Lounge Services
Waste ServicesBiomedical Engineering
Services
Inci
dent
Re
porti
ng &
M
anag
emen
tAu
dit S
ervi
ces
Risk
M
anag
emen
t &
Conti
nuou
s Im
prov
emen
t
Mental Health
Inpatient Services Mgmt
Community Services Mgmt
Ambulatory Services Mgmt
Exte
rnal
Clin
ical
Kn
owle
dge
Sour
ces
Inte
rnal
Clin
ical
Kn
owle
dge
Sour
ces
Emergency Management
Medi-Hotel
Manage Accounting &
Financial Decision Support
Manage Capital & Risk
Human Resource Management
Manage Capital
ProjectsManage Payroll Manage Staff
RosteringProcure
Materials & Services
ICT Management Plan & Manage Business
Business/ Statutory
Reporting & Analysis
Volunteer & Fundraising
Services
Customer Mgmt
Hotel Services
Security Services Management
Corporate Network
Other Network
Reception & Switchboard Management
Customer Service
Management
Legal Services Management
14
Service costing information footprint
Financial management
Human resources
Education and research
Businesssupport
Audit and risk
Patient Administration Operational support Business support Audit & RiskClinical care delivery support
Stra
tegi
c A
lignm
ent
Dec
isio
n Su
ppor
t
Patient care services
Clinical care support
Operational support
Non -clinical care support
Education & Research
Non -Clinical care delivery
support
Clinical results Operational support mgt data
Recruitment and Terminations
Payroll
Education content
Procurement
Legal services data
Risk data
Revenue
Volunteer and fundraising
Rostering
Audit data
Credentialing
Volunteer & Fundraising
Pathology
Medical images
Project Accounting
Billing data
Clinical Care costing analysis
Capacity planningPatient flow analysis Business and capital planning
Inventory management
Clinical Care Support utilisation analysis
Capital project management
Costing and funding analysis
Research project management
Rostering and workload analysis
Education service delivery
Remuneration analysis
Training and accreditation
Incident reporting and management
Quality monitoring and analysis
Audit/risk mgt planning Financing strategy
Capital analysis
Cost analysis
Revenue analysis
Research projects
Education events and records
Risk management
Customer service data
Operational support services
Supply and inventory
Demographic data
Inpatient episodic data
Dim
ensi
ons
Info
rmati
on G
roup
s an
d Su
bjec
tsD
ata
sour
ces
Costing
General Ledger
Education and research strategy
Capacity planning
Patient Care Services utilisation analysis
Incident data
Ambulatory event data
Clinical coding data
Medication data
Clinical information
Appointments
Care delivery support events
Care delivery support resources
Research data
Publications
Employees
Employee performance
Asset accounting
Capital projects
Security management data
Engineering and maintenance
Radiology
Specialist clinical
Medication management
Mental Health
Anaesthetic
TheatreTransport
management
Resource scheduling
Dictation system
Publishing
Research
Library
Document management
Capital Project
Financial
Asset
Rostering Quality
RiskHuman
Resources
Payroll
Credentialing
Procurement
Legal Services
Security Services
Audit
Client management
Community care
Emergency department
management
Patient billing
ICD coding
Patient Admin System
Biomedical engineering
Cleaning services
Building and engineering
maintenance
Food services
Laundry
Supply
Equipment management
Mortuary
Waste management
Customer service
management
Call Management
Casemix funding
Service delivery management
Capacity planning
Service delivery management
Costing analysis
Capacity planning
Service delivery management
Costing analysis
Operation Support utilisation analysis
Workforce capacity planning
Personnel management
Asset managementCasemix funding
Patient care costing analysis
Service delivery management
Accreditation compliance
Non-clinical Care utilisation analysis
15
Compliance requirements and standardsPrivacy 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:
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.
Key point
Data governance appears to be largely confined to a direct response to mandatory compliance areas
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
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
Provides the high level objectives for DM Policies
Direct the formalisation of standards to achieve an outcome
Provides the boundaries for the processes to achieve the standards
Provides traceable requirements to principles
Informs how & when policies will be executed and compliance measured
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.
Standards
Define the minimum requirements for data management, including data definition, quality and control standards to deliver upon the policies of the organisation.
Policies
The mechanism for translating guiding principles into pragmatic, actionable and measurable organisational objectives which will deliver upon the overarching objectives of DM
Guiding principles
Foundational capabilities required to achieve excellence in Data Management
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 dataPromote global enterprise stewardship of information in accordance with defined data policies, standards and processes.
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
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.
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
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
• Develop processes for formal compliance measurement of governance mechanisms.
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
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.
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
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
22
Conceptual data governance model Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
Executive sponsor(s)
Support functions
Business data stewardship
Governance working teams
Data owners
Governance organisation capabilities
“Information specialists”
Technology and change/comms specialistsGovernance lead
Data governance
23
Conceptual data governance model - typical current status
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
Executive sponsor(s)
Support functions
Business data stewardship
Governance working team
Data owners
Governance organisation capabilities
“Information specialists”
Technology and change/comms specialistsGovernance lead
Data governance Usually missing
Skills challenged(outside technology)
Business as usual
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
• 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.
Part/full timeshared
Business stewardship
• 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 timeshared
25
Operating view of the data governance organisation
Executive sponsor(s)
Business data stewardship Data steward community
Data StewardsData StewardsData Stewards
Subject processes
Governance working teams
Subject area Subject area
Data owners
Data owner Data owner
Governance lead
Data owner
Information technology
Facilitate impact assessment and issues management processes
Contributes to a body of knowledge
Raises Issues and concerns
Measure and communication
compliance with standards
Proposes new ideas and policies, standards and
processes
Escalation of issues that cannot be resolved
by the Working Team
Work together to develop standards, analyse issues and manage data issues
Issue resolution and endorsement of developed governance mechanisms
Provides guidelines and task direction
Provides executive support and budget
approval
Provide tools and technology capabilities
Request for budget and status reports
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
Subject processesSubject processes
Data Ownership functions are expected to have infrequent day-to-day involvement however will be accountable for their data subjects
The domain data management function have delegated authority to make agreed decisions as authorised by the data owners
Support issue management process
Support functions
Data quality mgt
Change management Issue management
Metadata mgtSubject area
26
Data governance organisation in health care provider
CXX
Business data stewardship
Data steward community
Data StewardsData StewardsData Stewards
Finance processes
Governance working teams
Patient and clinical care
Non-clinical care support
Operational support
Data owners
Health information manager
Business manager(s)
Operations managers
Information technology
Facilitate impact assessment and issues management processes
Raises Issues and concerns
Measure and communication
compliance with standards
Escalation of issues that cannot be resolved
by the Working Team
Issue resolution and endorsement of developed governance mechanisms
Provides guidelines and task direction
Provides executive support and budget
approval
Provide tools and technology capabilities
Request for budget and status reports
Organisation
Founded on Principles
Policies Technology Standards &Processes
Governance Framework
Managing Information as a Strategic Asset
HR processesPatient care processes
Data Ownership functions are expected to have infrequent day-to-day involvement however will be accountable for their data subjects
The domain data management function have delegated authority to make agreed decisions as authorised by the data owners
Support issue management process
Support functions
Data quality mgt
Change management Issue management
Metadata mgt
Business support
Education & research
Human resources
Audit and risk Finance
Education & research manager
Quality managerFinance manager HR manager
etc
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
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
Existing roles operating with suitable principles, standards and training supported by systems and issue resolution processes
Contributes to a body of knowledge
Proposes new ideas and policies, standards and
processes
Work together to develop standards, analyse issues and manage data issues
Governance lead
27
Data governance RACI model
Master data subjects Policies Standards Processes
Executive sponsor(s)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
This table shows a view of functional responsibilities across the data governance areas
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:
• 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.
Key point
Attach data governance initiatives to something that already matters and is on the executive agenda
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Business value modelConsider 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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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
• 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.
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.