Date post: | 26-Jun-2015 |
Category: |
Technology |
Upload: | ark-group-australia |
View: | 256 times |
Download: | 0 times |
The Various Roles and Challenges Associated with Information Governance Implementation
12 December 2010
Tatiana StebakovaManager Information and Standards at National eHealth Transition Authority (NEHTA)
About NEHTA
The National E-Health Transition Authority Limited (NEHTA)
was established by the Australian Commonwealth, State and Territory governments on 5 July, 2005 to develop better ways of electronically collecting and securely exchanging health information.
Presentation contents
• Why Information governance must concern senior management and executives? Information quality governance as a strategy for risk avoidance
• The various roles associated with information governance and challenges associated with information governance implementation
• From information creators to users: why should everyone be part of information governance?
• Data Governance implementation in action (example of Information quality governance implementation for the National Unique Healthcare Identification Services)
Why Information governance must concern senior management and executives?
Information quality governance as a strategy for risk avoidance
In 1805, the Austrian and Russian Emperors agreed to join forces against Napoleon. The Russians promised that their forces would be in the field in Bavaria by Oct. 20.
The Austrian staff planned its campaign based on that date in the Gregorian calendar. Russia, however, still used the ancient Julian calendar, which lagged 10 days behind.
The calendar difference allowed Napoleon to surround Austrian General Mack's army at Ulm and force its surrender on Oct. 21, well before the Russian forces could reach him, ultimately setting the stage for Austerlitz.
Source: David Chandler, The Campaigns of Napoleon, New York: MacMillan 1966, pg. 390,cited by R. Wang.
Begin from the beginning
40 billion reasons to spend money on Data Quality
• Wanted to sell 1 share for 600,000 yen
• Sold 600,000 shares for 1 yen• 40 billion yen loss (133 millions)• System did not have limit
checking and did not allow order cancellation
Data Quality and National Security
From information creators to users: why should everyone be part of information governance?
Information Factory
Data Stewardship v. Data Governance
Data Governance
is high level policy
making and arbitration
on data decisions
Data Stewardship
Day-to-day data
management activities to ensure that data meets stakeholders expectations
–Strategic level–Tactical level–Operational level
"Studies in cost analysis show that between 15% to > 20% of a company’s operating revenue is spent doing things to get around or fix data quality issues" Larry English, Information Impact International, Inc
14 Deming Points Pat Oliphant's Illustrations
Data Governance implementation in action -
National Unique Healthcare Identification Services
Data Quality Strategy
Page 14
Dat
a
Qu
alit
y S
trat
egy
Data Quality Implementation Roadmap
Data Quality Maturity Model
Level 1 – InitialLevel 2 – Repeatable Level 3 – DefinedLevel 4 – ManagedLevel 5 - Optimized
Data Quality Dimensions 1. Semantic2. Structure3. Provenance4. Completeness5. Consistency6. Currency7. Timeliness8. Accuracy9. Fitness for Use10. Compliance11. Quality rating
Data Quality Standards & Practices· Structure and format standards adhered to in all data exchanges· Certification of trusted data sources in place· Community-wide data standards metadata management· Exchange schemas are endorsed through data standards oversight
process
Data Quality Policies & Protocols· Policy-based Data Quality management on individual and at
community level· Data validation protocols· Data Provenance management
Data Quality Technology and Operations Guidelines· Standardization of Technology components across the community · Design and service use guidelines· Standardized techniques and procedures for data validation,
certification, quality assurance, and reporting
Data Quality Performance Management· Measuring conformance to data quality standards, expectations· Identifying where significant negative impacts are incurred due to
poor data quality· Providing longitudinal tracking for identifying and measuring areas
for improvement.
Data Quality GovernanceD
ata
Qu
alit
y F
ram
ew
ork
Data Quality Framework: Governance
Page 15
http://members.ozemail.com.au/~enigman/australia/tas.html
WA DQ Forum
SA DQ Forum
NT DQ Forum
VIC DQ Forum
TAS DQ Forum
DQ Steering Committee
4 members
QLD DQ Forum
ACT DQ Forum MCA HI Operations
Review Forum NEHTA DQ Forum Workgroups (9 members in each group)Public and Private Hospitals WorkgroupTrusted Data Sources (TDS) WorkgroupDiagnostics and Pharmacy Workgroup Primary Care Workgroup (includes allied health)
Jurisdictional Working Party Structure(5 members - each workgroup representative and a chairPublic and Private Hospitals WorkgroupTrusted Data Sources (TDS) WorkgroupDiagnostics and Pharmacy Workgroup Primary Care Workgroup (this will include allied health)
NEHTA DQ Forum Structure:
DQ Forum Director
DQ Technical Certification and Audit
Group5 members
DQ Technical Advisory Group
5 members
DQ Oversight Board
DQ Standards Advisory Group
5 members
NSW DQ Forum
Thank You and Questions